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  • Opportunities for AI in Accessibility

    Opportunities for AI in Accessibility

    I was completely moved by Joe Dolson’s current article on the crossroads of AI and availability because I found it to be both skeptical about how widespread use of AI is. Despite working for Microsoft as an affordability technology strategist and managing the AI for Accessibility grant program, I’m pretty skeptical of AI. As with any tool, AI can be used in quite productive, equitable, and visible ways, and it can also be used in dangerous, unique, and dangerous ones. Additionally, there are a lot of uses in the subpar center as well.

    I’d like you to consider this a “yes … and” piece to complement Joe’s post. Instead of refuting everything he’s saying, I’m pointing out some areas where AI may produce real, positive impacts on people with disabilities. To be clear, I’m not saying that there aren’t true threats or pressing problems with AI that need to be addressed—there are, and we’ve needed to address them, like, yesterday—but I want to take a little time to talk about what’s possible in hope that we’ll get there one day.

    Other text

    Joe’s article spends a lot of time examining how computer vision models can create other word. He raises a lot of valid points about the state of the world right now. And while computer-vision concepts continue to improve in the quality and complexity of information in their information, their benefits aren’t wonderful. As he rightly points out, the state of image research is currently very poor, especially for some graphic types, in large part due to the lack of context for which AI systems look at images ( which is a result of having separate “foundation” models for words analysis and picture analysis ). Today’s models aren’t trained to distinguish between images that are contextually relevant ( that should probably have descriptions ) and those that are purely decorative ( which might not need a description ) either. Nonetheless, I still think there’s possible in this area.

    As Joe mentions, human-in-the-loop publishing of alt word should definitely be a factor. And if AI can intervene and provide a starting point for alt text, even if the swift reads,” What is this BS?” That’s certainly correct at all … Let me try to offer a starting point— I think that’s a win.

    If we can specifically teach a design to consider image usage in context, it might be able to help us more swiftly distinguish between images that are likely to be beautiful and those that are more descriptive. That will clarify which situations require image descriptions, and it will increase authors ‘ effectiveness in making their sites more visible.

    The image example provided in the GPT4 announcement provides an interesting opportunity as well, even though complex images like graphs and charts are challenging to describe in any kind of succinct way ( even for humans ). Let’s say you came across a map that was simply the description of the chart’s name and the type of representation it was: Pie map comparing smartphone usage to have phone usage in US households earning under$ 30, 000 annually. ( That would be a pretty bad alt text for a chart because it would frequently leave many unanswered questions about the data, but let’s just assume that that was the description in place. ) Imagine a world where people could ask questions about the vivid if their browser knew that the image was a dessert chart ( because an ship model concluded this ).

    • Would more people use smartphones or other types of phones?
    • How many more?
    • Exists a group of people who don’t fall under either of these categories?
    • How many is that?

    Setting aside the realities of large language model ( LLM) hallucinations—where a model just makes up plausible-sounding “facts” —for a moment, the opportunity to learn more about images and data in this way could be revolutionary for blind and low-vision folks as well as for people with various forms of color blindness, cognitive disabilities, and so on. It might also be helpful in education settings to assist those who can view these graphs as they are able to comprehend the information in the charts.

    What if you could request your website to make a complicated map simpler? What if you asked it to separate a single line from a range curve? What if you could request your computer to transform the different lines ‘ colors so they match your color blindness better? What if you demanded that it switch shades in favor of habits? Given these resources ‘ chat-based interface and our existing ability to manipulate photos in today’s AI devices, that seems like a chance.

    Now imagine a specially designed model that could take the data from that map and transfer it to another format. For example, perhaps it could turn that pie chart ( or better yet, a series of pie charts ) into more accessible ( and useful ) formats, like spreadsheets. That would be awesome!

    Matching techniques

    When Safiya Umoja Noble chose to put her reserve Algorithms of Oppression, she hit the nail on the head. Although her book focused on the way that search engines can foster racism, I believe it’s equally true that all machine types have the potential to foster issue, prejudice, and hatred. We all know that poorly designed and maintained algorithms are incredibly harmful, whether it’s Twitter that keeps bringing you the most recent tweet from a drowsy billionaire, YouTube that keeps us in a q-hole, or Instagram that keeps us guessing what natural bodies look like. A large portion of this is attributable to the lack of diversity in those who create and shape them. When these platforms are built with inclusively baked in, however, there’s real potential for algorithm development to help people with disabilities.

    Take Mentra, for example. They serve as a network of employment for people who are neurodivers. They match job seekers with potential employers using an algorithm based on more than 75 data points. On the job-seeker side of things, it considers each candidate’s strengths, their necessary and preferred workplace accommodations, environmental sensitivities, and so on. On the employer side, it considers each work environment, communication factors related to each job, and the like. Mentra made the decision to change the script when it came to typical employment websites because it was run by neurodivergent people. They lower the emotional and physical labor on the job-seeker side of things by recommending available candidates to companies who can then connect with job seekers that they are interested in.

    When more people with disabilities are involved in developing algorithms, this can lower the likelihood that these algorithms will harm their communities. That’s why diverse teams are so important.

    Imagine if a social media company’s recommendation engine was tuned to prioritize follow recommendations for people who discussed topics similar to those that were important but who were different from your current sphere of influence in some fundamental ways. For instance, if you were to follow a group of non-disabled white male academics who talk about AI, it might be advisable to follow those who are disabled, aren’t white, or aren’t men who also talk about AI. If you took its recommendations, perhaps you’d get a more holistic and nuanced understanding of what’s happening in the AI field. These same systems should also use their understanding of biases about particular communities—including, for instance, the disability community—to make sure that they aren’t recommending any of their users follow accounts that perpetuate biases against (or, worse, spewing hate toward ) those groups.

    Other ways that AI can helps people with disabilities

    If I weren’t attempting to combine this with other tasks, I’m sure I could go on and on, giving various examples of how AI could be used to assist people with disabilities, but I’m going to make this last section into a bit of a lightning round. In no particular order:

      Voice preservation. You may have seen the VALL-E paper or Apple’s Global Accessibility Awareness Day announcement or you may be familiar with the voice-preservation offerings from Microsoft, Acapela, or others. It’s possible to train an artificial intelligence model to mimic your voice, which can be incredibly helpful for those who have ALS ( Lou Gehrig’s disease ) or motor-neuron disease or other medical conditions that can make it difficult to talk. This is, of course, the same tech that can also be used to create audio deepfakes, so it’s something that we need to approach responsibly, but the tech has truly transformative potential.
    • Voice recognition. Researchers are assisting people with disabilities in the collection of recordings of people with atypical speech, thanks to the assistance of the Speech Accessibility Project. As I type, they are actively recruiting people with Parkinson’s and related conditions, and they have plans to expand this to other conditions as the project progresses. More people with disabilities will be able to use voice assistants, dictation software, and voice-response services as a result of this research, which will lead to more inclusive data sets that enable them to use their computers and other devices more effectively and with just their voices.
    • Text transformation. The most recent generation of LLMs is quite capable of changing existing text without giving off hallucinations. This is incredibly empowering for those who have cognitive disabilities and who may benefit from text summaries, simplified versions, or even text that has been prepared for Bionic Reading.

    the value of various teams and data

    We must acknowledge that our differences matter. The intersections of the identities we live in have an impact on our lived experiences. These lived experiences—with all their complexities ( and joys and pain ) —are valuable inputs to the software, services, and societies that we shape. The data we use to train new models must be based on our differences, and those who provide it to us need to be compensated for doing so. Inclusive data sets produce stronger models that promote more justifiable outcomes.

    Want a model that doesn’t demean or patronize or objectify people with disabilities? Make sure that you include information about disabilities that has been written by people with a variety of disabilities in the training data.

    Want a model that doesn’t use ableist language? You might be able to use already-existing data sets to create a filter that can read and interpret ableist language before it is read. That being said, when it comes to sensitivity reading, AI models won’t be replacing human copy editors anytime soon.

    Want a copilot for coding that provides recomprehensible recommendations after the jump? Train it on code that you know to be accessible.


    I have no doubt that AI can and will harm people … today, tomorrow, and well into the future. But I also believe that we can acknowledge that and, with an eye towards accessibility ( and, more broadly, inclusion ), make thoughtful, considerate, and intentional changes in our approaches to AI that will reduce harm over time as well. Today, tomorrow, and well into the future.


    Many thanks to Kartik Sawhney for helping me with the development of this piece, Ashley Bischoff for her invaluable editorial assistance, and, of course, Joe Dolson for the prompt.

  • The Wax and the Wane of the Web

    The Wax and the Wane of the Web

    When you begin to believe you have everything figured out, everything will change. This is a one piece of advice I can give to friends and family when they become fresh families. Simply as you start to get the hang of injections, diapers, and ordinary sleep, it’s time for solid foods, potty training, and nighttime sleep. When those are determined, school and occasional sleeps are in order. The pattern continues to go on.

    The same holds true for those of us who are currently employed in design and development. Having worked on the web for about three years at this point, I’ve seen the typical wax and wane of concepts, strategies, and systems. Every day we as developers and designers re-enter the familiar pattern, a brand-new engineering or thought emerges to shake things up and completely alter the world.

    How we got below

    I built my first website in the mid-’90s. Design and development on the web back then was a free-for-all, with few established norms. For any layout aside from a single column, we used table elements, often with empty cells containing a single pixel spacer GIF to add empty space. We styled text with numerous font tags, nesting the tags every time we wanted to vary the font style. And we had only three or four typefaces to choose from: Arial, Courier, or Times New Roman. When Verdana and Georgia came out in 1996, we rejoiced because our options had nearly doubled. The only safe colors to choose from were the 216 “web safe” colors known to work across platforms. The few interactive elements (like contact forms, guest books, and counters) were mostly powered by CGI scripts (predominantly written in Perl at the time). Achieving any kind of unique look involved a pile of hacks all the way down. Interaction was often limited to specific pages in a site.

    The beginning of website standards

    At the turn of the century, a new cycle started. Crufty code littered with table layouts and font tags waned, and a push for web standards waxed. Newer technologies like CSS got more widespread adoption by browsers makers, developers, and designers. This shift toward standards didn’t happen accidentally or overnight. It took active engagement between the W3C and browser vendors and heavy evangelism from folks like the Web Standards Project to build standards. A List Apart and books like Designing with Web Standards by Jeffrey Zeldman played key roles in teaching developers and designers why standards are important, how to implement them, and how to sell them to their organizations. And approaches like progressive enhancement introduced the idea that content should be available for all browsers—with additional enhancements available for more advanced browsers. Meanwhile, sites like the CSS Zen Garden showcased just how powerful and versatile CSS can be when combined with a solid semantic HTML structure.

    Server-side language like PHP, Java, and.NET took Perl as the primary back-end computers, and the cgi-bin was tossed in the garbage bin. With these better server-side instruments came the first time of online applications, starting with content-management systems ( especially in the blog space with tools like Blogger, Grey Matter, Movable Type, and WordPress ). AJAX opened the door to sequential connection between the front end and back end in the mid-2000s. Immediately, websites may update their information without needing to refresh. A grain of JavaScript systems, including Prototype, YUI, and jQuery, were created to aid designers in creating more trustworthy client-side interactions across browsers with wildly varying standards support. Techniques like photo alternative enable skilled manufacturers and developers to use fonts of their choosing. And technology like Flash made it possible to include movies, sports, and even more engagement.

    These new technology, standards, and approaches reinvigorated the market in many ways. As manufacturers and designers explored more diversified styles and designs, website design flourished. However, we also relied heavily on tricks. When it came to basic layout and text styling, early CSS was a significant improvement over table-based layouts, but its limitations at the time meant that designers and developers still relied heavily on images for complex shapes ( such as rounded or angled corners ) and tiled backgrounds for the appearance of full-length columns (among other hacks ). All kinds of nested floats or absolute positioning ( or both ) were necessary for complicated layouts. The big five typefaces were initially influenced by display and photo replacement, but both tricks caused accessibility and performance issues. Additionally, JavaScript libraries made it simple to add a dash of conversation to pages without having to spend the money to double or even quadruple the get size for basic websites.

    The internet as technology platform

    The interplay between the front end and the back end continued to grow, which led to the development of the present time of current web applications. Between expanded server-side programming languages ( which kept growing to include Ruby, Python, Go, and others ) and newer front-end tools like React, Vue, and Angular, we could build fully capable software on the web. Alongside these equipment came others, including creative type control, build technology, and shared bundle libraries. What was once mainly a repository for linked papers has evolved into a world of possibilities.

    At the same time, wireless equipment became more ready, and they gave us online access in our wallets. Mobile applications and flexible style opened up possibilities for fresh relations anytime, anywhere.

    The development of social media and other centralized resources for people to connect and use resulted from this blend of potent portable devices and potent development resources. As it became easier and more popular to interact with others immediately on Twitter, Facebook, and yet Slack, the need for held private websites waned. Social media provided links on a worldwide scale, with both the positive and negative effects.

    Want to learn more about how we came to be where we are today, along with some other suggestions for improvement? ” Of Time and the Web” was written by Jeremy Keith. Or check out the” Web Design History Timeline” at the Web Design Museum. Additionally, Neal Agarwal takes a fascinating journey of” Internet Artifacts.”

    Where we are now

    In the last couple of years, it’s felt like we’ve begun to achieve another big tone place. As social-media programs bone and fade, there’s been a growing interest in owning our personal information again. There are many different ways to create websites, from the tried-and-true classic of hosting plain HTML files to static site generators to content management systems of all kinds. Social media fracturing also has a price: we lose essential infrastructure for discovery and connection. Webmentions, RSS, ActivityPub, and other tools of the IndieWeb can help with this, but they’re still relatively underimplemented and hard to use for the less nerdy. We can create incredible personal websites and update them frequently, but without discovery and connection, it can feel as though we could as well be yelling into the void.

    Browser support for CSS, JavaScript, and other standards like web components has accelerated, especially through efforts like Interop. In a fraction of the time that they once did, new technologies receive universal support. I frequently find out about a new feature and check its browser support only to discover that its coverage is already over 80 %. Browser support is frequently the only obstacle to using newer techniques today, rather than the time it takes to train and adopt new techniques.

    Today, with a few commands and a couple of lines of code, we can prototype almost any idea. With all the tools we currently have, it is simpler than ever to launch a new venture. However, the upfront cost these frameworks may save in initial delivery eventually comes down as the maintenance and upgrading they become a part of our technical debt.

    Adopting new standards can sometimes take longer if we rely on third-party frameworks because we might have to wait for those frameworks to adopt those standards. These frameworks—which used to let us adopt new techniques sooner—have now become hindrances instead. Users must wait for scripts to load before being able to read or interact with pages because these same frameworks frequently come with performance costs. And when scripts fail ( whether through poor code, network issues, or other environmental factors ), there’s often no alternative, leaving users with blank or broken pages.

    Where do we go from here?

    Today’s hacks help to shape tomorrow’s standards. And there’s nothing inherently wrong with embracing hacks —for now—to move the present forward. Problems only arise when we refuse to acknowledge that they are hacks or when we choose not to replace them. What can we do to create the web’s future, then?

    Build for the long haul. Optimize for performance, for accessibility, and for the user. Weigh the costs of those developer-friendly tools. They may make your job a little easier right now, but how do they affect everything else? What’s the cost to users? To future developers? To standards adoption? Sometimes the convenience may be worth it. Sometimes it’s just a hack that you’ve gotten used to. And occasionally, it prevents you from pursuing better options.

    Start from standards. Standards change over time, but browsers have done a remarkably good job of staying current with outdated standards. The same isn’t always true of third-party frameworks. Even the most advanced HTML from the 1990s still function flawlessly today. The same can’t be said about websites created with frameworks even after a few years.

    Design with care. Whether your craft is code, pixels, or processes, consider the impacts of each decision. Many modern tools have the convenience of having the ability to understand the underlying decisions that have led to their creation and to not always consider the effects those decisions can have. Use the time saved by modern tools to think more carefully and make decisions with care rather than rushing to “move fast and break things”

    Always be learning. If you’re always learning, you’re also growing. Sometimes it may be hard to pinpoint what’s worth learning and what’s just today’s hack. Even if you were to concentrate solely on learning standards, you might end up focusing on something that won’t matter next year. ( Remember XHTML? ) However, ongoing learning opens up new neural connections, and the techniques you learn in one day may be useful for guiding future experiments.

    Play, experiment, and be weird! This web that we’ve built is the ultimate experiment. Despite being the single largest human endeavor in human history, each of us has the ability to make their own money there. Be courageous and try new things. Build a playground for ideas. In your own bizarre science lab, conduct absurd experiments. Start your own small business. There has never been a more empowering place to be creative, take risks, and explore what we’re capable of.

    Share and amplify. As you experiment, play, and learn, share what’s worked for you. Write on your own website, post on whichever social media site you prefer, or shout it from a TikTok. Write something for A List Apart! But take the time to amplify others too: find new voices, learn from them, and share what they’ve taught you.

    Go forth and make

    As designers and developers for the web ( and beyond ), we’re responsible for building the future every day, whether that may take the shape of personal websites, social media tools used by billions, or anything in between. Let’s imbue our values into the things that we create, and let’s make the web a better place for everyone. Create something that you are only qualified to make for yourself. Then share it, make it better, make it again, or make something new. Learn. Make. Share. Grow. Rinse and repeat. Every time you think that you’ve mastered the web, everything will change.

  • To Ignite a Personalization Practice, Run this Prepersonalization Workshop

    To Ignite a Personalization Practice, Run this Prepersonalization Workshop

    Photo this. You’ve joined a club at your business that’s designing innovative product features with an focus on technology or AI. Or perhaps your business only started using a personalization website. In any case, you’re using files to design. Then what? There are many warning stories, no immediately achievement, and some guides for the baffled when it comes to designing for customisation.

    The personalization gap is real, between the dream of getting it right and the worry of it going wrong ( like when we encounter “persofails” similar to a company’s constant plea to regular people to purchase additional bathroom seats ). It’s an particularly confusing place to be a modern professional without a map, a map, or a strategy.

    Because successful personalisation is so dependent on each group’s skill, technology, and market position, there are no Lonely Planet and some tour guides for those of you who want to personalize.

    However, you can make sure your team has properly packed its carriers.

    There’s a DIY method to increase your chances for victory. You’ll at least at least disarm your boss ‘ irrational exuberance. You’ll need to properly prepare before the celebration.

    We call it prepersonalization.

    Behind the song

    Take into account Spotify’s DJ element, which debuted this year.

    We’re used to seeing the polished final outcome of a personalization function. A personal have had to be developed, budgeted, and given priority before the year-end prize, the making-of-backstory, or the behind-the-scenes success chest. Before any customisation function is implemented in your product or service, it lives among a long list of thought-provoking concepts that can be used to enhance customer experience more automatically.

    So how do you understand where to position your personalization bet? How can you create regular interactions that didn’t irritate users or worse, breed trust? We’ve found that for many well-known budgeted programs to support their continued investments, they initially required one or more workshops to join vital technologies users and stakeholders. Create it count.

    We’ve closely monitored the same evolution with our consumers, from major software to young companies. How effective these prepersonalization actions play out, in our experiences working on small and large customisation efforts, and how effective is the program’s supreme track record and its ability to weather challenging questions, work steadily toward shared answers, and manage its design and engineering efforts.

    Time and again, we’ve seen successful workshops individual coming success stories from fruitless efforts, saving many time, resources, and social well-being in the process.

    A personalization process involves a year-long process of testing and feature creation. Your technical load is not experiencing a switch-flip. It’s ideal managed as a queue that usually evolves through three methods:

    1. customer experience optimization ( CXO, also known as A/B testing or experimentation )
    2. always-on chatbots, whether they are rules-based or machine-generated.
    3. mature features or standalone product development ( such as Spotify’s DJ experience )

    We think there is a basic language, a set of “nouns and verbs” that your business can use to create experiences that are personalized, personalized, or automated, which is why we created our democratic personalization platform and why we’re field-testing an following deck of cards. These cards are not necessary for you. But we strongly recommend that you create something similar, whether that might be digital or physical.

    Set the timer for your kitchen.

    How long does a prepersonalization workshop take to prepare? The surrounding assessment activities that we recommend including can ( and often do ) span weeks. We suggest aiming for two to three days for the core workshop. Here’s a summary of our more general approach as well as information on the crucial first-day activities.

    The full arc of the wider workshop is threefold:

      Kickstart: This specifies the terms of your engagement as you concentrate on both your team’s and your team’s readiness and drive.
    1. Plan your work: This is where the card-based workshop activities take place, giving you a plan of attack and the scope of work.
    2. Work your plan: This phase is all about creating a competitive environment for team participants to individually pitch their own pilots that each contain a proof-of-concept project, its business case, and its operating model.

    Give yourself at least two days, divided into two long time periods, to work through those initial two phases more effectively.

    Kickstart: Apt your appetite

    We call the first lesson the “landscape of connected experience“. It looks at the possibilities for personalization at your company. Any UX that necessitates the orchestration of multiple systems of record on the backend is a connected experience, in our opinion. This could be a content-management system combined with a marketing-automation platform. It might be a customer-data platform combined with a digital asset manager.

    Give examples of connected experience interactions that you admire, find familiar, or even dislike, as examples of consumer and business-to-business examples. This should cover a representative range of personalization patterns, including automated app-based interactions ( such as onboarding sequences or wizards ), notifications, and recommenders. These are in the cards, which we have a catalog of. To jog your mind, here are 142 different interactions.

    This is all about setting the table. What potential avenues might the practice take in your organization? Here’s a long-form primer and a strategic framework for a broad perspective.

    Assess each example that you discuss for its complexity and the level of effort that you estimate that it would take for your team to deliver that feature ( or something similar ). We break down connected experiences into five categories in our cards: functions, features, experiences, complete products, and portfolios. Here, you can size your own build. This will help to focus the conversation on the merits of ongoing investment as well as the gap between what you deliver today and what you want to deliver in the future.

    Next, have your team plot each concept on the following 2x grid, which lists the four enduring justifications for a personalized experience. This is crucial because it emphasizes how personalization can affect your own methods of working as well as your external customers. It’s also a reminder ( which is why we used the word argument earlier ) of the broader effort beyond these tactical interventions.

    Each team member should vote on where they see your product or service putting its emphasis. You can’t give them all a priority, of course. Here, the goal is to show how various departments may view their own benefits from the effort, which can vary from one department to the next. Documenting your desired outcomes lets you know how the team internally aligns across representatives from different departments or functional areas.

    The third and final kickstart activity is about filling in the personalization gap. Is the customer journey well documented in your business? Will data and privacy compliance be too big of a challenge? Do you have any needs for content metadata that you must address? ( We’re pretty sure you do; it’s just a matter of recognizing the need’s magnitude and its solution. ) In our cards, we’ve noted a number of program risks, including common team dispositions. For instance, our Detractor card lists six intractable behaviors that prevent progress.

    It is crucial to your success to effectively coexist and manage expectations. Consider the potential barriers to your future progress. Ask the participants to list specific actions you can take to help your organization overcome or reduce those obstacles. As research has shown, personalization initiatives face a number of common obstacles.

    You should have at this point discussed sample interactions, emphasized a significant benefit area, and identified significant gaps. Good—you’re ready to continue.

    Hit the test kitchen

    Next, let’s take a look at what you’ll need to create personalization recipes. Personalization engines, which are robust software suites for automating and expressing dynamic content, can intimidate new customers. They give you a variety of options for how your organization can conduct its activities because of their broad and potent capabilities. This raises the question: When creating a connected experience, where do you start?

    What’s important here is to avoid treating the installed software like it were a dream kitchen from some fantasy remodeling project ( as one of our client executives memorably put it ). These software engines are more like test kitchens where your team can begin creating, testing, and improving the snacks and meals that will be a part of your personalizedization program’s constantly evolving menu.

    Over the course of the workshop, the ultimate menu of the prioritized backlog will come together. And by creating “dishes,” you can expect individual team members to create personalized interactions that either serve their or others ‘ needs.

    The dishes will come from recipes, and those recipes have set ingredients.

    Verify your ingredients

    Like a good product manager, you’ll make sure you have everything you need to make your desired interaction ( or that you can figure out what needs to be added to your pantry ) and that you validate with the right stakeholders present. These elements include the audience you’re targeting, content and design elements, the interaction’s context, and your idea of how it’ll come together.

    This isn’t just about discovering requirements. The team can: Identify your personalizations as a series of if-then statements by documenting them as a series of if-then statements.

    1. compare findings to a common strategy for developing features, similar to how artists paint with the same color palette,
    2. specify a consistent set of interactions that users find uniform or familiar,
    3. and establish parity among performance indicators and key performance indicators as well.

    This enables you to streamline your technical and design efforts while delivering a common color palette of the fundamental motifs of your personalized or automated experience.

    Compose your recipe

    What elements are significant to you? Consider a who-what-when-why construct:

    • Who are your key audience segments or groups?
    • What kind of content will you offer them, what design elements, and under what circumstances?
    • And what are the business and user benefits?

    We first developed these cards and card categories five years ago. We regularly test their suitability with clients and audience members at conferences. And we still come across fresh possibilities. But they all follow an underlying who-what-when-why logic.

    In the cards in the accompanying photo below, you can typically follow along with right to left in three examples of subscription-based reading apps.

    1. A guest or an unidentified visitor interacts with a product title and receives a banner or alert bar that makes it simpler for them to read the related title, saving time.
    2. Welcome automation: When there’s a newly registered user, an email is generated to call out the breadth of the content catalog and to make them a happier subscriber.
    3. Winback automation: A user receives an email before their subscription expires or after a recent failed renewal to request that they reconsider renew or request that they be reminded to do so.

    We’ve also found that cocreating the recipes themselves can sometimes be the most effective way to start brainstorming about what these cards might be for your organization. Start with a set of blank cards, and begin labeling and grouping them through the design process, eventually distilling them to a refined subset of highly useful candidate cards.

    The workshop’s later stages could be characterized as shifting from focusing on a cookbook to a more nuanced customer-journey mapping. Individual” cooks” will pitch their recipes to the team using a standard jobs-to-be-done format to ensure consistency and outcomes, and from there, the resulting collection will be prioritized for finished design and production delivery.

    Better kitchens require better architecture

    For those who are actually delivering it, simplifying a customer experience is a challenging task. Beware of anyone who contradicts your advice. With that being said,” Complicated problems can be hard to solve, but they are addressable with rules and recipes“.

    A team overfitting: they aren’t designing with their best data, is what causes personalization to become a laugh line. Every organization has metadata debt to go along with its technical debt, which causes a drag on the effectiveness of personalization, much like a sparse pantry. Your AI’s output quality, for example, is indeed limited by your IA. Before they acquired a seemingly modest metadata startup that now powers its underlying information architecture, Spotify’s poster-child prowess today was unfathomable.

    You can’t stand the heat, unquestionably…

    Personalization technology opens a doorway into a confounding ocean of possible designs. Only a deliberate and cooperative approach will produce the desired outcome. Banish the ideal kitchen. Instead, hit the test kitchen to save time, preserve job satisfaction and security, and safely dispense with the fanciful ideas that originate upstairs of the doers in your organization. There are mouths to feed and meals to be served.

    This framework of the workshop gives you a strong chance at long-term success as well as solid ground. Wiring up your information layer isn’t an overnight affair. However, you’ll have solid ground for success if you use the same cookbook and the same recipes. We created these activities so that you can anticipate the needs of your organization before the hazards become overwhelming.

    While there are associated costs toward investing in this kind of technology and product design, your ability to size up and confront your unique situation and your digital capabilities is time well spent. Don’t waste it. The pudding is the proof, as they say.

  • User Research Is Storytelling

    User Research Is Storytelling

    I’ve been fascinated by shows since I was a child. I loved the figures and the excitement—but most of all the reports. I aspired to be an artist. And I backed up the idea that I would get to do the things Indiana Jones did and have interesting adventures. I also dreamed up suggestions for videos that my friends and I could render and sun in. But they never advanced. However, I did end up in the user experience ( UX) field. Today, I realize that there’s an element of drama to UX— I hadn’t actually considered it before, but consumer analysis is story. And to get the most out of customer studies, you must tell a compelling story that involves stakeholders, including the product team and decision-makers, and piques their interest in learning more.

    Think about your favorite film. More than likely it follows a three-act construction that’s frequently seen in story: the layout, the fight, and the quality. The second act provides an overview of the current events and allows you to understand the characters, their difficulties, and problems. Act two sets the scene for the issue and the action begins. Here, issues grow or get worse. The solution comes in the third and final action. The issues are resolved in this area, and the figures grow and change. I believe that this architecture is also a great way to think about customer study, and I think that it can be particularly helpful in explaining person exploration to others.

    Use story as a framework when conducting research.

    Unfortunately, some people now believe that study is unprofitable. If finances or timelines are strong, analysis tends to be one of the first points to go. Some goods managers rely on developers or, worse, their own mind to make the “right” decisions for customers based on their experience or accepted best practices rather than investing in research. That may get groups a little bit out of the way, but that approach is therefore easily miss out on resolving people ‘ real issues. To be user-centered, this is something we really avoid. User study improves pattern. It provides opportunities and problems while keeping it on record. Being aware of the issues with your goods and reacting to them can help you stay ahead of your competition.

    Each action in the three-act construction corresponds to a specific stage of the process, and each stage is crucial to delivering the full narrative. Let’s take a look at the various functions and how they relate to consumer study.

    Act one: layout

    The fundamental research comes in handy because the layout is all about understanding the background. Foundational research aids in understanding people and identifying their issues ( also known as relational, discovery, or preliminary research ). You’re learning about what exists now, the obstacles people have, and how the problems affect them—just like in the videos. You can conduct contextual inquiries or diary studies ( or both! ) to conduct foundational research. ), which may assist you in identifying both challenges and options. It doesn’t need to be a great investment in time or money.

    Erika Hall writes about the most effective anthropology, which can be as straightforward as spending 15 hours with a customer and asking them to” Walk me through your morning yesterday.” That is it. Provide that one ask. Opened up and spend fifteen minutes listening to them. Do everything in your power to protect both your objectives and yourself. Bam, you’re doing ethnography”. According to Hall, “[This ] will definitely prove quite fascinating. In the unlikely event that you don’t learn anything new or important, move on with more self-assurance in your direction.

    This makes total sense to me. And I adore how consumer research is made so simple. You can simply attract individuals and carry out the recruitment process without having to make a lot of paperwork! This can offer a wealth of knowledge about your customers, and it’ll help you better understand them and what’s going on in their life. Understanding where people are coming from is what action one is really all about.

    Jared Spool discusses the significance of basic research and how it may comprise the majority of your study. If you can pick from any further user data that you can get your hands on, such as surveys or analytics, that can complement what you’ve heard in the fundamental studies or even time to areas that need more research. All of this information helps to reveal both the state of items and its flaws more clearly. And that’s the start of a gripping tale. It’s the place in the story where you realize that the principal characters—or the people in this case—are facing issues that they need to conquer. This is where you begin to develop compassion for the figures and support their success, much like in the movies. And hoped that partners are now doing the same. Their love may be with their company, which could be losing wealth because people didn’t complete certain tasks. Or perhaps they feel the challenges of the users. In either case, work one serves as your main strategy for piqueing interest and investment from the participants.

    When stakeholders begin to understand the value of basic research, that is open doors to more opportunities that involve users in the decision-making approach. And that can help product teams become more user-centric. Everyone benefits from this, including the product, stakeholders, and users. It’s like winning an Oscar in movie terms—it often leads to your product being well received and successful. And this might encourage stakeholders to carry out this process with additional products. The secret to this process is storytelling, and knowing how to tell a compelling story is the only way to entice stakeholders to do more research.

    This brings us to act two, where you iteratively evaluate a design or concept to see whether it addresses the issues.

    Act two: conflict

    Act two is all about approving the issues you raised in act one. This usually involves directional research, such as usability tests, where you assess a potential solution ( such as a design ) to see whether it addresses the issues that you found. The issues might be caused by unmet needs or issues with a flow or process that is causing users to fall asleep. More issues will come up in the process, much like in act two of a movie. It’s here that you learn more about the characters as they grow and develop through this act.

    According to Jakob Nielsen, five users should be typically in usability tests, which means that this number of users can typically identify the majority of the issues:” You learn less and less as you add more and more users because you will keep seeing the same things over and over again… After the fifth user, you are wasting your time by repeatedly observing the same findings but not learning much new.”

    The plot may become lost if you try to tell a story with too many characters, which is similar to storytelling in this case. Having fewer participants means that each user’s struggles will be more memorable and easier to relay to other stakeholders when talking about the research. This can help convey the problems that need to be solved while also highlighting the worth of conducting the research in the first place.

    Usability tests have been conducted in person for tens of thousands of years, but remote testing can also be done using software like Microsoft Teams, Zoom, or other teleconferencing tools. This approach has become increasingly popular since the beginning of the pandemic, and it works well. You might interpret in-person usability tests as a form of theater watching as opposed to remote testing. Each has advantages and disadvantages. In-person usability research is a much richer experience. The sessions can be had by stakeholders with other stakeholders. Additionally, you get real-time reactions, including surprises, disagreements, and discussions about what they’re seeing. Much like going to a play, where audiences get to take in the stage, the costumes, the lighting, and the actors ‘ interactions, in-person research lets you see users up close, including their body language, how they interact with the moderator, and how the scene is set up.

    If conducting usability testing in the field is like watching a play that is staged and controlled, where any two sessions may be very different from one another. You can conduct usability testing in the real world by creating a replica of the environment where users interact with the product and then conducting your research there. Or you can go out to meet users at their location to do your research. With either option, you can see how things work in context, how things develop, and how conversion can take a completely different turn. You have less control over how these sessions end as researchers, but this can occasionally help you understand users even better. Meeting users where they are can provide clues to the external forces that could be affecting how they use your product. Usability tests in person offer a level of detail that is frequently absent from remote testing.

    That doesn’t mean that “movies” —remote sessions—aren’t a good option. Remote sessions can reach a wider audience. They make it possible for much more people to participate in the research and to observe what is happening. Additionally, they make the doors accessible to a much wider range of users. But with any remote session there is the potential of time wasted if participants can’t log in or get their microphone working.

    You can ask real users questions to understand their thoughts and understanding of the solution as a result of usability testing, whether it is done remotely or in person. This can help you identify issues as well as understand why they were initially issues. Furthermore, you can test hypotheses and gauge whether your thinking is correct. By the end of the sessions, you’ll have a much clearer understanding of how useful the designs are and whether or not they fulfill their intended purpose. Act two is where the excitement is at the heart of the narrative, but there are also potential surprises. This is equally true of usability tests. Unexpected things that participants say frequently alter the way you look at things, and these unexpected revelations can lead to unexpected turns in the narrative.

    Unfortunately, user research can occasionally be viewed as unreliable. And too often usability testing is the only research process that some stakeholders think that they ever need. There isn’t much to be gained by conducting usability testing in the first place if the designs you’re evaluating in the usability test aren’t grounded in thorough understanding of your users ( foundational research ). Because you narrow down the subject matter of your feedback without understanding the needs of the users. As a result, there’s no way of knowing whether the designs might solve a problem that users have. In the context of a usability test, it’s only feedback on a particular design.

    On the other hand, if you only do foundational research, you won’t know whether the object you’re building will actually solve the problem you might have intended to solve. This illustrates the importance of doing both foundational and directional research.

    In act two, stakeholders will hopefully be able to observe the story develop in the user sessions, which reveal the conflict and tension in the current design’s highs and lows. And in turn, this can encourage stakeholders to take action on the issues raised.

    Act three: resolution

    The third act is about resolving the issues from the first two acts, while the first two acts are about understanding the background and the tensions that can compel stakeholders to take action. While having an audience for the first two acts is crucial, having them stay for the final act is also important. That means the whole product team, including developers, UX practitioners, business analysts, delivery managers, product managers, and any other stakeholders that have a say in the next steps. It allows the entire team to discuss what’s possible within the project’s constraints, ask questions, and discuss user feedback together. Additionally, it enables the UX design and research teams to clarify, suggest alternatives, or provide more context for their choices. So you can get everyone on the same page and get agreement on the way forward.

    Voiceover narration of this act is typically used with audience input. The researcher serves as the narrator, who depicts the issues and what the product’s future might look like given the lessons the team has learned. They give the stakeholders their recommendations and their guidance on creating this vision.

    In the Harvard Business Review, Nancy Duarte describes a method for structuring presentations that follow a persuasive narrative. The most effective presenters employ the same methods as great storytellers: By reaffirming the status quo and then revealing a better way, they create a conflict that needs to be resolved, writes Duarte. ” That tension helps them persuade the audience to adopt a new mindset or behave differently”.

    This kind of structure is in line with research findings, particularly those from usability tests. It provides evidence for “what is “—the problems that you’ve identified. And “what might be “—your suggestions for how to respond to them. And so forth and forth.

    You can reinforce your recommendations with examples of things that competitors are doing that could address these issues or with examples where competitors are gaining an edge. Or they can be visual, like quick sketches of how a new design could function to solve a problem. These can help create momentum and conversation. And this continues until the end of the session when you’ve wrapped everything up in the conclusion by summarizing the main issues and suggesting a way forward. This is the section where you make the most of the main themes or issues and what they mean for the finished product, or the story’s denial. The stakeholders will now have the opportunity to take the next steps, and hopefully the will-power to do so!

    While we are nearly at the end of this story, let’s reflect on the idea that user research is storytelling. The three-act structure of user research contains all the components for a good story:

      Act one: You encounter both the users and the antagonists ( the issues affecting users ). This is the beginning of the plot. Researchers might employ techniques like contextual inquiry, ethnography, diary studies, surveys, and analytics in act one. These techniques can produce personas, empathy maps, user journeys, and analytics dashboards as output.
      Act two: Next, there’s character development. The protagonists encounter problems and difficulties, which they must overcome, and there is conflict and tension. Researchers might employ heuristics evaluation, usability testing, competitive benchmarking, and other methods in act two. The output of these can include usability findings reports, UX strategy documents, usability guidelines, and best practices.
      Act three: The protagonists win, and you can see what a better future might look like. Researchers may use techniques like storytelling, presentation decks, and digital media in act three. The output of these can be: presentation decks, video clips, audio clips, and pictures.

    The researcher performs a number of tasks: they are the producer, the director, and the storyteller. Although the participants are only a small part in the study, they are significant characters. And the stakeholders are the audience. However, the most crucial thing is to get the story straight and to use storytelling to research user stories. By the end, the parties should leave with a goal and an eagerness to address the product’s flaws.

    So the next time that you’re planning research with clients or you’re speaking to stakeholders about research that you’ve done, think about how you can weave in some storytelling. User research is ultimately a win-win situation for everyone, and all you need to do is pique stakeholders ‘ interest in how the story ends.

  • Beware the Cut ‘n’ Paste Persona

    Beware the Cut ‘n’ Paste Persona

    This Person Does Not Exist is a website that generates human faces with a machine learning algorithm. It takes real portraits and recombines them into fake human faces. We recently scrolled past a LinkedIn post stating that this website could be useful “if you are developing a persona and looking for a photo.” 

    We agree: the computer-generated faces could be a great match for personas—but not for the reason you might think. Ironically, the website highlights the core issue of this very common design method: the person(a) does not exist. Like the pictures, personas are artificially made. Information is taken out of natural context and recombined into an isolated snapshot that’s detached from reality. 

    But strangely enough, designers use personas to inspire their design for the real world. 

    Personas: A step back

    Most designers have created, used, or come across personas at least once in their career. In their article “Personas – A Simple Introduction,” the Interaction Design Foundation defines personas as “fictional characters, which you create based upon your research in order to represent the different user types that might use your service, product, site, or brand.” In their most complete expression, personas typically consist of a name, profile picture, quotes, demographics, goals, needs, behavior in relation to a certain service/product, emotions, and motivations (for example, see Creative Companion’s Persona Core Poster). The purpose of personas, as stated by design agency Designit, is “to make the research relatable, [and] easy to communicate, digest, reference, and apply to product and service development.”

    The decontextualization of personas

    Personas are popular because they make “dry” research data more relatable, more human. However, this method constrains the researcher’s data analysis in such a way that the investigated users are removed from their unique contexts. As a result, personas don’t portray key factors that make you understand their decision-making process or allow you to relate to users’ thoughts and behavior; they lack stories. You understand what the persona did, but you don’t have the background to understand why. You end up with representations of users that are actually less human.

    This “decontextualization” we see in personas happens in four ways, which we’ll explain below. 

    Personas assume people are static 

    Although many companies still try to box in their employees and customers with outdated personality tests (referring to you, Myers-Briggs), here’s a painfully obvious truth: people are not a fixed set of features. You act, think, and feel differently according to the situations you experience. You appear different to different people; you might act friendly to some, rough to others. And you change your mind all the time about decisions you’ve taken. 

    Modern psychologists agree that while people generally behave according to certain patterns, it’s actually a combination of background and environment that determines how people act and take decisions. The context—the environment, the influence of other people, your mood, the entire history that led up to a situation—determines the kind of person you are in each specific moment. 

    In their attempt to simplify reality, personas do not take this variability into account; they present a user as a fixed set of features. Like personality tests, personas snatch people away from real life. Even worse, people are reduced to a label and categorized as “that kind of person” with no means to exercise their innate flexibility. This practice reinforces stereotypes, lowers diversity, and doesn’t reflect reality. 

    Personas focus on individuals, not the environment

    In the real world, you’re designing for a context, not for an individual. Each person lives in a family, a community, an ecosystem, where there are environmental, political, and social factors you need to consider. A design is never meant for a single user. Rather, you design for one or more particular contexts in which many people might use that product. Personas, however, show the user alone rather than describe how the user relates to the environment. 

    Would you always make the same decision over and over again? Maybe you’re a committed vegan but still decide to buy some meat when your relatives are coming over. As they depend on different situations and variables, your decisions—and behavior, opinions, and statements—are not absolute but highly contextual. The persona that “represents” you wouldn’t take into account this dependency, because it doesn’t specify the premises of your decisions. It doesn’t provide a justification of why you act the way you do. Personas enact the well-known bias called fundamental attribution error: explaining others’ behavior too much by their personality and too little by the situation.

    As mentioned by the Interaction Design Foundation, personas are usually placed in a scenario that’s a “specific context with a problem they want to or have to solve”—does that mean context actually is considered? Unfortunately, what often happens is that you take a fictional character and based on that fiction determine how this character might deal with a certain situation. This is made worse by the fact that you haven’t even fully investigated and understood the current context of the people your persona seeks to represent; so how could you possibly understand how they would act in new situations? 

    Personas are meaningless averages

    As mentioned in Shlomo Goltz’s introductory article on Smashing Magazine, “a persona is depicted as a specific person but is not a real individual; rather, it is synthesized from observations of many people.” A well-known critique to this aspect of personas is that the average person does not exist, as per the famous example of the USA Air Force designing planes based on the average of 140 of their pilots’ physical dimensions and not a single pilot actually fitting within that average seat. 

    The same limitation applies to mental aspects of people. Have you ever heard a famous person say, “They took what I said out of context! They used my words, but I didn’t mean it like that.” The celebrity’s statement was reported literally, but the reporter failed to explain the context around the statement and didn’t describe the non-verbal expressions. As a result, the intended meaning was lost. You do the same when you create personas: you collect somebody’s statement (or goal, or need, or emotion), of which the meaning can only be understood if you provide its own specific context, yet report it as an isolated finding. 

    But personas go a step further, extracting a decontextualized finding and joining it with another decontextualized finding from somebody else. The resulting set of findings often does not make sense: it’s unclear, or even contrasting, because it lacks the underlying reasons on why and how that finding has arisen. It lacks meaning. And the persona doesn’t give you the full background of the person(s) to uncover this meaning: you would need to dive into the raw data for each single persona item to find it. What, then, is the usefulness of the persona?

    The relatability of personas is deceiving

    To a certain extent, designers realize that a persona is a lifeless average. To overcome this, designers invent and add “relatable” details to personas to make them resemble real individuals. Nothing captures the absurdity of this better than a sentence by the Interaction Design Foundation: “Add a few fictional personal details to make the persona a realistic character.” In other words, you add non-realism in an attempt to create more realism. You deliberately obscure the fact that “John Doe” is an abstract representation of research findings; but wouldn’t it be much more responsible to emphasize that John is only an abstraction? If something is artificial, let’s present it as such.

    It’s the finishing touch of a persona’s decontextualization: after having assumed that people’s personalities are fixed, dismissed the importance of their environment, and hidden meaning by joining isolated, non-generalizable findings, designers invent new context to create (their own) meaning. In doing so, as with everything they create, they introduce a host of biases. As phrased by Designit, as designers we can “contextualize [the persona] based on our reality and experience. We create connections that are familiar to us.” This practice reinforces stereotypes, doesn’t reflect real-world diversity, and gets further away from people’s actual reality with every detail added. 

    To do good design research, we should report the reality “as-is” and make it relatable for our audience, so everyone can use their own empathy and develop their own interpretation and emotional response.

    Dynamic Selves: The alternative to personas

    If we shouldn’t use personas, what should we do instead? 

    Designit has proposed using Mindsets instead of personas. Each Mindset is a “spectrum of attitudes and emotional responses that different people have within the same context or life experience.” It challenges designers to not get fixated on a single user’s way of being. Unfortunately, while being a step in the right direction, this proposal doesn’t take into account that people are part of an environment that determines their personality, their behavior, and, yes, their mindset. Therefore, Mindsets are also not absolute but change in regard to the situation. The question remains, what determines a certain Mindset?

    Another alternative comes from Margaret P., author of the article “Kill Your Personas,” who has argued for replacing personas with persona spectrums that consist of a range of user abilities. For example, a visual impairment could be permanent (blindness), temporary (recovery from eye surgery), or situational (screen glare). Persona spectrums are highly useful for more inclusive and context-based design, as they’re based on the understanding that the context is the pattern, not the personality. Their limitation, however, is that they have a very functional take on users that misses the relatability of a real person taken from within a spectrum. 

    In developing an alternative to personas, we aim to transform the standard design process to be context-based. Contexts are generalizable and have patterns that we can identify, just like we tried to do previously with people. So how do we identify these patterns? How do we ensure truly context-based design? 

    Understand real individuals in multiple contexts

    Nothing is more relatable and inspiring than reality. Therefore, we have to understand real individuals in their multi-faceted contexts, and use this understanding to fuel our design. We refer to this approach as Dynamic Selves.

    Let’s take a look at what the approach looks like, based on an example of how one of us applied it in a recent project that researched habits of Italians around energy consumption. We drafted a design research plan aimed at investigating people’s attitudes toward energy consumption and sustainable behavior, with a focus on smart thermostats. 

    1. Choose the right sample

    When we argue against personas, we’re often challenged with quotes such as “Where are you going to find a single person that encapsulates all the information from one of these advanced personas[?]” The answer is simple: you don’t have to. You don’t need to have information about many people for your insights to be deep and meaningful. 

    In qualitative research, validity does not derive from quantity but from accurate sampling. You select the people that best represent the “population” you’re designing for. If this sample is chosen well, and you have understood the sampled people in sufficient depth, you’re able to infer how the rest of the population thinks and behaves. There’s no need to study seven Susans and five Yuriys; one of each will do. 

    Similarly, you don’t need to understand Susan in fifteen different contexts. Once you’ve seen her in a couple of diverse situations, you’ve understood the scheme of Susan’s response to different contexts. Not Susan as an atomic being but Susan in relation to the surrounding environment: how she might act, feel, and think in different situations. 

    Given that each person is representative of a part of the total population you’re researching, it becomes clear why each should be represented as an individual, as each already is an abstraction of a larger group of individuals in similar contexts. You don’t want abstractions of abstractions! These selected people need to be understood and shown in their full expression, remaining in their microcosmos—and if you want to identify patterns you can focus on identifying patterns in contexts.

    Yet the question remains: how do you select a representative sample? First of all, you have to consider what’s the target audience of the product or service you are designing: it might be useful to look at the company’s goals and strategy, the current customer base, and/or a possible future target audience. 

    In our example project, we were designing an application for those who own a smart thermostat. In the future, everyone could have a smart thermostat in their house. Right now, though, only early adopters own one. To build a significant sample, we needed to understand the reason why these early adopters became such. We therefore recruited by asking people why they had a smart thermostat and how they got it. There were those who had chosen to buy it, those who had been influenced by others to buy it, and those who had found it in their house. So we selected representatives of these three situations, from different age groups and geographical locations, with an equal balance of tech savvy and non-tech savvy participants. 

    2. Conduct your research

    After having chosen and recruited your sample, conduct your research using ethnographic methodologies. This will make your qualitative data rich with anecdotes and examples. In our example project, given COVID-19 restrictions, we converted an in-house ethnographic research effort into remote family interviews, conducted from home and accompanied by diary studies.

    To gain an in-depth understanding of attitudes and decision-making trade-offs, the research focus was not limited to the interviewee alone but deliberately included the whole family. Each interviewee would tell a story that would then become much more lively and precise with the corrections or additional details coming from wives, husbands, children, or sometimes even pets. We also focused on the relationships with other meaningful people (such as colleagues or distant family) and all the behaviors that resulted from those relationships. This wide research focus allowed us to shape a vivid mental image of dynamic situations with multiple actors. 

    It’s essential that the scope of the research remains broad enough to be able to include all possible actors. Therefore, it normally works best to define broad research areas with macro questions. Interviews are best set up in a semi-structured way, where follow-up questions will dive into topics mentioned spontaneously by the interviewee. This open-minded “plan to be surprised” will yield the most insightful findings. When we asked one of our participants how his family regulated the house temperature, he replied, “My wife has not installed the thermostat’s app—she uses WhatsApp instead. If she wants to turn on the heater and she is not home, she will text me. I am her thermostat.”

    3. Analysis: Create the Dynamic Selves

    During the research analysis, you start representing each individual with multiple Dynamic Selves, each “Self” representing one of the contexts you have investigated. The core of each Dynamic Self is a quote, which comes supported by a photo and a few relevant demographics that illustrate the wider context. The research findings themselves will show which demographics are relevant to show. In our case, as our research focused on families and their lifestyle to understand their needs for thermal regulation, the important demographics were family type, number and nature of houses owned, economic status, and technological maturity. (We also included the individual’s name and age, but they’re optional—we included them to ease the stakeholders’ transition from personas and be able to connect multiple actions and contexts to the same person).

    To capture exact quotes, interviews need to be video-recorded and notes need to be taken verbatim as much as possible. This is essential to the truthfulness of the several Selves of each participant. In the case of real-life ethnographic research, photos of the context and anonymized actors are essential to build realistic Selves. Ideally, these photos should come directly from field research, but an evocative and representative image will work, too, as long as it’s realistic and depicts meaningful actions that you associate with your participants. For example, one of our interviewees told us about his mountain home where he used to spend every weekend with his family. Therefore, we portrayed him hiking with his little daughter. 

    At the end of the research analysis, we displayed all of the Selves’ “cards” on a single canvas, categorized by activities. Each card displayed a situation, represented by a quote and a unique photo. All participants had multiple cards about themselves.

    4. Identify design opportunities

    Once you have collected all main quotes from the interview transcripts and diaries, and laid them all down as Self cards, you will see patterns emerge. These patterns will highlight the opportunity areas for new product creation, new functionalities, and new services—for new design. 

    In our example project, there was a particularly interesting insight around the concept of humidity. We realized that people don’t know what humidity is and why it is important to monitor it for health: an environment that’s too dry or too wet can cause respiratory problems or worsen existing ones. This highlighted a big opportunity for our client to educate users on this concept and become a health advisor.

    Benefits of Dynamic Selves

    When you use the Dynamic Selves approach in your research, you start to notice unique social relations, peculiar situations real people face and the actions that follow, and that people are surrounded by changing environments. In our thermostat project, we have come to know one of the participants, Davide, as a boyfriend, dog-lover, and tech enthusiast. 

    Davide is an individual we might have once reduced to a persona called “tech enthusiast.” But we can have tech enthusiasts who have families or are single, who are rich or poor. Their motivations and priorities when deciding to purchase a new thermostat can be opposite according to these different frames. 

    Once you have understood Davide in multiple situations, and for each situation have understood in sufficient depth the underlying reasons for his behavior, you’re able to generalize how he would act in another situation. You can use your understanding of him to infer what he would think and do in the contexts (or scenarios) that you design for.

    The Dynamic Selves approach aims to dismiss the conflicted dual purpose of personas—to summarize and empathize at the same time—by separating your research summary from the people you’re seeking to empathize with. This is important because our empathy for people is affected by scale: the bigger the group, the harder it is to feel empathy for others. We feel the strongest empathy for individuals we can personally relate to.  

    If you take a real person as inspiration for your design, you no longer need to create an artificial character. No more inventing details to make the character more “realistic,” no more unnecessary additional bias. It’s simply how this person is in real life. In fact, in our experience, personas quickly become nothing more than a name in our priority guides and prototype screens, as we all know that these characters don’t really exist. 

    Another powerful benefit of the Dynamic Selves approach is that it raises the stakes of your work: if you mess up your design, someone real, a person you and the team know and have met, is going to feel the consequences. It might stop you from taking shortcuts and will remind you to conduct daily checks on your designs.

    And finally, real people in their specific contexts are a better basis for anecdotal storytelling and therefore are more effective in persuasion. Documentation of real research is essential in achieving this result. It adds weight and urgency behind your design arguments: “When I met Alessandra, the conditions of her workplace struck me. Noise, bad ergonomics, lack of light, you name it. If we go for this functionality, I’m afraid we’re going to add complexity to her life.”

    Conclusion

    Designit mentioned in their article on Mindsets that “design thinking tools offer a shortcut to deal with reality’s complexities, but this process of simplification can sometimes flatten out people’s lives into a few general characteristics.” Unfortunately, personas have been culprits in a crime of oversimplification. They are unsuited to represent the complex nature of our users’ decision-making processes and don’t account for the fact that humans are immersed in contexts. 

    Design needs simplification but not generalization. You have to look at the research elements that stand out: the sentences that captured your attention, the images that struck you, the sounds that linger. Portray those, use them to describe the person in their multiple contexts. Both insights and people come with a context; they cannot be cut from that context because it would remove meaning. 

    It’s high time for design to move away from fiction, and embrace reality—in its messy, surprising, and unquantifiable beauty—as our guide and inspiration.

  • That’s Not My Burnout

    That’s Not My Burnout

    Are you like me, reading about people fading away as they burn out, and feeling unable to relate? Do you feel like your feelings are invisible to the world because you’re experiencing burnout differently? When burnout starts to push down on us, our core comes through more. Beautiful, peaceful souls get quieter and fade into that distant and distracted burnout we’ve all read about. But some of us, those with fires always burning on the edges of our core, get hotter. In my heart I am fire. When I face burnout I double down, triple down, burning hotter and hotter to try to best the challenge. I don’t fade—I am engulfed in a zealous burnout

    So what on earth is a zealous burnout?

    Imagine a woman determined to do it all. She has two amazing children whom she, along with her husband who is also working remotely, is homeschooling during a pandemic. She has a demanding client load at work—all of whom she loves. She gets up early to get some movement in (or often catch up on work), does dinner prep as the kids are eating breakfast, and gets to work while positioning herself near “fourth grade” to listen in as she juggles clients, tasks, and budgets. Sound like a lot? Even with a supportive team both at home and at work, it is. 

    Sounds like this woman has too much on her plate and needs self-care. But no, she doesn’t have time for that. In fact, she starts to feel like she’s dropping balls. Not accomplishing enough. There’s not enough of her to be here and there; she is trying to divide her mind in two all the time, all day, every day. She starts to doubt herself. And as those feelings creep in more and more, her internal narrative becomes more and more critical.

    Suddenly she KNOWS what she needs to do! She should DO MORE. 

    This is a hard and dangerous cycle. Know why? Because once she doesn’t finish that new goal, that narrative will get worse. Suddenly she’s failing. She isn’t doing enough. SHE is not enough. She might fail, she might fail her family…so she’ll find more she should do. She doesn’t sleep as much, move as much, all in the efforts to do more. Caught in this cycle of trying to prove herself to herself, never reaching any goal. Never feeling “enough.” 

    So, yeah, that’s what zealous burnout looks like for me. It doesn’t happen overnight in some grand gesture but instead slowly builds over weeks and months. My burning out process looks like speeding up, not a person losing focus. I speed up and up and up…and then I just stop.

    I am the one who could

    It’s funny the things that shape us. Through the lens of childhood, I viewed the fears, struggles, and sacrifices of someone who had to make it all work without having enough. I was lucky that my mother was so resourceful and my father supportive; I never went without and even got an extra here or there. 

    Growing up, I did not feel shame when my mother paid with food stamps; in fact, I’d have likely taken on any debate on the topic, verbally eviscerating anyone who dared to criticize the disabled woman trying to make sure all our needs were met with so little. As a child, I watched the way the fear of not making those ends meet impacted people I love. As the non-disabled person in my home, I would take on many of the physical tasks because I was “the one who could” make our lives a little easier. I learned early to associate fears or uncertainty with putting more of myself into it—I am the one who can. I learned early that when something frightens me, I can double down and work harder to make it better. I can own the challenge. When people have seen this in me as an adult, I’ve been told I seem fearless, but make no mistake, I’m not. If I seem fearless, it’s because this behavior was forged from other people’s fears. 

    And here I am, more than 30 years later still feeling the urge to mindlessly push myself forward when faced with overwhelming tasks ahead of me, assuming that I am the one who can and therefore should. I find myself driven to prove that I can make things happen if I work longer hours, take on more responsibility, and do more

    I do not see people who struggle financially as failures, because I have seen how strong that tide can be—it pulls you along the way. I truly get that I have been privileged to be able to avoid many of the challenges that were present in my youth. That said, I am still “the one who can” who feels she should, so if I were faced with not having enough to make ends meet for my own family, I would see myself as having failed. Though I am supported and educated, most of this is due to good fortune. I will, however, allow myself the arrogance of saying I have been careful with my choices to have encouraged that luck. My identity stems from the idea that I am “the one who can” so therefore feel obligated to do the most. I can choose to stop, and with some quite literal cold water splashed in my face, I’ve made the choice to before. But that choosing to stop is not my go-to; I move forward, driven by a fear that is so a part of me that I barely notice it’s there until I’m feeling utterly worn away.

    So why all the history? You see, burnout is a fickle thing. I have heard and read a lot about burnout over the years. Burnout is real. Especially now, with COVID, many of us are balancing more than we ever have before—all at once! It’s hard, and the procrastinating, the avoidance, the shutting down impacts so many amazing professionals. There are important articles that relate to what I imagine must be the majority of people out there, but not me. That’s not what my burnout looks like.

    The dangerous invisibility of zealous burnout

    A lot of work environments see the extra hours, extra effort, and overall focused commitment as an asset (and sometimes that’s all it is). They see someone trying to rise to challenges, not someone stuck in their fear. Many well-meaning organizations have safeguards in place to protect their teams from burnout. But in cases like this, those alarms are not always tripped, and then when the inevitable stop comes, some members of the organization feel surprised and disappointed. And sometimes maybe even betrayed. 

    Parents—more so mothers, statistically speaking—are praised as being so on top of it all when they can work, be involved in the after-school activities, practice self-care in the form of diet and exercise, and still meet friends for coffee or wine. During COVID many of us have binged countless streaming episodes showing how it’s so hard for the female protagonist, but she is strong and funny and can do it. It’s a “very special episode” when she breaks down, cries in the bathroom, woefully admits she needs help, and just stops for a bit. Truth is, countless people are hiding their tears or are doom-scrolling to escape. We know that the media is a lie to amuse us, but often the perception that it’s what we should strive for has penetrated much of society.

    Women and burnout

    I love men. And though I don’t love every man (heads up, I don’t love every woman or nonbinary person either), I think there is a beautiful spectrum of individuals who represent that particular binary gender. 

    That said, women are still more often at risk of burnout than their male counterparts, especially in these COVID stressed times. Mothers in the workplace feel the pressure to do all the “mom” things while giving 110%. Mothers not in the workplace feel they need to do more to “justify” their lack of traditional employment. Women who are not mothers often feel the need to do even more because they don’t have that extra pressure at home. It’s vicious and systemic and so a part of our culture that we’re often not even aware of the enormity of the pressures we put on ourselves and each other. 

    And there are prices beyond happiness too. Harvard Health Publishing released a study a decade ago that “uncovered strong links between women’s job stress and cardiovascular disease.” The CDC noted, “Heart disease is the leading cause of death for women in the United States, killing 299,578 women in 2017—or about 1 in every 5 female deaths.” 

    This relationship between work stress and health, from what I have read, is more dangerous for women than it is for their non-female counterparts.

    But what if your burnout isn’t like that either?

    That might not be you either. After all, each of us is so different and how we respond to stressors is too. It’s part of what makes us human. Don’t stress what burnout looks like, just learn to recognize it in yourself. Here are a few questions I sometimes ask friends if I am concerned about them.

    Are you happy? This simple question should be the first thing you ask yourself. Chances are, even if you’re burning out doing all the things you love, as you approach burnout you’ll just stop taking as much joy from it all.

    Do you feel empowered to say no? I have observed in myself and others that when someone is burning out, they no longer feel they can say no to things. Even those who don’t “speed up” feel pressure to say yes to not disappoint the people around them.

    What are three things you’ve done for yourself? Another observance is that we all tend to stop doing things for ourselves. Anything from skipping showers and eating poorly to avoiding talking to friends. These can be red flags. 

    Are you making excuses? Many of us try to disregard feelings of burnout. Over and over I have heard, “It’s just crunch time,” “As soon as I do this one thing, it will all be better,” and “Well I should be able to handle this, so I’ll figure it out.” And it might really be crunch time, a single goal, and/or a skill set you need to learn. That happens—life happens. BUT if this doesn’t stop, be honest with yourself. If you’ve worked more 50-hour weeks since January than not, maybe it’s not crunch time—maybe it’s a bad situation that you’re burning out from.

    Do you have a plan to stop feeling this way? If something is truly temporary and you do need to just push through, then it has an exit route with a
    defined end.

    Take the time to listen to yourself as you would a friend. Be honest, allow yourself to be uncomfortable, and break the thought cycles that prevent you from healing. 

    So now what?

    What I just described is a different path to burnout, but it’s still burnout. There are well-established approaches to working through burnout:

    • Get enough sleep.
    • Eat healthy.
    • Work out.
    • Get outside.
    • Take a break.
    • Overall, practice self-care.

    Those are hard for me because they feel like more tasks. If I’m in the burnout cycle, doing any of the above for me feels like a waste. The narrative is that if I’m already failing, why would I take care of myself when I’m dropping all those other balls? People need me, right? 

    If you’re deep in the cycle, your inner voice might be pretty awful by now. If you need to, tell yourself you need to take care of the person your people depend on. If your roles are pushing you toward burnout, use them to help make healing easier by justifying the time spent working on you. 

    To help remind myself of the airline attendant message about putting the mask on yourself first, I have come up with a few things that I do when I start feeling myself going into a zealous burnout.

    Cook an elaborate meal for someone! 

    OK, I am a “food-focused” individual so cooking for someone is always my go-to. There are countless tales in my home of someone walking into the kitchen and turning right around and walking out when they noticed I was “chopping angrily.” But it’s more than that, and you should give it a try. Seriously. It’s the perfect go-to if you don’t feel worthy of taking time for yourself—do it for someone else. Most of us work in a digital world, so cooking can fill all of your senses and force you to be in the moment with all the ways you perceive the world. It can break you out of your head and help you gain a better perspective. In my house, I’ve been known to pick a place on the map and cook food that comes from wherever that is (thank you, Pinterest). I love cooking Indian food, as the smells are warm, the bread needs just enough kneading to keep my hands busy, and the process takes real attention for me because it’s not what I was brought up making. And in the end, we all win!

    Vent like a foul-mouthed fool

    Be careful with this one! 

    I have been making an effort to practice more gratitude over the past few years, and I recognize the true benefits of that. That said, sometimes you just gotta let it all out—even the ugly. Hell, I’m a big fan of not sugarcoating our lives, and that sometimes means that to get past the big pile of poop, you’re gonna wanna complain about it a bit. 

    When that is what’s needed, turn to a trusted friend and allow yourself some pure verbal diarrhea, saying all the things that are bothering you. You need to trust this friend not to judge, to see your pain, and, most importantly, to tell you to remove your cranium from your own rectal cavity. Seriously, it’s about getting a reality check here! One of the things I admire the most about my husband (though often after the fact) is his ability to break things down to their simplest. “We’re spending our lives together, of course you’re going to disappoint me from time to time, so get over it” has been his way of speaking his dedication, love, and acceptance of me—and I could not be more grateful. It also, of course, has meant that I needed to remove my head from that rectal cavity. So, again, usually those moments are appreciated in hindsight.

    Pick up a book! 

    There are many books out there that aren’t so much self-help as they are people just like you sharing their stories and how they’ve come to find greater balance. Maybe you’ll find something that speaks to you. Titles that have stood out to me include:

    • Thrive by Arianna Huffington
    • Tools of Titans by Tim Ferriss
    • Girl, Stop Apologizing by Rachel Hollis
    • Dare to Lead by Brené Brown

    Or, another tactic I love to employ is to read or listen to a book that has NOTHING to do with my work-life balance. I’ve read the following books and found they helped balance me out because my mind was pondering their interesting topics instead of running in circles:

    • The Drunken Botanist by Amy Stewart
    • Superlife by Darin Olien
    • A Brief History of Everyone Who Ever Lived by Adam Rutherford
    • Gaia’s Garden by Toby Hemenway 

    If you’re not into reading, pick up a topic on YouTube or choose a podcast to subscribe to. I’ve watched countless permaculture and gardening topics in addition to how to raise chickens and ducks. For the record, I do not have a particularly large food garden, nor do I own livestock of any kind…yet. I just find the topic interesting, and it has nothing to do with any aspect of my life that needs anything from me.

    Forgive yourself 

    You are never going to be perfect—hell, it would be boring if you were. It’s OK to be broken and flawed. It’s human to be tired and sad and worried. It’s OK to not do it all. It’s scary to be imperfect, but you cannot be brave if nothing were scary.

    This last one is the most important: allow yourself permission to NOT do it all. You never promised to be everything to everyone at all times. We are more powerful than the fears that drive us. 

    This is hard. It is hard for me. It’s what’s driven me to write this—that it’s OK to stop. It’s OK that your unhealthy habit that might even benefit those around you needs to end. You can still be successful in life.

    I recently read that we are all writing our eulogy in how we live. Knowing that your professional accomplishments won’t be mentioned in that speech, what will yours say? What do you want it to say? 

    Look, I get that none of these ideas will “fix it,” and that’s not their purpose. None of us are in control of our surroundings, only how we respond to them. These suggestions are to help stop the spiral effect so that you are empowered to address the underlying issues and choose your response. They are things that work for me most of the time. Maybe they’ll work for you.

    Does this sound familiar? 

    If this sounds familiar, it’s not just you. Don’t let your negative self-talk tell you that you “even burn out wrong.” It’s not wrong. Even if rooted in fear like my own drivers, I believe that this need to do more comes from a place of love, determination, motivation, and other wonderful attributes that make you the amazing person you are. We’re going to be OK, ya know. The lives that unfold before us might never look like that story in our head—that idea of “perfect” or “done” we’re looking for, but that’s OK. Really, when we stop and look around, usually the only eyes that judge us are in the mirror. 

    Do you remember that Winnie the Pooh sketch that had Pooh eat so much at Rabbit’s house that his buttocks couldn’t fit through the door? Well, I already associate a lot with Rabbit, so it came as no surprise when he abruptly declared that this was unacceptable. But do you recall what happened next? He put a shelf across poor Pooh’s ankles and decorations on his back, and made the best of the big butt in his kitchen. 

    At the end of the day we are resourceful and know that we are able to push ourselves if we need to—even when we are tired to our core or have a big butt of fluff ‘n’ stuff in our room. None of us has to be afraid, as we can manage any obstacle put in front of us. And maybe that means we will need to redefine success to allow space for being uncomfortably human, but that doesn’t really sound so bad either. 

    So, wherever you are right now, please breathe. Do what you need to do to get out of your head. Forgive and take care.

  • Asynchronous Design Critique: Giving Feedback

    Asynchronous Design Critique: Giving Feedback

    One of the most successful soft skills we have at our disposal is feedback, in whatever form it takes, and whatever it may be called. It helps us collaborate to improve our designs while developing our own abilities and perspectives.

    Feedback is also one of the most underestimated equipment, and generally by assuming that we’re now great at it, we settle, forgetting that it’s a skill that can be trained, grown, and improved. Bad comments can lead to conflict in projects, lower confidence, and long-term, undermine trust and teamwork. Quality suggestions can have a revolutionary effect.

    Practicing our knowledge is absolutely a good way to enhance, but the learning gets yet faster when it’s paired with a good base that programs and focuses the exercise. What are some fundamental components of providing effective opinions? And how can comments be changed for rural and distributed workplaces?

    On the web, we may discover a long history of sequential suggestions: from the early weeks of open source, script was shared and discussed on email addresses. Developers and sprint masters discuss ideas on tickets, designers post on their favourite design tools, and so on.

    Design criticism is frequently referred to as a form of collaborative suggestions that is used to improve our work. So it shares a lot of the rules with comments in public, but it also has some variations.

    The information

    The material of the feedback serves as the foundation for all effective critiques, so we need to start there. There are many designs that you can use to form your content. This one from Lara Hogan is the one I personally like best because it’s obvious and actionable.

    Although this equation is typically used to provide feedback to individuals, it likewise fits really well in a style criticism because it finally addresses some of the main inquiries that we work on: What? Where? Why? How? Imagine that you’re giving some comments about some pattern function that spans several screens, like an onboard movement: there are some pages shown, a stream blueprint, and an outline of the decisions made. You notice a flaw in the situation. You’ll have a mental unit that can help you become more precise and effective if you keep the three components of the equation in mind.

    Here is a reply that could be given as a part of some comments, and it might seem reasonable at a first glance: it seems to casually serve the elements in the equation. But does it exist?

    Concerning the buttons ‘ styles and hierarchy, it seems off. Can you change them?

    Observation for design feedback doesn’t just mean pointing out which area of the interface your feedback touches, but it also means offering a perspective that’s as specific as possible. Do you offer the user’s viewpoint? Your expert perspective? From a business perspective? From the perspective of the project manager? A first-time user’s perspective?

    When I see these two buttons, I anticipate one to go forward and the other to go back.

    Impact is about the why. Just pointing out a UI element might sometimes be enough if the issue may be obvious, but more often than not, you should add an explanation of what you’re pointing out.

    When I see these two buttons, I anticipate one to go forward and the other to go back. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow.

    By provoking the designer’s critical thinking while receiving the feedback, the question approach is intended to provide open guidance. Notably, Lara’s equation includes a second approach: request, which instead provides instructions for a particular solution. While that’s a viable option for feedback in general, for design critiques, in my experience, defaulting to the question approach usually reaches the best solutions because designers are generally more comfortable in being given an open space to explore.

    For the question approach, the difference between the two can be demonstrated as an illustration:

    When I see these two buttons, I anticipate one to go forward and the other to go back. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Would it make sense to unify them?

    Or, for the request approach:

    When I see these two buttons, I anticipate one to go forward and the other to go back. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Let’s make sure that all screens have the same pair of forward and back buttons.

    In some situations, it might be helpful to include an additional reason why you think the suggestion is better at this point.

    When I see these two buttons, I anticipate one to go forward and the other to go back. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Let’s make sure that all screens have the same two forward and back buttons so that users don’t get confused.

    Choosing between the request and question approaches can occasionally be a matter of personal preference. I spent a while working on improving my feedback, conducting anonymous feedback reviews and sharing feedback with others. After a few rounds of this work and a year later, I got a positive response: my feedback came across as effective and grounded. until I switched teams. Quite unexpected, my next round of criticism from one particular person wasn’t very positive. The reason is that I had previously tried not to be prescriptive in my advice—because the people who I was previously working with preferred the open-ended question format over the request style of suggestions. However, there was a member of this other team who preferred specific guidance. So I modified my feedback to include requests.

    One comment that I heard come up a few times is that this kind of feedback is quite long, and it doesn’t seem very efficient. Yes, but no. Let’s look at both sides.

    No, this style of feedback is actually efficient because the length here is a byproduct of clarity, and spending time giving this kind of feedback can provide exactly enough information for a good fix. Additionally, if we zoom out, it may lessen misunderstandings and back-and-forth conversations in the future, thereby increasing overall effectiveness and efficiency of collaboration beyond the single comment. Consider the following example:” Let’s make sure that all screens have the same two forward and back buttons” instead. The designer receiving this feedback wouldn’t have much to go by, so they might just apply the change. The interface might change in later iterations or new features might be introduced, and perhaps the change won’t make sense anymore. Without explaining the why, the designer might assume that the change is one of consistency, but what if it wasn’t? So there could now be an underlying concern that changing the buttons would be perceived as a regression.

    Yes, this type of feedback is not always effective because some comments don’t always need to be thorough, some times because some changes may be obvious ( the font used doesn’t follow our guidelines ), and others because the team may have a lot of internal knowledge, making some of the whys may be implied.

    The equation above is not intended to provide a predetermined template for feedback, but rather a mnemonic to reflect and enhance the practice. Even after years of active work on my critiques, I still from time to time go back to this formula and reflect on whether what I just wrote is effective.

    The atmosphere

    Feedback forms the basis for well-developed content, but that’s not really enough. The soft skills of the person who’s providing the critique can multiply the likelihood that the feedback will be well received and understood. It has been demonstrated that only positive feedback can lead to sustained change in people. It can be determined by tone alone whether content is rejected or welcomed.

    Tone is crucial to work on because our goal is to be understood and create a positive working environment. Over the years, I’ve tried to summarize the required soft skills in a formula that mirrors the one for content: the receptivity equation.

    Respectful feedback comes across as grounded, solid, and constructive. It’s the kind of feedback that, regardless of whether it’s positive or negative, is viewed as useful and fair.

    Timing refers to when the feedback happens. When given at the wrong time, to-the-point feedback has little chance of receiving favorable reception. If a new feature’s entire high-level information architecture is about to go live when it’s about to be released, it might still be relevant if that questioning raises a significant blocker that no one saw, but those concerns are much more likely to have to wait for a later revision. So in general, attune your feedback to the stage of the project. Early iteration? Iteration that was later? Polishing work in progress? Each of these has unique needs. Your feedback will be received favorably if the right timing is chosen.

    Attitude is the equivalent of intent, and in the context of person-to-person feedback, it can be referred to as radical candor. That entails checking before writing to see if what we have in mind will actually help the person and improve the project overall. Perhaps we don’t want to admit that we don’t really appreciate that person when we reflect on them. Hopefully that’s not the case, but that can happen, and that’s okay. How would I write if I really cared about them, if you could help you make up for it? How can I stop acting aggressively? How can I be more constructive?

    Form is important especially in diverse and cross-cultural workplaces because having excellent writing, perfect timing, and the right attitude might not be effective if the writing style leads to miscommunications. There could be many reasons for this: some words might cause particular reactions, some non-native speakers might not understand all the nuances of some sentences, and other times our brains might be different and we might perceive the world differently. Neurodiversity must be taken into account. Whatever the reason, it’s important to review not just what we write but how.

    A few years ago, I asked for some suggestions for how to give feedback. I was given some helpful advice, but I also found a surprise in my comment. They pointed out that when I wrote” Oh, ]… ]”, I made them feel stupid. That wasn’t my intention at all! I just realized that I had been giving them feedback for months and that I had always made them feel foolish. I was horrified … but also thankful. I quickly changed the way I typed “oh” into my list of replaced words (your choice between aText, TextExpander, or others ), so that it was instantly deleted when I typed “oh.”

    Something to keep in mind is that people frequently beat around the bush, especially in teams with strong group spirit. It’s important to remember here that a positive attitude doesn’t mean going light on the feedback—it just means that even when you provide hard, difficult, or challenging feedback, you do so in a way that’s respectful and constructive. You can help someone grow the best way you can.

    Giving feedback in written form can be reviewed by someone else who isn’t directly involved, which can help to reduce or eliminate any bias that might exist. I found that the best, most insightful moments for me have happened when I’ve shared a comment and I’ve asked someone who I highly trusted,” How does this sound”?,” How can I do it better”, and even” How would you have written it” ?—and I’ve learned a lot by seeing the two versions side by side.

    The format

    Asynchronous feedback also has a significant inherent benefit: we can devote more time to making sure that the suggestions ‘ clarity of communication and actionability meet two main objectives.

    Let’s imagine that someone shared a design iteration for a project. You are commenting on it while reviewing it. There are many ways to accomplish this, and context is of course important, but let’s try to think about some things that might be worthwhile to take into account.

    In terms of clarity, start by grounding the critique that you’re about to give by providing context. This includes specifically describing where you’re coming from: do you have a thorough understanding of the project, or is this your first encounter with it? Do you have a high-level perspective, or are you just learning the details? Are there regressions? Which user’s point of view do you consider when providing feedback? Is the design iteration ready to ship this, or are important issues still to be addressed first?

    Providing context is helpful even if you’re sharing feedback within a team that already has some information on the project. And context is a must when providing cross-team feedback. If I were to review a design that might be directly related to my work, I would say that, underlining my opinion as external, and if I had no idea how the project might have come to that conclusion.

    We often focus on the negatives, trying to outline all the things that could be done better. That’s obviously important, but it’s even more crucial to concentrate on the positives, especially if you saw improvement in the previous iteration. Although this may seem superfluous, it’s important to keep in mind that design is a field with hundreds of possible solutions to each problem. So pointing out that the design solution that was chosen is good and explaining why it’s good has two major benefits: it confirms that the approach taken was solid, and it helps to ground your negative feedback. Sharing positive feedback can help prevent regressions in things that are going well because those things will have been deemed significant in the long run. Positive feedback can also help, as an added bonus, prevent impostor syndrome.

    There’s one powerful approach that combines both context and a focus on the positives: frame how the design is better than the status quo ( compared to a previous iteration, competitors, or benchmarks ) and why, and then on that foundation, you can add what could be improved. There is a significant difference between a critique of a design that is already in good shape and one that isn’t quite there yet.

    Depersonalizing your feedback is another way to make it better: it should never be about the creator of the piece of art. It’s” This button isn’t well aligned” versus” You haven’t aligned this button well”. This can be changed in your writing very quickly by reviewing it just before sending.

    One of the best ways to assist the designer who is reading through your feedback in terms of actionability is to divide it into bullet points or paragraphs, which are easier to review and analyze one by one. For longer pieces of feedback, you might also consider splitting it into sections or even across multiple comments. Of course, it’s also possible to include screenshots or indicators for the specific area of the interface you’re referring to.

    One method that I’ve personally used to enhance the bullet points in some situations is using emojis. So a red square � � means that it’s something that I consider blocking, a yellow diamond � � is something that I can be convinced otherwise, but it seems to me that it should be changed, and a green circle � � is a detailed, positive confirmation. A blue spiral is also used for exploration, open alternatives, or just a note when I’m not sure what to make. However, I’d only use this strategy on teams where I’ve already established a high level of trust because it might turn out to be quite demoralizing if I deliver a lot of red squares and change how I communicate that.

    Let’s see how this would work by reusing the example that we used earlier as the first bullet point in this list:

    • 🔶 Navigation—When I see these two buttons, I anticipate one to go forward and the other to go back. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Let’s make sure that all screens have the same two forward and back buttons so that users don’t get confused.
    • Overall, I believe the page is strong, and this is a good candidate for our version 1. 1.0 release candidate.
    • � � Metrics—Good improvement in the buttons on the metrics area, the improved contrast and new focus style make them more accessible.
    • Button Style: Using the green accent in this context gives the impression that it’s a positive action because green is typically seen as a confirmation color. Should we look for a different color?
    • 🔶Tiles—Given the number of items on the page, and the overall page hierarchy, it seems to me that the tiles shouldn’t be using the Subtitle 1 style but the Subtitle 2 style. This will maintain consistency in the visual hierarchy.
    • Background: Using a light texture is effective, but I’m not sure if doing so will cause too much noise on this kind of page. What is the thinking in using that?

    What about using Figma or another design tool that enables in-place feedback to provide feedback directly? These are generally difficult to use because they conceal discussions and are harder to follow, but in the right setting, they can be very effective. Just make sure that each of the comments is separate so that it’s easier to match each discussion to a single task, similar to the idea of splitting mentioned above.

    One last word: avoid the obvious. Sometimes we might feel good or bad about something, so we don’t say it. Or sometimes we might have a doubt that we don’t express because the question might sound stupid. Say it, that’s fine. Don’t hold it back, though, because you might need to change the phrasing a little to make the reader feel more at ease. Good feedback is transparent, even when it may be obvious.

    Asynchronous feedback also has the benefit of automatically guiding decisions, according to writing. Why did we do this, especially in large projects? could be a question that pops up from time to time, and there’s nothing better than open, transparent discussions that can be reviewed at any time. I advise using software to save these discussions so they can be hidden once they are resolved, for this reason.

    Content, tone, and format are all present. Each one of these subjects provides a useful model, but working to improve eight areas—observation, impact, question, timing, attitude, form, clarity, and actionability—is a lot of work to put in all at once. One way to take them one by one is to first identify the area you most need from both your own perspective and feedback from others. Then the second, followed by the third, and so on. At first you’ll have to put in extra time for every piece of feedback that you give, but after a while, it’ll become second nature, and your impact on the work will multiply.

    Thanks to Mike Shelton and Brie Anne Demkiw for their initial review of this article.

  • Asynchronous Design Critique: Getting Feedback

    Asynchronous Design Critique: Getting Feedback

    “Any comment?” is probably one of the worst ways to ask for feedback. It’s vague and open ended, and it doesn’t provide any indication of what we’re looking for. Getting good feedback starts earlier than we might expect: it starts with the request. 

    It might seem counterintuitive to start the process of receiving feedback with a question, but that makes sense if we realize that getting feedback can be thought of as a form of design research. In the same way that we wouldn’t do any research without the right questions to get the insights that we need, the best way to ask for feedback is also to craft sharp questions.

    Design critique is not a one-shot process. Sure, any good feedback workflow continues until the project is finished, but this is particularly true for design because design work continues iteration after iteration, from a high level to the finest details. Each level needs its own set of questions.

    And finally, as with any good research, we need to review what we got back, get to the core of its insights, and take action. Question, iteration, and review. Let’s look at each of those.

    The question

    Being open to feedback is essential, but we need to be precise about what we’re looking for. Just saying “Any comment?”, “What do you think?”, or “I’d love to get your opinion” at the end of a presentation—whether it’s in person, over video, or through a written post—is likely to get a number of varied opinions or, even worse, get everyone to follow the direction of the first person who speaks up. And then… we get frustrated because vague questions like those can turn a high-level flows review into people instead commenting on the borders of buttons. Which might be a hearty topic, so it might be hard at that point to redirect the team to the subject that you had wanted to focus on.

    But how do we get into this situation? It’s a mix of factors. One is that we don’t usually consider asking as a part of the feedback process. Another is how natural it is to just leave the question implied, expecting the others to be on the same page. Another is that in nonprofessional discussions, there’s often no need to be that precise. In short, we tend to underestimate the importance of the questions, so we don’t work on improving them.

    The act of asking good questions guides and focuses the critique. It’s also a form of consent: it makes it clear that you’re open to comments and what kind of comments you’d like to get. It puts people in the right mental state, especially in situations when they weren’t expecting to give feedback.

    There isn’t a single best way to ask for feedback. It just needs to be specific, and specificity can take many shapes. A model for design critique that I’ve found particularly useful in my coaching is the one of stage versus depth.

    Stage” refers to each of the steps of the process—in our case, the design process. In progressing from user research to the final design, the kind of feedback evolves. But within a single step, one might still review whether some assumptions are correct and whether there’s been a proper translation of the amassed feedback into updated designs as the project has evolved. A starting point for potential questions could derive from the layers of user experience. What do you want to know: Project objectives? User needs? Functionality? Content? Interaction design? Information architecture? UI design? Navigation design? Visual design? Branding?

    Here’re a few example questions that are precise and to the point that refer to different layers:

    • Functionality: Is automating account creation desirable?
    • Interaction design: Take a look through the updated flow and let me know whether you see any steps or error states that I might’ve missed.
    • Information architecture: We have two competing bits of information on this page. Is the structure effective in communicating them both?
    • UI design: What are your thoughts on the error counter at the top of the page that makes sure that you see the next error, even if the error is out of the viewport? 
    • Navigation design: From research, we identified these second-level navigation items, but once you’re on the page, the list feels too long and hard to navigate. Are there any suggestions to address this?
    • Visual design: Are the sticky notifications in the bottom-right corner visible enough?

    The other axis of specificity is about how deep you’d like to go on what’s being presented. For example, we might have introduced a new end-to-end flow, but there was a specific view that you found particularly challenging and you’d like a detailed review of that. This can be especially useful from one iteration to the next where it’s important to highlight the parts that have changed.

    There are other things that we can consider when we want to achieve more specific—and more effective—questions.

    A simple trick is to remove generic qualifiers from your questions like “good,” “well,” “nice,” “bad,” “okay,” and “cool.” For example, asking, “When the block opens and the buttons appear, is this interaction good?” might look specific, but you can spot the “good” qualifier, and convert it to an even better question: “When the block opens and the buttons appear, is it clear what the next action is?”

    Sometimes we actually do want broad feedback. That’s rare, but it can happen. In that sense, you might still make it explicit that you’re looking for a wide range of opinions, whether at a high level or with details. Or maybe just say, “At first glance, what do you think?” so that it’s clear that what you’re asking is open ended but focused on someone’s impression after their first five seconds of looking at it.

    Sometimes the project is particularly expansive, and some areas may have already been explored in detail. In these situations, it might be useful to explicitly say that some parts are already locked in and aren’t open to feedback. It’s not something that I’d recommend in general, but I’ve found it useful to avoid falling again into rabbit holes of the sort that might lead to further refinement but aren’t what’s most important right now.

    Asking specific questions can completely change the quality of the feedback that you receive. People with less refined critique skills will now be able to offer more actionable feedback, and even expert designers will welcome the clarity and efficiency that comes from focusing only on what’s needed. It can save a lot of time and frustration.

    The iteration

    Design iterations are probably the most visible part of the design work, and they provide a natural checkpoint for feedback. Yet a lot of design tools with inline commenting tend to show changes as a single fluid stream in the same file, and those types of design tools make conversations disappear once they’re resolved, update shared UI components automatically, and compel designs to always show the latest version—unless these would-be helpful features were to be manually turned off. The implied goal that these design tools seem to have is to arrive at just one final copy with all discussions closed, probably because they inherited patterns from how written documents are collaboratively edited. That’s probably not the best way to approach design critiques, but even if I don’t want to be too prescriptive here: that could work for some teams.

    The asynchronous design-critique approach that I find most effective is to create explicit checkpoints for discussion. I’m going to use the term iteration post for this. It refers to a write-up or presentation of the design iteration followed by a discussion thread of some kind. Any platform that can accommodate this structure can use this. By the way, when I refer to a “write-up or presentation,” I’m including video recordings or other media too: as long as it’s asynchronous, it works.

    Using iteration posts has many advantages:

    • It creates a rhythm in the design work so that the designer can review feedback from each iteration and prepare for the next.
    • It makes decisions visible for future review, and conversations are likewise always available.
    • It creates a record of how the design changed over time.
    • Depending on the tool, it might also make it easier to collect feedback and act on it.

    These posts of course don’t mean that no other feedback approach should be used, just that iteration posts could be the primary rhythm for a remote design team to use. And other feedback approaches (such as live critique, pair designing, or inline comments) can build from there.

    I don’t think there’s a standard format for iteration posts. But there are a few high-level elements that make sense to include as a baseline:

    1. The goal
    2. The design
    3. The list of changes
    4. The questions

    Each project is likely to have a goal, and hopefully it’s something that’s already been summarized in a single sentence somewhere else, such as the client brief, the product manager’s outline, or the project owner’s request. So this is something that I’d repeat in every iteration post—literally copy and pasting it. The idea is to provide context and to repeat what’s essential to make each iteration post complete so that there’s no need to find information spread across multiple posts. If I want to know about the latest design, the latest iteration post will have all that I need.

    This copy-and-paste part introduces another relevant concept: alignment comes from repetition. So having posts that repeat information is actually very effective toward making sure that everyone is on the same page.

    The design is then the actual series of information-architecture outlines, diagrams, flows, maps, wireframes, screens, visuals, and any other kind of design work that’s been done. In short, it’s any design artifact. For the final stages of work, I prefer the term blueprint to emphasize that I’ll be showing full flows instead of individual screens to make it easier to understand the bigger picture. 

    It can also be useful to label the artifacts with clear titles because that can make it easier to refer to them. Write the post in a way that helps people understand the work. It’s not too different from organizing a good live presentation. 

    For an efficient discussion, you should also include a bullet list of the changes from the previous iteration to let people focus on what’s new, which can be especially useful for larger pieces of work where keeping track, iteration after iteration, could become a challenge.

    And finally, as noted earlier, it’s essential that you include a list of the questions to drive the design critique in the direction you want. Doing this as a numbered list can also help make it easier to refer to each question by its number.

    Not all iterations are the same. Earlier iterations don’t need to be as tightly focused—they can be more exploratory and experimental, maybe even breaking some of the design-language guidelines to see what’s possible. Then later, the iterations start settling on a solution and refining it until the design process reaches its end and the feature ships.

    I want to highlight that even if these iteration posts are written and conceived as checkpoints, by no means do they need to be exhaustive. A post might be a draft—just a concept to get a conversation going—or it could be a cumulative list of each feature that was added over the course of each iteration until the full picture is done.

    Over time, I also started using specific labels for incremental iterations: i1, i2, i3, and so on. This might look like a minor labelling tip, but it can help in multiple ways:

    • Unique—It’s a clear unique marker. Within each project, one can easily say, “This was discussed in i4,” and everyone knows where they can go to review things.
    • Unassuming—It works like versions (such as v1, v2, and v3) but in contrast, versions create the impression of something that’s big, exhaustive, and complete. Iterations must be able to be exploratory, incomplete, partial.
    • Future proof—It resolves the “final” naming problem that you can run into with versions. No more files named “final final complete no-really-its-done.” Within each project, the largest number always represents the latest iteration.

    To mark when a design is complete enough to be worked on, even if there might be some bits still in need of attention and in turn more iterations needed, the wording release candidate (RC) could be used to describe it: “with i8, we reached RC” or “i12 is an RC.”

    The review

    What usually happens during a design critique is an open discussion, with a back and forth between people that can be very productive. This approach is particularly effective during live, synchronous feedback. But when we work asynchronously, it’s more effective to use a different approach: we can shift to a user-research mindset. Written feedback from teammates, stakeholders, or others can be treated as if it were the result of user interviews and surveys, and we can analyze it accordingly.

    This shift has some major benefits that make asynchronous feedback particularly effective, especially around these friction points:

    1. It removes the pressure to reply to everyone.
    2. It reduces the frustration from swoop-by comments.
    3. It lessens our personal stake.

    The first friction point is feeling a pressure to reply to every single comment. Sometimes we write the iteration post, and we get replies from our team. It’s just a few of them, it’s easy, and it doesn’t feel like a problem. But other times, some solutions might require more in-depth discussions, and the amount of replies can quickly increase, which can create a tension between trying to be a good team player by replying to everyone and doing the next design iteration. This might be especially true if the person who’s replying is a stakeholder or someone directly involved in the project who we feel that we need to listen to. We need to accept that this pressure is absolutely normal, and it’s human nature to try to accommodate people who we care about. Sometimes replying to all comments can be effective, but if we treat a design critique more like user research, we realize that we don’t have to reply to every comment, and in asynchronous spaces, there are alternatives:

    • One is to let the next iteration speak for itself. When the design evolves and we post a follow-up iteration, that’s the reply. You might tag all the people who were involved in the previous discussion, but even that’s a choice, not a requirement. 
    • Another is to briefly reply to acknowledge each comment, such as “Understood. Thank you,” “Good points—I’ll review,” or “Thanks. I’ll include these in the next iteration.” In some cases, this could also be just a single top-level comment along the lines of “Thanks for all the feedback everyone—the next iteration is coming soon!”
    • Another is to provide a quick summary of the comments before moving on. Depending on your workflow, this can be particularly useful as it can provide a simplified checklist that you can then use for the next iteration.

    The second friction point is the swoop-by comment, which is the kind of feedback that comes from someone outside the project or team who might not be aware of the context, restrictions, decisions, or requirements—or of the previous iterations’ discussions. On their side, there’s something that one can hope that they might learn: they could start to acknowledge that they’re doing this and they could be more conscious in outlining where they’re coming from. Swoop-by comments often trigger the simple thought “We’ve already discussed this…”, and it can be frustrating to have to repeat the same reply over and over.

    Let’s begin by acknowledging again that there’s no need to reply to every comment. If, however, replying to a previously litigated point might be useful, a short reply with a link to the previous discussion for extra details is usually enough. Remember, alignment comes from repetition, so it’s okay to repeat things sometimes!

    Swoop-by commenting can still be useful for two reasons: they might point out something that still isn’t clear, and they also have the potential to stand in for the point of view of a user who’s seeing the design for the first time. Sure, you’ll still be frustrated, but that might at least help in dealing with it.

    The third friction point is the personal stake we could have with the design, which could make us feel defensive if the review were to feel more like a discussion. Treating feedback as user research helps us create a healthy distance between the people giving us feedback and our ego (because yes, even if we don’t want to admit it, it’s there). And ultimately, treating everything in aggregated form allows us to better prioritize our work.

    Always remember that while you need to listen to stakeholders, project owners, and specific advice, you don’t have to accept every piece of feedback. You have to analyze it and make a decision that you can justify, but sometimes “no” is the right answer. 

    As the designer leading the project, you’re in charge of that decision. Ultimately, everyone has their specialty, and as the designer, you’re the one who has the most knowledge and the most context to make the right decision. And by listening to the feedback that you’ve received, you’re making sure that it’s also the best and most balanced decision.

    Thanks to Brie Anne Demkiw and Mike Shelton for reviewing the first draft of this article.

  • Designing for the Unexpected

    Designing for the Unexpected

    I’m not sure when I first heard this quote, but it’s something that has stayed with me over the years. How do you create services for situations you can’t imagine? Or design products that work on devices yet to be invented?

    Flash, Photoshop, and responsive design

    When I first started designing websites, my go-to software was Photoshop. I created a 960px canvas and set about creating a layout that I would later drop content in. The development phase was about attaining pixel-perfect accuracy using fixed widths, fixed heights, and absolute positioning.

    Ethan Marcotte’s talk at An Event Apart and subsequent article “Responsive Web Design” in A List Apart in 2010 changed all this. I was sold on responsive design as soon as I heard about it, but I was also terrified. The pixel-perfect designs full of magic numbers that I had previously prided myself on producing were no longer good enough.

    The fear wasn’t helped by my first experience with responsive design. My first project was to take an existing fixed-width website and make it responsive. What I learned the hard way was that you can’t just add responsiveness at the end of a project. To create fluid layouts, you need to plan throughout the design phase.

    A new way to design

    Designing responsive or fluid sites has always been about removing limitations, producing content that can be viewed on any device. It relies on the use of percentage-based layouts, which I initially achieved with native CSS and utility classes:

    .column-span-6 {
      width: 49%;
      float: left;
      margin-right: 0.5%;
      margin-left: 0.5%;
    }
    
    
    .column-span-4 {
      width: 32%;
      float: left;
      margin-right: 0.5%;
      margin-left: 0.5%;
    }
    
    .column-span-3 {
      width: 24%;
      float: left;
      margin-right: 0.5%;
      margin-left: 0.5%;
    }

    Then with Sass so I could take advantage of @includes to re-use repeated blocks of code and move back to more semantic markup:

    .logo {
      @include colSpan(6);
    }
    
    .search {
      @include colSpan(3);
    }
    
    .social-share {
      @include colSpan(3);
    }

    Media queries

    The second ingredient for responsive design is media queries. Without them, content would shrink to fit the available space regardless of whether that content remained readable (The exact opposite problem occurred with the introduction of a mobile-first approach).

    Media queries prevented this by allowing us to add breakpoints where the design could adapt. Like most people, I started out with three breakpoints: one for desktop, one for tablets, and one for mobile. Over the years, I added more and more for phablets, wide screens, and so on. 

    For years, I happily worked this way and improved both my design and front-end skills in the process. The only problem I encountered was making changes to content, since with our Sass grid system in place, there was no way for the site owners to add content without amending the markup—something a small business owner might struggle with. This is because each row in the grid was defined using a div as a container. Adding content meant creating new row markup, which requires a level of HTML knowledge.

    Row markup was a staple of early responsive design, present in all the widely used frameworks like Bootstrap and Skeleton.

    1 of 7
    2 of 7
    3 of 7
    4 of 7
    5 of 7
    6 of 7
    7 of 7

    Another problem arose as I moved from a design agency building websites for small- to medium-sized businesses, to larger in-house teams where I worked across a suite of related sites. In those roles I started to work much more with reusable components. 

    Our reliance on media queries resulted in components that were tied to common viewport sizes. If the goal of component libraries is reuse, then this is a real problem because you can only use these components if the devices you’re designing for correspond to the viewport sizes used in the pattern library—in the process not really hitting that “devices that don’t yet exist”  goal.

    Then there’s the problem of space. Media queries allow components to adapt based on the viewport size, but what if I put a component into a sidebar, like in the figure below?

    Container queries: our savior or a false dawn?

    Container queries have long been touted as an improvement upon media queries, but at the time of writing are unsupported in most browsers. There are JavaScript workarounds, but they can create dependency and compatibility issues. The basic theory underlying container queries is that elements should change based on the size of their parent container and not the viewport width, as seen in the following illustrations.

    One of the biggest arguments in favor of container queries is that they help us create components or design patterns that are truly reusable because they can be picked up and placed anywhere in a layout. This is an important step in moving toward a form of component-based design that works at any size on any device.

    In other words, responsive components to replace responsive layouts.

    Container queries will help us move from designing pages that respond to the browser or device size to designing components that can be placed in a sidebar or in the main content, and respond accordingly.

    My concern is that we are still using layout to determine when a design needs to adapt. This approach will always be restrictive, as we will still need pre-defined breakpoints. For this reason, my main question with container queries is, How would we decide when to change the CSS used by a component? 

    A component library removed from context and real content is probably not the best place for that decision. 

    As the diagrams below illustrate, we can use container queries to create designs for specific container widths, but what if I want to change the design based on the image size or ratio?

    In this example, the dimensions of the container are not what should dictate the design; rather, the image is.

    It’s hard to say for sure whether container queries will be a success story until we have solid cross-browser support for them. Responsive component libraries would definitely evolve how we design and would improve the possibilities for reuse and design at scale. But maybe we will always need to adjust these components to suit our content.

    CSS is changing

    Whilst the container query debate rumbles on, there have been numerous advances in CSS that change the way we think about design. The days of fixed-width elements measured in pixels and floated div elements used to cobble layouts together are long gone, consigned to history along with table layouts. Flexbox and CSS Grid have revolutionized layouts for the web. We can now create elements that wrap onto new rows when they run out of space, not when the device changes.

    .wrapper {
      display: grid;
      grid-template-columns: repeat(auto-fit, 450px);
      gap: 10px;
    }

    The repeat() function paired with auto-fit or auto-fill allows us to specify how much space each column should use while leaving it up to the browser to decide when to spill the columns onto a new line. Similar things can be achieved with Flexbox, as elements can wrap over multiple rows and “flex” to fill available space. 

    .wrapper {
      display: flex;
      flex-wrap: wrap;
      justify-content: space-between;
    }
    
    .child {
      flex-basis: 32%;
      margin-bottom: 20px;
    }

    The biggest benefit of all this is you don’t need to wrap elements in container rows. Without rows, content isn’t tied to page markup in quite the same way, allowing for removals or additions of content without additional development.

    This is a big step forward when it comes to creating designs that allow for evolving content, but the real game changer for flexible designs is CSS Subgrid. 

    Remember the days of crafting perfectly aligned interfaces, only for the customer to add an unbelievably long header almost as soon as they’re given CMS access, like the illustration below?

    Subgrid allows elements to respond to adjustments in their own content and in the content of sibling elements, helping us create designs more resilient to change.

    .wrapper {
      display: grid;
      grid-template-columns: repeat(auto-fit, minmax(150px, 1fr));
         grid-template-rows: auto 1fr auto;
      gap: 10px;
    }
    
    .sub-grid {
      display: grid;
      grid-row: span 3;
      grid-template-rows: subgrid; /* sets rows to parent grid */
    }

    CSS Grid allows us to separate layout and content, thereby enabling flexible designs. Meanwhile, Subgrid allows us to create designs that can adapt in order to suit morphing content. Subgrid at the time of writing is only supported in Firefox but the above code can be implemented behind an @supports feature query. 

    Intrinsic layouts 

    I’d be remiss not to mention intrinsic layouts, the term created by Jen Simmons to describe a mixture of new and old CSS features used to create layouts that respond to available space. 

    Responsive layouts have flexible columns using percentages. Intrinsic layouts, on the other hand, use the fr unit to create flexible columns that won’t ever shrink so much that they render the content illegible.

    fr units is a way to say I want you to distribute the extra space in this way, but…don’t ever make it smaller than the content that’s inside of it.

    —Jen Simmons, “Designing Intrinsic Layouts”

    Intrinsic layouts can also utilize a mixture of fixed and flexible units, allowing the content to dictate the space it takes up.

    What makes intrinsic design stand out is that it not only creates designs that can withstand future devices but also helps scale design without losing flexibility. Components and patterns can be lifted and reused without the prerequisite of having the same breakpoints or the same amount of content as in the previous implementation. 

    We can now create designs that adapt to the space they have, the content within them, and the content around them. With an intrinsic approach, we can construct responsive components without depending on container queries.

    Another 2010 moment?

    This intrinsic approach should in my view be every bit as groundbreaking as responsive web design was ten years ago. For me, it’s another “everything changed” moment. 

    But it doesn’t seem to be moving quite as fast; I haven’t yet had that same career-changing moment I had with responsive design, despite the widely shared and brilliant talk that brought it to my attention. 

    One reason for that could be that I now work in a large organization, which is quite different from the design agency role I had in 2010. In my agency days, every new project was a clean slate, a chance to try something new. Nowadays, projects use existing tools and frameworks and are often improvements to existing websites with an existing codebase. 

    Another could be that I feel more prepared for change now. In 2010 I was new to design in general; the shift was frightening and required a lot of learning. Also, an intrinsic approach isn’t exactly all-new; it’s about using existing skills and existing CSS knowledge in a different way. 

    You can’t framework your way out of a content problem

    Another reason for the slightly slower adoption of intrinsic design could be the lack of quick-fix framework solutions available to kick-start the change. 

    Responsive grid systems were all over the place ten years ago. With a framework like Bootstrap or Skeleton, you had a responsive design template at your fingertips.

    Intrinsic design and frameworks do not go hand in hand quite so well because the benefit of having a selection of units is a hindrance when it comes to creating layout templates. The beauty of intrinsic design is combining different units and experimenting with techniques to get the best for your content.

    And then there are design tools. We probably all, at some point in our careers, used Photoshop templates for desktop, tablet, and mobile devices to drop designs in and show how the site would look at all three stages.

    How do you do that now, with each component responding to content and layouts flexing as and when they need to? This type of design must happen in the browser, which personally I’m a big fan of. 

    The debate about “whether designers should code” is another that has rumbled on for years. When designing a digital product, we should, at the very least, design for a best- and worst-case scenario when it comes to content. To do this in a graphics-based software package is far from ideal. In code, we can add longer sentences, more radio buttons, and extra tabs, and watch in real time as the design adapts. Does it still work? Is the design too reliant on the current content?

    Personally, I look forward to the day intrinsic design is the standard for design, when a design component can be truly flexible and adapt to both its space and content with no reliance on device or container dimensions.

    Content first 

    Content is not constant. After all, to design for the unknown or unexpected we need to account for content changes like our earlier Subgrid card example that allowed the cards to respond to adjustments to their own content and the content of sibling elements.

    Thankfully, there’s more to CSS than layout, and plenty of properties and values can help us put content first. Subgrid and pseudo-elements like ::first-line and ::first-letter help to separate design from markup so we can create designs that allow for changes.

    Instead of old markup hacks like this—

    First line of text with different styling...

    —we can target content based on where it appears.

    .element::first-line {
      font-size: 1.4em;
    }
    
    .element::first-letter {
      color: red;
    }

    Much bigger additions to CSS include logical properties, which change the way we construct designs using logical dimensions (start and end) instead of physical ones (left and right), something CSS Grid also does with functions like min(), max(), and clamp().

    This flexibility allows for directional changes according to content, a common requirement when we need to present content in multiple languages. In the past, this was often achieved with Sass mixins but was often limited to switching from left-to-right to right-to-left orientation.

    In the Sass version, directional variables need to be set.

    $direction: rtl;
    $opposite-direction: ltr;
    
    $start-direction: right;
    $end-direction: left;

    These variables can be used as values—

    body {
      direction: $direction;
      text-align: $start-direction;
    }

    —or as properties.

    margin-#{$end-direction}: 10px;
    padding-#{$start-direction}: 10px;

    However, now we have native logical properties, removing the reliance on both Sass (or a similar tool) and pre-planning that necessitated using variables throughout a codebase. These properties also start to break apart the tight coupling between a design and strict physical dimensions, creating more flexibility for changes in language and in direction.

    margin-block-end: 10px;
    padding-block-start: 10px;

    There are also native start and end values for properties like text-align, which means we can replace text-align: right with text-align: start.

    Like the earlier examples, these properties help to build out designs that aren’t constrained to one language; the design will reflect the content’s needs.

    Fixed and fluid 

    We briefly covered the power of combining fixed widths with fluid widths with intrinsic layouts. The min() and max() functions are a similar concept, allowing you to specify a fixed value with a flexible alternative. 

    For min() this means setting a fluid minimum value and a maximum fixed value.

    .element {
      width: min(50%, 300px);
    }

    The element in the figure above will be 50% of its container as long as the element’s width doesn’t exceed 300px.

    For max() we can set a flexible max value and a minimum fixed value.

    .element {
      width: max(50%, 300px);
    }

    Now the element will be 50% of its container as long as the element’s width is at least 300px. This means we can set limits but allow content to react to the available space. 

    The clamp() function builds on this by allowing us to set a preferred value with a third parameter. Now we can allow the element to shrink or grow if it needs to without getting to a point where it becomes unusable.

    .element {
      width: clamp(300px, 50%, 600px);
    }

    This time, the element’s width will be 50% (the preferred value) of its container but never less than 300px and never more than 600px.

    With these techniques, we have a content-first approach to responsive design. We can separate content from markup, meaning the changes users make will not affect the design. We can start to future-proof designs by planning for unexpected changes in language or direction. And we can increase flexibility by setting desired dimensions alongside flexible alternatives, allowing for more or less content to be displayed correctly.

    Situation first

    Thanks to what we’ve discussed so far, we can cover device flexibility by changing our approach, designing around content and space instead of catering to devices. But what about that last bit of Jeffrey Zeldman’s quote, “…situations you haven’t imagined”?

    It’s a very different thing to design for someone seated at a desktop computer as opposed to someone using a mobile phone and moving through a crowded street in glaring sunshine. Situations and environments are hard to plan for or predict because they change as people react to their own unique challenges and tasks.

    This is why choice is so important. One size never fits all, so we need to design for multiple scenarios to create equal experiences for all our users.

    Thankfully, there is a lot we can do to provide choice.

    Responsible design 

    “There are parts of the world where mobile data is prohibitively expensive, and where there is little or no broadband infrastructure.”

    I Used the Web for a Day on a 50 MB Budget

    Chris Ashton

    One of the biggest assumptions we make is that people interacting with our designs have a good wifi connection and a wide screen monitor. But in the real world, our users may be commuters traveling on trains or other forms of transport using smaller mobile devices that can experience drops in connectivity. There is nothing more frustrating than a web page that won’t load, but there are ways we can help users use less data or deal with sporadic connectivity.

    The srcset attribute allows the browser to decide which image to serve. This means we can create smaller ‘cropped’ images to display on mobile devices in turn using less bandwidth and less data.

    Image alt text

    The preload attribute can also help us to think about how and when media is downloaded. It can be used to tell a browser about any critical assets that need to be downloaded with high priority, improving perceived performance and the user experience. 

     
     

    There’s also native lazy loading, which indicates assets that should only be downloaded when they are needed.

    …

    With srcset, preload, and lazy loading, we can start to tailor a user’s experience based on the situation they find themselves in. What none of this does, however, is allow the user themselves to decide what they want downloaded, as the decision is usually the browser’s to make. 

    So how can we put users in control?

    The return of media queries 

    Media queries have always been about much more than device sizes. They allow content to adapt to different situations, with screen size being just one of them.

    We’ve long been able to check for media types like print and speech and features such as hover, resolution, and color. These checks allow us to provide options that suit more than one scenario; it’s less about one-size-fits-all and more about serving adaptable content. 

    As of this writing, the Media Queries Level 5 spec is still under development. It introduces some really exciting queries that in the future will help us design for multiple other unexpected situations.

    For example, there’s a light-level feature that allows you to modify styles if a user is in sunlight or darkness. Paired with custom properties, these features allow us to quickly create designs or themes for specific environments.

    @media (light-level: normal) {
      --background-color: #fff;
      --text-color: #0b0c0c;  
    }
    
    @media (light-level: dim) {
      --background-color: #efd226;
      --text-color: #0b0c0c;
    }

    Another key feature of the Level 5 spec is personalization. Instead of creating designs that are the same for everyone, users can choose what works for them. This is achieved by using features like prefers-reduced-data, prefers-color-scheme, and prefers-reduced-motion, the latter two of which already enjoy broad browser support. These features tap into preferences set via the operating system or browser so people don’t have to spend time making each site they visit more usable. 

    Media queries like this go beyond choices made by a browser to grant more control to the user.

    Expect the unexpected

    In the end, the one thing we should always expect is for things to change. Devices in particular change faster than we can keep up, with foldable screens already on the market.

    We can’t design the same way we have for this ever-changing landscape, but we can design for content. By putting content first and allowing that content to adapt to whatever space surrounds it, we can create more robust, flexible designs that increase the longevity of our products. 

    A lot of the CSS discussed here is about moving away from layouts and putting content at the heart of design. From responsive components to fixed and fluid units, there is so much more we can do to take a more intrinsic approach. Even better, we can test these techniques during the design phase by designing in-browser and watching how our designs adapt in real-time.

    When it comes to unexpected situations, we need to make sure our products are usable when people need them, whenever and wherever that might be. We can move closer to achieving this by involving users in our design decisions, by creating choice via browsers, and by giving control to our users with user-preference-based media queries. 

    Good design for the unexpected should allow for change, provide choice, and give control to those we serve: our users themselves.

  • Voice Content and Usability

    Voice Content and Usability

    We’ve been having conversations for thousands of years. Whether to convey information, conduct transactions, or simply to check in on one another, people have yammered away, chattering and gesticulating, through spoken conversation for countless generations. Only in the last few millennia have we begun to commit our conversations to writing, and only in the last few decades have we begun to outsource them to the computer, a machine that shows much more affinity for written correspondence than for the slangy vagaries of spoken language.

    Computers have trouble because between spoken and written language, speech is more primordial. To have successful conversations with us, machines must grapple with the messiness of human speech: the disfluencies and pauses, the gestures and body language, and the variations in word choice and spoken dialect that can stymie even the most carefully crafted human-computer interaction. In the human-to-human scenario, spoken language also has the privilege of face-to-face contact, where we can readily interpret nonverbal social cues.

    In contrast, written language immediately concretizes as we commit it to record and retains usages long after they become obsolete in spoken communication (the salutation “To whom it may concern,” for example), generating its own fossil record of outdated terms and phrases. Because it tends to be more consistent, polished, and formal, written text is fundamentally much easier for machines to parse and understand.

    Spoken language has no such luxury. Besides the nonverbal cues that decorate conversations with emphasis and emotional context, there are also verbal cues and vocal behaviors that modulate conversation in nuanced ways: how something is said, not what. Whether rapid-fire, low-pitched, or high-decibel, whether sarcastic, stilted, or sighing, our spoken language conveys much more than the written word could ever muster. So when it comes to voice interfaces—the machines we conduct spoken conversations with—we face exciting challenges as designers and content strategists.

    Voice Interactions

    We interact with voice interfaces for a variety of reasons, but according to Michael McTear, Zoraida Callejas, and David Griol in The Conversational Interface, those motivations by and large mirror the reasons we initiate conversations with other people, too (). Generally, we start up a conversation because:

    • we need something done (such as a transaction),
    • we want to know something (information of some sort), or
    • we are social beings and want someone to talk to (conversation for conversation’s sake).

    These three categories—which I call transactional, informational, and prosocial—also characterize essentially every voice interaction: a single conversation from beginning to end that realizes some outcome for the user, starting with the voice interface’s first greeting and ending with the user exiting the interface. Note here that a conversation in our human sense—a chat between people that leads to some result and lasts an arbitrary length of time—could encompass multiple transactional, informational, and prosocial voice interactions in succession. In other words, a voice interaction is a conversation, but a conversation is not necessarily a single voice interaction.

    Purely prosocial conversations are more gimmicky than captivating in most voice interfaces, because machines don’t yet have the capacity to really want to know how we’re doing and to do the sort of glad-handing humans crave. There’s also ongoing debate as to whether users actually prefer the sort of organic human conversation that begins with a prosocial voice interaction and shifts seamlessly into other types. In fact, in Voice User Interface Design, Michael Cohen, James Giangola, and Jennifer Balogh recommend sticking to users’ expectations by mimicking how they interact with other voice interfaces rather than trying too hard to be human—potentially alienating them in the process ().

    That leaves two genres of conversations we can have with one another that a voice interface can easily have with us, too: a transactional voice interaction realizing some outcome (“buy iced tea”) and an informational voice interaction teaching us something new (“discuss a musical”).

    Transactional voice interactions

    Unless you’re tapping buttons on a food delivery app, you’re generally having a conversation—and therefore a voice interaction—when you order a Hawaiian pizza with extra pineapple. Even when we walk up to the counter and place an order, the conversation quickly pivots from an initial smattering of neighborly small talk to the real mission at hand: ordering a pizza (generously topped with pineapple, as it should be).

    Alison: Hey, how’s it going?

    Burhan: Hi, welcome to Crust Deluxe! It’s cold out there. How can I help you?

    Alison: Can I get a Hawaiian pizza with extra pineapple?

    Burhan: Sure, what size?

    Alison: Large.

    Burhan: Anything else?

    Alison: No thanks, that’s it.

    Burhan: Something to drink?

    Alison: I’ll have a bottle of Coke.

    Burhan: You got it. That’ll be $13.55 and about fifteen minutes.

    Each progressive disclosure in this transactional conversation reveals more and more of the desired outcome of the transaction: a service rendered or a product delivered. Transactional conversations have certain key traits: they’re direct, to the point, and economical. They quickly dispense with pleasantries.

    Informational voice interactions

    Meanwhile, some conversations are primarily about obtaining information. Though Alison might visit Crust Deluxe with the sole purpose of placing an order, she might not actually want to walk out with a pizza at all. She might be just as interested in whether they serve halal or kosher dishes, gluten-free options, or something else. Here, though we again have a prosocial mini-conversation at the beginning to establish politeness, we’re after much more.

    Alison: Hey, how’s it going?

    Burhan: Hi, welcome to Crust Deluxe! It’s cold out there. How can I help you?

    Alison: Can I ask a few questions?

    Burhan: Of course! Go right ahead.

    Alison: Do you have any halal options on the menu?

    Burhan: Absolutely! We can make any pie halal by request. We also have lots of vegetarian, ovo-lacto, and vegan options. Are you thinking about any other dietary restrictions?

    Alison: What about gluten-free pizzas?

    Burhan: We can definitely do a gluten-free crust for you, no problem, for both our deep-dish and thin-crust pizzas. Anything else I can answer for you?

    Alison: That’s it for now. Good to know. Thanks!

    Burhan: Anytime, come back soon!

    This is a very different dialogue. Here, the goal is to get a certain set of facts. Informational conversations are investigative quests for the truth—research expeditions to gather data, news, or facts. Voice interactions that are informational might be more long-winded than transactional conversations by necessity. Responses tend to be lengthier, more informative, and carefully communicated so the customer understands the key takeaways.

    Voice Interfaces

    At their core, voice interfaces employ speech to support users in reaching their goals. But simply because an interface has a voice component doesn’t mean that every user interaction with it is mediated through voice. Because multimodal voice interfaces can lean on visual components like screens as crutches, we’re most concerned in this book with pure voice interfaces, which depend entirely on spoken conversation, lack any visual component whatsoever, and are therefore much more nuanced and challenging to tackle.

    Though voice interfaces have long been integral to the imagined future of humanity in science fiction, only recently have those lofty visions become fully realized in genuine voice interfaces.

    Interactive voice response (IVR) systems

    Though written conversational interfaces have been fixtures of computing for many decades, voice interfaces first emerged in the early 1990s with text-to-speech (TTS) dictation programs that recited written text aloud, as well as speech-enabled in-car systems that gave directions to a user-provided address. With the advent of interactive voice response (IVR) systems, intended as an alternative to overburdened customer service representatives, we became acquainted with the first true voice interfaces that engaged in authentic conversation.

    IVR systems allowed organizations to reduce their reliance on call centers but soon became notorious for their clunkiness. Commonplace in the corporate world, these systems were primarily designed as metaphorical switchboards to guide customers to a real phone agent (“Say Reservations to book a flight or check an itinerary”); chances are you will enter a conversation with one when you call an airline or hotel conglomerate. Despite their functional issues and users’ frustration with their inability to speak to an actual human right away, IVR systems proliferated in the early 1990s across a variety of industries (, PDF).

    While IVR systems are great for highly repetitive, monotonous conversations that generally don’t veer from a single format, they have a reputation for less scintillating conversation than we’re used to in real life (or even in science fiction).

    Screen readers

    Parallel to the evolution of IVR systems was the invention of the screen reader, a tool that transcribes visual content into synthesized speech. For Blind or visually impaired website users, it’s the predominant method of interacting with text, multimedia, or form elements. Screen readers represent perhaps the closest equivalent we have today to an out-of-the-box implementation of content delivered through voice.

    Among the first screen readers known by that moniker was the Screen Reader for the BBC Micro and NEEC Portable developed by the Research Centre for the Education of the Visually Handicapped (RCEVH) at the University of Birmingham in 1986 (). That same year, Jim Thatcher created the first IBM Screen Reader for text-based computers, later recreated for computers with graphical user interfaces (GUIs) ().

    With the rapid growth of the web in the 1990s, the demand for accessible tools for websites exploded. Thanks to the introduction of semantic HTML and especially ARIA roles beginning in 2008, screen readers started facilitating speedy interactions with web pages that ostensibly allow disabled users to traverse the page as an aural and temporal space rather than a visual and physical one. In other words, screen readers for the web “provide mechanisms that translate visual design constructs—proximity, proportion, etc.—into useful information,” writes Aaron Gustafson in A List Apart. “At least they do when documents are authored thoughtfully” ().

    Though deeply instructive for voice interface designers, there’s one significant problem with screen readers: they’re difficult to use and unremittingly verbose. The visual structures of websites and web navigation don’t translate well to screen readers, sometimes resulting in unwieldy pronouncements that name every manipulable HTML element and announce every formatting change. For many screen reader users, working with web-based interfaces exacts a cognitive toll.

    In Wired, accessibility advocate and voice engineer Chris Maury considers why the screen reader experience is ill-suited to users relying on voice:

    From the beginning, I hated the way that Screen Readers work. Why are they designed the way they are? It makes no sense to present information visually and then, and only then, translate that into audio. All of the time and energy that goes into creating the perfect user experience for an app is wasted, or even worse, adversely impacting the experience for blind users. ()

    In many cases, well-designed voice interfaces can speed users to their destination better than long-winded screen reader monologues. After all, visual interface users have the benefit of darting around the viewport freely to find information, ignoring areas irrelevant to them. Blind users, meanwhile, are obligated to listen to every utterance synthesized into speech and therefore prize brevity and efficiency. Disabled users who have long had no choice but to employ clunky screen readers may find that voice interfaces, particularly more modern voice assistants, offer a more streamlined experience.

    Voice assistants

    When we think of voice assistants (the subset of voice interfaces now commonplace in living rooms, smart homes, and offices), many of us immediately picture HAL from 2001: A Space Odyssey or hear Majel Barrett’s voice as the omniscient computer in Star Trek. Voice assistants are akin to personal concierges that can answer questions, schedule appointments, conduct searches, and perform other common day-to-day tasks. And they’re rapidly gaining more attention from accessibility advocates for their assistive potential.

    Before the earliest IVR systems found success in the enterprise, Apple published a demonstration video in 1987 depicting the Knowledge Navigator, a voice assistant that could transcribe spoken words and recognize human speech to a great degree of accuracy. Then, in 2001, Tim Berners-Lee and others formulated their vision for a Semantic Web “agent” that would perform typical errands like “checking calendars, making appointments, and finding locations” (, behind paywall). It wasn’t until 2011 that Apple’s Siri finally entered the picture, making voice assistants a tangible reality for consumers.

    Thanks to the plethora of voice assistants available today, there is considerable variation in how programmable and customizable certain voice assistants are over others (Fig 1.1). At one extreme, everything except vendor-provided features is locked down; for example, at the time of their release, the core functionality of Apple’s Siri and Microsoft’s Cortana couldn’t be extended beyond their existing capabilities. Even today, it isn’t possible to program Siri to perform arbitrary functions, because there’s no means by which developers can interact with Siri at a low level, apart from predefined categories of tasks like sending messages, hailing rideshares, making restaurant reservations, and certain others.

    At the opposite end of the spectrum, voice assistants like Amazon Alexa and Google Home offer a core foundation on which developers can build custom voice interfaces. For this reason, programmable voice assistants that lend themselves to customization and extensibility are becoming increasingly popular for developers who feel stifled by the limitations of Siri and Cortana. Amazon offers the Alexa Skills Kit, a developer framework for building custom voice interfaces for Amazon Alexa, while Google Home offers the ability to program arbitrary Google Assistant skills. Today, users can choose from among thousands of custom-built skills within both the Amazon Alexa and Google Assistant ecosystems.

    As corporations like Amazon, Apple, Microsoft, and Google continue to stake their territory, they’re also selling and open-sourcing an unprecedented array of tools and frameworks for designers and developers that aim to make building voice interfaces as easy as possible, even without code.

    Often by necessity, voice assistants like Amazon Alexa tend to be monochannel—they’re tightly coupled to a device and can’t be accessed on a computer or smartphone instead. By contrast, many development platforms like Google’s Dialogflow have introduced omnichannel capabilities so users can build a single conversational interface that then manifests as a voice interface, textual chatbot, and IVR system upon deployment. I don’t prescribe any specific implementation approaches in this design-focused book, but in Chapter 4 we’ll get into some of the implications these variables might have on the way you build out your design artifacts.

    Voice Content

    Simply put, voice content is content delivered through voice. To preserve what makes human conversation so compelling in the first place, voice content needs to be free-flowing and organic, contextless and concise—everything written content isn’t.

    Our world is replete with voice content in various forms: screen readers reciting website content, voice assistants rattling off a weather forecast, and automated phone hotline responses governed by IVR systems. In this book, we’re most concerned with content delivered auditorily—not as an option, but as a necessity.

    For many of us, our first foray into informational voice interfaces will be to deliver content to users. There’s only one problem: any content we already have isn’t in any way ready for this new habitat. So how do we make the content trapped on our websites more conversational? And how do we write new copy that lends itself to voice interactions?

    Lately, we’ve begun slicing and dicing our content in unprecedented ways. Websites are, in many respects, colossal vaults of what I call macrocontent: lengthy prose that can extend for infinitely scrollable miles in a browser window, like microfilm viewers of newspaper archives. Back in 2002, well before the present-day ubiquity of voice assistants, technologist Anil Dash defined microcontent as permalinked pieces of content that stay legible regardless of environment, such as email or text messages:

    A day’s weather forcast [sic], the arrival and departure times for an airplane flight, an abstract from a long publication, or a single instant message can all be examples of microcontent. ()

    I’d update Dash’s definition of microcontent to include all examples of bite-sized content that go well beyond written communiqués. After all, today we encounter microcontent in interfaces where a small snippet of copy is displayed alone, unmoored from the browser, like a textbot confirmation of a restaurant reservation. Microcontent offers the best opportunity to gauge how your content can be stretched to the very edges of its capabilities, informing delivery channels both established and novel.

    As microcontent, voice content is unique because it’s an example of how content is experienced in time rather than in space. We can glance at a digital sign underground for an instant and know when the next train is arriving, but voice interfaces hold our attention captive for periods of time that we can’t easily escape or skip, something screen reader users are all too familiar with.

    Because microcontent is fundamentally made up of isolated blobs with no relation to the channels where they’ll eventually end up, we need to ensure that our microcontent truly performs well as voice content—and that means focusing on the two most important traits of robust voice content: voice content legibility and voice content discoverability.

    Fundamentally, the legibility and discoverability of our voice content both have to do with how voice content manifests in perceived time and space.