Category: Blog

I’ve been fascinated by shows since I was a child. I loved the heroes and the excitement—but most of all the stories. I aspired to be an artist. And I believed that I’d get to do the things that Indiana Jones did and go on fascinating experiences. Perhaps my friends and I had movie ideas to make and sun in. But they never went any farther. 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 research is story. And you must tell a compelling story to entice stakeholders, such as the product team and decision-makers, to learn more in order to get the most out of consumer research.

Think of your favourite film. It probably follows a three-act narrative architecture: the layout, the conflict, and the resolution, which is prevalent in literature. The second act shows what exists now, and it helps you get to know the figures and the challenges and problems that they face. Act two sets the scene for the fight and introduces the activity. Here, difficulties grow or get worse. And the quality is the third and final work. This is where the issues are resolved and the figures learn and change. This structure, in my opinion, is also a fantastic way to think about customer research, and I think it can be particularly useful for explaining consumer research to others.

Use story as a framework when conducting analysis.

It’s sad to say, but many have come to see studies as being dispensable. Research is typically one of the first things to go when expenses or deadlines are tight. Instead of investing in study, some goods professionals rely on manufacturers or—worse—their personal judgment to make the “right” options for users based on their experience or accepted best practices. 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. Design is enhanced by consumer study. It keeps it on trail, pointing to problems and opportunities. Being aware of problems with your goods and taking corrective actions can help you be ahead of your competition.

In the three-act structure, each action corresponds to a part of the process, and each part is important to telling the whole story. Let’s examine the various functions and how they relate to consumer analysis.

Act one: installation

The rig consists entirely in comprehending the history, and that’s where fundamental research comes in. Basic research ( also called conceptual, discovery, or original research ) helps you understand people and identify their problems. Just like in the movies, you’re learning about the problems users face, what options are available, and how those challenges impact them. To do basic research, you may conduct situational inquiries or journal studies ( or both! ), which can assist you in identifying both prospects and issues. It doesn’t need to get a great investment in time or money.

What is the least feasible ethnography that Erika Hall can do is spend fifteen minutes with a consumer and say,” Walk me through your day yesterday. That’s it. Provide that one ask. Locked up and listen to them for 15 days. Do everything in your power to protect both your objectives and yourself. Bam, you’re doing ethnography”. Hall predicts that “[This ] will probably prove quite fascinating. In the very unlikely event that you didn’t learn anything new or helpful, carry on with increased confidence in your way”.

This makes sense to me in all its entirety. And I love that this makes consumer research so visible. You can only attract participants and do it! You don’t need to make a lot of documentation. 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. That’s what action one is really all about: understanding where people are coming from.

Maybe Spool talks about the importance of basic research and how it may type the bulk of your research. If you can substitute what you’ve heard in the fundamental research by using more customer information that you can obtain, such as surveys or analytics, or to highlight areas that need more research. Together, all this information creates a clearer picture of the state of things and all its inadequacies. 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 characters and support their success, much like in films. And maybe partners are now doing the same. Their business may lose money because users can’t finish specific tasks, which may be their love. Or probably they do connect with customers ‘ problems. In either case, work one serves as your main strategy for piqueing interest and investment from the participants.

When partners 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. This benefits everyone—users, the product, and stakeholders. It’s similar to winning an Oscar for a film; it frequently results in a favorable reception and success for your product. And this can be an incentive for stakeholders to repeat this process with other 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 digging deeper into the problems that you identified in act one. This typically involves conducting directional research, such as usability tests, where you evaluate a potential solution ( such as a design ) to see if it addresses the issues you identified. The issues could include unmet needs or problems with a flow or process that’s tripping users up. Additional problems will arise in the course of act two of a film. It’s here that you learn more about the characters as they grow and develop through this act.

Usability tests should typically consist of five participants, according to Jakob Nielsen, who found that that number of users can typically identify the majority of the issues:” As you add more and more users, you learn less and less because you will keep seeing the same things again and again… After the fifth user, you are wasting your time by observing the same findings repeatedly but not learning much new.”

There are parallels with storytelling here too, if you try to tell a story with too many characters, the plot may get lost. With fewer participants, each user’s struggles will be more memorable and accessible to other stakeholders when presenting the research. This can help convey the issues that need to be addressed while also highlighting the value of doing 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 consider in-person usability tests like watching a movie as opposed to remote testing like attending a play. There are advantages and disadvantages to each. Usability research in person is a much more valuable learning experience. Stakeholders can experience the sessions 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 take usability testing into the field by creating a replica of the space where users interact with the product and then conduct your research there. Or you can conduct your research by meeting users at their locations. With either option, you get to see how things work in context, things come up that wouldn’t have in a lab environment—and conversion can shift in entirely different directions. 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. In-person usability tests add a level of detail that remote usability tests frequently lack.

That’s not to say that the “movies” —remote sessions—aren’t a good option. A wider audience can be obtained from remote sessions. They allow a lot more stakeholders to be involved in the research and to see what’s going on. 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.

The advantage of usability testing, whether conducted remotely or in person, is that you can ask real users questions to understand their reasoning and understanding of the problem. This can help you not only identify problems but also glean why they’re problems in the first place. Additionally, you can test your own hypotheses and determine whether your reasoning is correct. By the end of the sessions, you’ll have a much clearer picture of how usable the designs are and whether they work for their intended purposes. The excitement centers on Act 2, but there are also potential surprises in that Act. 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 is sometimes seen as expendable. Usability testing is often the only method of research that some stakeholders believe they ever need, especially in this regard. In fact, if the designs that you’re evaluating in the usability test aren’t grounded in a solid understanding of your users ( foundational research ), there’s not much to be gained by doing usability testing in the first place. Because you’re narrowing the scope of what you’re receiving feedback on 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 just feedback on a particular design.

On the other hand, if you only do foundational research, while you might have set out to solve the right problem, you won’t know whether the thing that you’re building will actually solve that. This demonstrates the value of conducting both directional and foundational research.

In act two, stakeholders will—hopefully—get to watch the story unfold in the user sessions, which creates the conflict and tension in the current design by surfacing their 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, whereas the first two acts are about understanding the context and the tensions that can compel stakeholders to act. While it’s important to have an audience for the first two acts, it’s crucial that they stick around for the final act. That includes all members of the product team, including developers, UX experts, business analysts, delivery managers, product managers, and any other parties who have a say in the coming development. It allows the whole team to hear users ‘ feedback together, ask questions, and discuss what’s possible within the project’s constraints. 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 is the narrator, who paints a picture of the issues and what the future of the product could look like given the things that the team has learned. They provide the stakeholders with their suggestions and suggestions for how to create this vision.

Nancy Duarte in the Harvard Business Review offers an approach to structuring presentations that follow a persuasive story. 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 type of structure aligns well with research results, and particularly results from usability tests. It provides proof for “what is “—the issues you’ve identified. And “what could be “—your recommendations on how to address 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 as visual as quick sketches of a potential solution to a problem. These can help generate conversation and momentum. And this continues until the session is over when you’ve concluded by bridging the gaps and offering suggestions for improvement. This is the part where you reiterate the main themes or problems and what they mean for the product—the denouement of the story. 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 of a good story:

Act one: You meet the protagonists ( the users ) and the antagonists ( the problems affecting users ). This is the plot’s beginning. In act one, researchers might use methods including contextual inquiry, ethnography, diary studies, surveys, and analytics. These techniques can produce personas, empathy maps, user journeys, and analytics dashboards.

Act two: Next, there’s character development. The protagonists encounter problems and challenges, which they must overcome, and there is conflict and tension. In act two, researchers might use methods including usability testing, competitive benchmarking, and heuristics evaluation. Usability findings reports, UX strategy documents, usability guidelines, and best practices can be included in the output of these.

Act three: The protagonists triumph and you see what a better future looks 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 plays a variety of roles, including producer, director, and storyteller. The participants have a small role, but they are significant characters ( in the research ). And the audience is the audience, as well. But the most important thing is to get the story right and to use storytelling to tell users ‘ stories through research. By the end, the parties should have a goal and a desire to solve 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. In the end, user research is beneficial for everyone, and all you need to do is pique stakeholders ‘ interest in how the story ends.

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.

There are no Lonely Planet and some tour guides for those of you who want to personalize because successful personalization depends so much on each group’s talent, technology, and market position.

But you can ensure that your group has packed its carriers rationally.

There’s a DIY method to increase your chances for victory. You’ll at least at least disarm your boss ‘ irrational exuberance. Before the group you’ll need to properly plan.

It’s known as prepersonalization.

Behind the audio

Take into account Spotify’s DJ feature, which was introduced last season.

We’re used to seeing the polished final outcome of a personalization function. A personal have had to be conceived, budgeted, and prioritized before the year-end prize, the making-of-backstory, or the behind-the-scenes success chest. Before any customisation have goes live in your product or service, it lives amid a delay of valuable ideas for expressing consumer experiences more automatically.

So how do you decide where to position your personalisation wagers? How do you design regular interactions that didn’t journey up users or—worse—breed mistrust? We’ve discovered that several budgeted programs second required one or more workshops to join key stakeholders and domestic customers of the technology in order to justify their continuous investments. Make it count.

We’ve closely monitored the same evolution with our consumers, from major software to young companies. In our experience with working on small and large personalization work, a program’s best monitor record—and its capacity to weather tough questions, work steadily toward shared answers, and manage its design and engineering efforts—turns on how successfully these prepersonalization activities play out.

Successful seminars consistently save time, money, and overall well-being by separating successful potential endeavors from unsuccessful ones.

A personalization training involves a yearlong work of testing and function development. It’s never a technical load 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 automations ( whether rules-based or machine-generated )
3. mature features or standalone product development ( like Spotify’s DJ experience )?

This is why we created our democratic personalization platform and why we’re field-testing an following deck of cards: we believe that there’s a foundation grammar, a set of “nouns and verbs” that your organization can use to style experiences that are customized, personalized, or automated. These cards won’t be necessary for you. But we strongly recommend that you create something similar, whether that might be digital or physical.

Set the timer for the kitchen.

How long does it take to cook up a prepersonalization workshop? The evaluation activities that we suggest include can last for a number of weeks ( and frequently do ). For the core workshop, we recommend aiming for two to three days. 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 engagement as you concentrate on the potential, the readiness and drive of your team, and your leadership.
1. Plan your work: This is the heart of the card-based workshop activities where you specify a plan of attack and the scope of work.
2. Work your plan: This stage consists of making it possible for team members to individually pitch their own pilots that each include a proof-of-concept project, business case, and operating model.

Give yourself at least a day, split into two large time blocks, to power through a concentrated version of those first two phases.

Kickstart: Apt your appetite

We call the first lesson the “landscape of connected experience“. It looks at the possibilities for personalization in your organization. A connected experience, in our parlance, is any UX requiring the orchestration of multiple systems of record on the backend. A marketing-automation platform and a content-management system could be used together. It could be a digital-asset manager combined with a customer-data platform.

Create a conversation by mentioning consumer and business-to-business examples of connected experience interactions that you admire, find familiar, or even dislike. 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. Here’s a list of 142 different interactions to jog your thinking.

The table must be set up for this. What are the possible paths for the practice in your organization? Here’s a long-form primer and a strategic framework for a broader view.

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 ). In our cards, we break down connected experiences into five categories: functions, features, experiences, complete products, and portfolios. Size your own build here. This will help to draw attention to the benefits of ongoing investment as well as the difference between what you deliver right now and what you want to deliver in the future.

Next, have your team plot each idea on the following 2×2 grid, which lays out the four enduring arguments 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 decide where their focus should be placed for your product or service. Naturally, you can’t prioritize all of them. Here, the goal is to demonstrate how various departments may view their own advantages over the effort, which can be different 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 your customer journey well documented? Will compliance with data and privacy be a significant challenge? Do you have content metadata needs that you have to address? It’s just a matter of acknowledging the magnitude of that need and finding a solution ( we’re fairly certain that you do ). 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.

Effectively collaborating and managing expectations is critical to your success. Consider the potential obstacles to your upcoming progress. Press the participants to name specific steps to overcome or mitigate those barriers in your organization. As research has shown, personalization initiatives face a number of common obstacles.

At this point, you’ve hopefully discussed sample interactions, emphasized a key area of benefit, and flagged key gaps? You’re all set to go on, good.

Hit that test kitchen

What will you need next to bring your personalized recipes to life. 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 presents the question: Where do you begin when you’re configuring a connected experience?

The key here is to avoid treating the installed software like some imagined kitchen from a fantasy remodeling project ( as one of our client executives humorously put it ). These software engines are more like test kitchens where your team can begin devising, tasting, and refining the snacks and meals that will become a part of your personalization program’s regularly evolving menu.

Over the course of the workshop, the ultimate menu of the prioritized backlog will come together. And creating “dishes” is the way that you’ll have individual team stakeholders construct personalized interactions that serve their needs or the needs of others.

The dishes will be made using recipes that have predetermined ingredients.

Verify your ingredients

You’ll ensure that you have everything you need to create your desired interaction ( or that you can determine what needs to be added to your pantry like a good product manager ) and that you have validated with the right stakeholders present. These ingredients include the audience that you’re targeting, content and design elements, the context for the interaction, and your measure for how it’ll come together.

Not just discovering requirements, it is. Documenting your personalizations as a series of if-then statements lets the team:

1. compare findings to a common method 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 between all important performance indicators and performance metrics.

This helps you streamline your designs and your technical efforts while you deliver a shared palette of core motifs of your personalized or automated experience.

Create a recipe.

What ingredients are important to you? Consider the construct “what-what-when-why”

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

Five years ago, we developed these cards and card categories for the first time. We regularly play-test their fit with conference audiences and clients. And there are still 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. Nurture personalization: When a guest or an unknown visitor interacts with a product title, a banner or alert bar appears that makes it easier for them to encounter a related title they may want to read, saving them time.
2. Welcome automation: An email is sent when a newly registered user is a subscriber and is able to highlight the breadth of the content catalog.
3. Winback automation: Before their subscription lapses or after a recent failed renewal, a user is sent an email that gives them a promotional offer to suggest that they reconsider renewing or to remind them to renew.

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, which shift from focusing on cookbooks to focusing on customers, might seem more nuanced. Individual” cooks” will pitch their recipes to the team, using a common jobs-to-be-done format so that measurability and results are baked in, and from there, the resulting collection will be prioritized for finished design and delivery to production.

Architecture must be improved to produce better kitchens.

Simplifying a customer experience is a complicated effort for those who are inside delivering it. Avoid those who make up their mind. 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. Like a sparse pantry, every organization has metadata debt to go along with its technical debt, and this creates a drag on personalization effectiveness. For instance, your AI’s output quality is in fact impacted by your IA. Spotify’s poster-child prowess today was unfathomable before they acquired a seemingly modest metadata startup that now powers its underlying information architecture.

You can withstand the heat without a doubt.

Personalization technology opens a doorway into a confounding ocean of possible designs. Only a deliberate and cooperative approach will produce the desired outcome. So banish the dream kitchen. Instead, head to the test kitchen to save time, preserve job security, and avoid imagining the creative concepts that come from your organization’s masters. There are meals to serve and mouths to feed.

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, if you use the same cookbook and the same recipes, you’ll have solid ground for success. We designed these activities to make your organization’s needs concrete and clear, long before the hazards pile up.

Although there are associated costs associated with purchasing this kind of technology and product design, your time well spent is on sizing up and confronting your unique situation and digital skills. Don’t squander it. The pudding is the proof, as they say.

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 systems or idea 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 development of internet requirements

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 improved server-side software, the first period of internet programs started with content-management methods (especially those used in blogs like Blogger, Grey Matter, Movable Type, and WordPress ) In the mid-2000s, AJAX opened gates for sequential interaction between the front end and back finish. Pages had now revise their content without having to reload. A grain of Script frameworks like Prototype, YUI, and ruby arose to aid developers develop more credible client-side conversation across browsers that had wildly varying levels of standards support. Techniques like picture alternative enable the use of fonts by skilled developers and developers. And technology like Flash made it possible to include movies, sports, and even more engagement.

The economy was reenergized by these new tools, requirements, and methods in many ways. Web style flourished as creators and designers explored more different styles and designs. However, we also relied heavily on tricks. Early CSS was a huge improvement over table-based layouts when it came to basic layout and text styling, 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. Display and photo substitute for specialty styles was a great start toward varying the designs from the big five, but both tricks introduced convenience and efficiency issues. And JavaScript libraries made it simple for anyone to add a dash of interaction to pages, even at the expense of double, even quadrupling, the download size of basic websites.

The web as software platform

The front-end and back-end symbiosis continued to improve, leading to the development of the modern web application. 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. Along with these tools, there were additional options, such as shared package libraries, build automation, and collaborative version control. What was once primarily an environment for linked documents became a realm of infinite possibilities.

Mobile devices increased in their capabilities as well, and they gave us access to the internet while we were traveling. Mobile apps and responsive design opened up opportunities for new interactions anywhere and any time.

This fusion of potent mobile devices and potent development tools contributed to the growth of social media and other centralized tools for user interaction and consumption. As it became easier and more common to connect with others directly on Twitter, Facebook, and even Slack, the desire for hosted personal sites waned. Social media made connections on a global scale, with both positive and negative outcomes.

Want a much more extensive history of how we got here, with some other takes on ways that we can improve? ” Of Time and the Web” was written by Jeremy Keith. Or check out the” Web Design History Timeline” at the Web Design Museum. A fun tour of” Internet Artifacts” is also available from Neal Agarwal.

Where we are now

It seems like we’ve been at a new significant inflection point over the past couple of years. As social-media platforms fracture and wane, there’s been a growing interest in owning our own content again. There are many different ways to create a website, from the tried-and-true classic of hosting plain HTML files to static site generators to content management systems of all varieties. The fracturing of social media also comes with a cost: we lose crucial infrastructure for discovery and connection. The IndieWeb‘s Webmentions, RSS, ActivityPub, and other tools can assist with this, but they’re still largely underdeveloped and difficult to use for the less geeky. We can build amazing personal websites and add to them regularly, but without discovery and connection, it can sometimes feel like we may as well be shouting into the void.

Browser support for CSS, JavaScript, and other web components has increased, particularly with initiatives like Interop. New technologies gain support across the board in a fraction of the time that they used to. I frequently find out about a new feature and check its browser support only to discover that its coverage has already exceeded 80 %. Nowadays, the barrier to using newer techniques often isn’t browser support but simply the limits of how quickly designers and developers can learn what’s available and how to adopt it.

We can prototype almost any idea today with just a few commands and a few lines of code. All the tools that we now have available make it easier than ever to start something new. However, as we upgrade and maintain these frameworks, we eventually pay the upfront costs that these frameworks may initially save in terms of our technical debt.

If we rely on third-party frameworks, adopting new standards can sometimes take longer since we may have to wait for those frameworks to adopt those standards. These frameworks, which previously made it easier to adopt new techniques sooner, have since evolved into obstacles. These same frameworks often come with performance costs too, forcing users to wait for scripts to load before they can read or interact with pages. And frequently, when scripts fail ( whether due to poor code, network problems, or other environmental factors ), users are left with blank or broken pages.

Where do we go from here?

Hacks of today help to shape standards for the future. 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. So what can we do to create the future we want for the web?

Build for the long haul. Optimize for performance, for accessibility, and for the user. weigh the costs of those user-friendly tools. They may make your job a little easier today, but how do they affect everything else? What does each user pay? To future developers? To adoption of standards? Sometimes the convenience may be worth it. Sometimes it’s just a hack that you’ve gotten used to. And sometimes it’s holding you back from even better options.

Start with standards. Standards continue to evolve over time, but browsers have done a remarkably good job of continuing to support older standards. The same isn’t always the case with third-party frameworks. Sites built with even the hackiest of HTML from the’ 90s still work just fine today. Even after a few years, the same can’t be said about websites created with frameworks.

Design with care. Consider the effects of each choice, whether your craft is code, pixels, or processes. The convenience of many a modern tool comes at the cost of not always understanding the underlying decisions that have led to its design and not always considering the impact that 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 constantly learn, you also develop. 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 in your brain, and the techniques you learn in one day may be used to inform different experiments in the future.

Play, experiment, and be weird! This website we created is the most incredible experiment. It’s the single largest human endeavor in history, and yet each of us can create our own pocket within it. Be brave and make new friends. Build a playground for ideas. Create absurd experiments in your own crazy science lab. Start your own small business. There has never been a place where we have more room to be creative, take risks, and discover our potential.

Share and amplify. As you play, experiment, and learn, share what has 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 ahead and create a masterpiece.

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 incorporate our values into the products we produce, and let’s improve the world for everyone. Create that thing that only you are uniquely qualified to make. Then, share it, improve it, re-create it, or create something new. Learn. Make. Share. Grow. Rinse and repeat. Everything will change whenever you believe you have mastered the web.

I’d like you to consider this a “yes … and” piece to complement Joe’s post. I’m just trying to contradict what he’s saying, but I’m just trying to give some context to initiatives and opportunities where AI can make a difference for 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; instead, I want to take a moment to talk about what’s possible so that we can get there one day.

Other words

Joe’s article spends a lot of time addressing computer-vision types ‘ ability to create alternative words. He raises a number of true points about the state of affairs 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. He argues to be accurate that the state of image research is currently very poor, especially for some image types, in large part due to the lack of context-based analysis that exists in the AI systems ( which is a result of having separate “foundation” models for text analysis and image analysis ). Today’s models aren’t trained to distinguish between images that are contextually relevant ( should probably have descriptions ) and those that are purely decorative ( couldn’t possibly need a description ) either. However, I still think there’s possible in this area.

As Joe points out, far word authoring by human-in-the-loop should definitely be a thing. And if AI can intervene and provide a starting point for alt text, even if the quick 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 station a design to examine image usage in context, it might help us more quickly determine which images are likely to be elegant and which ones are likely to need a description. That will help clarify which situations require image descriptions, and it will increase authors ‘ effectiveness in making their sites more visible.

While complex images—like graphs and charts—are challenging to describe in any sort of succinct way ( even for humans ), the image example shared in the GPT4 announcement points to an interesting opportunity as well. Let’s say you came across a map that was simply the name of the table and the type of visualization it was: Pie table comparing smartphone use to have phone use among US households making under$ 30, 000 annually. ( That would be a pretty bad alt text for a chart because it frequently leaves many unanswered questions about the data, but let’s just assume that was the description in place. ) If your website knew that that picture was a pie graph ( because an onboard model concluded this ), imagine a world where people could ask questions like these about the creative:

• Do more people use smartphones or other types of smartphones?
• How many more?
• Is there a group of people that don’t fall into either of these buckets?
• That number, how many?

For a moment, the chance to learn more about images and data in this way could be revolutionary for people with low vision and blindness as well as for those with various forms of color blindness, cognitive disabilities, and other issues. It could also be useful in educational contexts to help people who can see these charts, as is, to understand the data in the charts.

What if you could ask your browser to make a complicated chart simpler? What if you asked it to separate a single line from a line graph? What if you could ask your browser to transpose the colors of the different lines to work better for form of color blindness you have? What if you could ask it to switch colors for patterns? That seems like a possibility given the chat-based interfaces and our current ability to manipulate images in today’s AI tools.

Now imagine a purpose-built model that could extract the information from that chart and convert it to another format. For instance, it might be able to convert that pie chart (or, better yet, a number of pie charts ) into more usable ( and useful ) formats, like spreadsheets. That would be incredible!

Matching algorithms

When Safiya Umoja Noble chose to call her book Algorithms of Oppression, she hit the nail on the head. Although her book focused on the ways that search engines can foster racism, I believe it to be equally accurate to say that all computer models have the potential to amplify conflict, bias, and intolerance. Whether it’s Twitter always showing you the latest tweet from a bored billionaire, YouTube sending us into a Q-hole, or Instagram warping our ideas of what natural bodies look like, we know that poorly authored and maintained algorithms are incredibly harmful. A large portion of this is attributable to the lack of diversity in those who create and shape them. There is still a lot of potential for algorithm development when these platforms are built with inclusive features in mind.

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

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

Imagine that a social media company’s recommendation engine was tuned to analyze who you’re following and if it was tuned to prioritize follow recommendations for people who talked about similar things but who were different in some key ways from your existing sphere of influence. For instance, if you followed a group of nondisabled white male academics who spoke about AI, it might be advisable to follow those who are disabled, aren’t white, or aren’t men who also speak about AI. If you followed its advice, you might gain a more in-depth 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 assist 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 might have heard about the voice-preserve offerings from Microsoft, Acapela, or others, or have seen the VALL-E paper or Apple’s Global Accessibility Awareness Day announcement. It’s possible to train an AI model to replicate your voice, which can be a tremendous boon for people who have ALS ( Lou Gehrig’s disease ) or motor-neuron disease or other medical conditions that can lead to an inability to talk. We need to approach this tech responsibly because it has the potential to have a truly transformative impact, which is why it can also be used to create audio deepfakes.
• voice recognition Researchers like those in the Speech Accessibility Project are paying people with disabilities for their help in collecting recordings of people with atypical speech. As I type, they are currently hiring people with Parkinson’s and related conditions, and they intend to expand this list as the project develops. 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 result in more inclusive data sets that will enable them to use their computers and other devices more easily and with just their voices.
• Text transformation. The most recent generation of LLMs is capable of altering already-existing text without giving off hallucinations. This is incredibly empowering for those who have cognitive disabilities and who may benefit from text summaries or simplified versions, or even text that has been prepared for bionic reading.

The importance of diverse 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. Our differences must be reflected in the data we use to develop new models, and those who provide it need to be compensated for doing so. More robust models are produced by inclusive data sets, which 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 uses ableist language without using it? You may be able to use existing data sets to build a filter that can intercept and remediate ableist language before it reaches readers. Despite this, AI models won’t soon replace human copy editors when it comes to sensitivity reading.

Want a coding copilot who can provide you with useful recommendations after the jump? Train it on code that you know to be accessible.

I have no doubts about how dangerous AI will be for people today, tomorrow, and for the rest of the world. However, I also think we should acknowledge this and make thoughtful, thoughtful, and intentional changes to 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 supporting the development of this article, Ashley Bischoff for providing me with invaluable editorial support, and, of course, Joe Dolson for the prompt.

I have a creative side. Alchemy is what I do. It is a secret. I don’t perform it as much as I let it be done by me.

I have a creative side. Not all aspiring artists approve of this brand. No everyone sees themselves in this way. Some innovative persons incorporate technology into their work. That is the way they are, and I take that into account. Perhaps I even have a small fear for them. However, my being and approach are unique.

It distracts one to apologize and qualify in progress. My mind uses that to destroy me. I put it off for the moment. I may regret and be qualified at any time. after I’ve said what I should have. which is difficult enough.

Except when it is simple and flows like a beverage valley.

Sometimes it does go that method. Maybe what I need to make arrives right away. When I say something at that time, I’ve learned not to say it because people often don’t work hard enough to acknowledge that the idea is the best idea even when you know it’s the best idea.

Sometimes I just work until the thought strikes me. Maybe it arrives right away, but I don’t remind people for three days. Sometimes I blurt out the plan so quickly that I didn’t stop myself. like a child who discovered a reward in a box of Cracker Jacks. Often I get away with this. Yes, that is the best plan, but sometimes another people disagree. The majority of the time, they don’t, and I regret that joy has faded.

Passion should only be saved for the meet, when it will matter. not the informal gathering that two different gatherings precede that meeting. Nothing understands why we hold these gatherings. We keep saying we’re going to get rid of them, but we just keep trying to find different ways to get them. They occasionally yet are good. But occasionally they are a hindrance to the actual labor. Depending on what you do and where you do it, the ratio between when conferences are valuable and when they are a sad distraction vary. And who you are and how you go about doing it. Once, I digress. I have a creative side. That is the design.

Often, a lot of diligent and persistent work ends up with something that is rarely useful. Often I have to accept that and move on to the next task.

Don’t inquire about the procedure. I have a creative side.

I have a creative side. I have no control over my desires. And I have no control over my best tips.

I can nail ahead, fill in the blanks, or use graphics or information, which occasionally works. I can go for a move, which occasionally works. There is a Eureka, which has nothing to do with boiling pots and sizzling oil, and I may be making dinner. I frequently have a sense of direction when I awaken. The idea that may have saved me disappears almost as frequently as I become aware and a part of the world once more as a senseless wind of oblivion. For imagination, in my opinion, originates in that other world. the one that we enter in ambitions and, possibly, before and after suicide. But writers should be asking this, and I am not a writer. I have a creative side. Theologians should circulate mass armies throughout their artistic globe, which they claim to be true. But that is yet another diversion. And it’s miserable. Possibly on a much bigger issue than whether or not I am creative. But that’s not how I came around, though.

Often the outcome is mitigation. And suffering. Do you know the actor who is tortured by the cliché? Even when the artist ( this place that noun in quotes ) attempts to write a sweet drink jingle, a call in a worn-out comedy, or a budget ask, it’s true.

Some individuals who detest being called artistic perhaps been closeted artists, but that’s between them and their gods. No act here. Your facts is also true. But I should take care of me.

Artists are recognized as designers.

Disadvantages are aware of cons, just like queers are aware of queers, just like real rappers are aware of genuine rappers are aware of cons. People have a lot of regard for artists. We revere, follow, and nearly deify the great types. Of course, it is horrible to revere any person. We’ve been given a warning. Better is what we are. We are aware that people are really people. Because they are clay, like us, they squabble, they are depressed, they regret making the most important decisions, they are poor and hungry, they can be violent, and they can be as ridiculous as we can. But. But. However, they produce something incredible. They give birth to something that may not occur before them and couldn’t exist without. They are the inspirations of thought. And I suppose I should add that they are the mother of technology because it’s just lying it. Ba ho bum! Okay, that’s all said and done. Continue.

Because we compare our personal small accomplishments to those of the great ones, designers denigrate our own. Wonderful video! I‘m not Miyazaki, so I‘m not. Greatness is then that. That is glory directly from God’s heart. This unsatisfied small thing I created? It essentially fell off the turnip vehicle. And the carrots weren’t actually new.

Artists is aware that they are at best Some. Yet Mozart’s original artists hold that opinion.

I have a creative side. In my hallucinations, my previous artistic managers are the ones who judge me because I haven’t worked in advertising in 30 times. They are correct in doing so. When it really matters, my brain goes flat because I am too stupid and complacent. There is no treatment for artistic mania.

I have a creative side. Every experience I create has the potential to make Indiana Jones look older while snoring in a deck head. The more I pursue my creative endeavors, the faster I progress in my work, and the more I slog through lines and gaze blankly before beginning that task.

I can move ten times more quickly than those who aren’t innovative, those who have just been creative for a short while, and those who have just had a short time of creative work. Only that I spend twice as long as they do putting the job away before I work ten times as quickly as they do. When I put my mind to it, I am so confident in my ability to do a great career. I am completely dependent on the excitement scramble of delay. The leap also terrifies me.

I am hardly a painter.

I have a creative side. never a performer. Though as a boy, I had a dream that I would one day become that. Some of us criticize our abilities and fear our own selves because we are not Michelangelos and Warhols. That is narcissism, but at least we don’t practice politicians.

I have a creative side. Despite my belief in reason and science, I make decisions based on my own senses and instincts. and accept both the successes and the disasters that come with them.

I have a creative side. Every term I’ve said these may irritate another artists who have different viewpoints. Ask two artists a topic and find three opinions. No matter how we perhaps think about it, our debate, our passion for it, and our responsibility to our own truth, at least in my opinion, are the best indications that we are artists.

I have a creative side. I lament my lack of taste in the areas of human knowledge that I know quite small, that is to say about everything. And I put my ego before everything else in the areas that are most important to me, or perhaps more precisely, to my obsessions. Without my passions, I had probably have to spend time staring living in the eye, which almost none of us can do for very long. No seriously. Actually, not. Because living is so difficult to handle when you really look at it.

I have a creative side. I think that when I’m gone, some of the good parts of me will stay in the head of at least one additional person, just like a family does.

Working frees me from worrying about my job.

I have a creative side. I worry that my little product will disappear unexpectedly.

I have a creative side. I’m too busy making the next thing to devote too much time to it, especially since practically everything I create did achieve the level of success I conceive of.

I have a creative side. I think that approach is the greatest secret. I think I have to consider it so strongly that I actually made the foolish decision to publish an essay I wrote without having to go through or edit. I swear I didn’t do this frequently. But I did it right away because I was even more frightened of forgetting what I was saying because I was afraid of you seeing through my sad movements toward the beautiful.

There. I believe I’ve said it.

One of the most powerful sweet skills we have at our disposal is the ability to work together to improve our designs while developing our own abilities and perspectives, regardless of how it is used or what it might be called.

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 on projects, lower confidence, and long-term, undermine trust and teamwork. Quality opinions can be a revolutionary force.

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 adjusted for isolated and distributed job settings?

We can find a long history of sequential comments on the web: code was written and discussed on mailing lists since the beginning of open source. Currently, engineers engage on pull calls, developers post in their favourite design tools, project managers and sprint masters exchange ideas on tickets, and so on.

Design analysis is often the label used for a type of input that’s provided to make our job better, jointly. It generally shares many of the concepts with comments, but it also has some differences.

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. The one that I personally like best—because it’s obvious and actionable—is this one from Lara Hogan.

This formula is typically used to provide feedback to people, but it also fits really well in a design criticism because it finally addresses one 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 things that needs to be improved. If you keep the three components of the equation in mind, you’ll have a mental unit that can help you become more precise and effective.

Here is a reply that could be included in some feedback, and it might appear fair at first glance because it appears to partially fulfill the requirements. But does it?

Not confident about the keys ‘ patterns and hierarchy—it feels off. May you alter them?

Observation for style feedback doesn’t really mean pointing out which part of the software your input refers to, but it also refers to offering a viewpoint that’s as specific as possible. Do you offer the user’s viewpoint? Your expert perspective? A business perspective? From the perspective of the project manager? A first-time user’s perspective?

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

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.

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

The question approach is meant to provide open guidance by eliciting the critical thinking in the designer receiving the feedback. Notably, in Lara’s equation she provides a second approach: request, which instead provides guidance toward a specific solution. While that’s a viable option for feedback in general, in my experience, going back to the question approach typically leads to the best solutions because designers are generally more at ease in being given an open space to explore.

The difference between the two can be exemplified with, for the question approach:

I anticipate one to go forward and the other to go back when I see these two buttons. 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:

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

At this point in some situations, it might be useful to integrate with an extra why: why you consider the given suggestion to be better.

I anticipate one to go forward and the other to go back when I see these two buttons. 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 the question approach or the request approach can also at times be a matter of personal preference. I did rounds of anonymous feedback and I reviewed feedback with other people a while back when I was putting a lot of effort into improving my feedback. 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 changed 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 one person in this other team who now preferred specific guidance. So I adapted my feedback for them 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. No, but also yes. Let’s explore both sides.

No, this kind of feedback is effective because the length is a byproduct of clarity, and giving this kind of feedback can provide precisely enough information for a sound fix. Also if we zoom out, it can reduce future back-and-forth conversations and misunderstandings, improving the overall efficiency and effectiveness of collaboration beyond the single comment. Imagine that in the example above the feedback were instead just,” Let’s make sure that all screens have the same two forward and back buttons”. The designer receiving this feedback wouldn’t have much to go by, so they might just implement the change. In later iterations, the interface might change or they might introduce new features—and maybe that change might not 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 style of feedback is not always efficient because the points in some comments don’t always need to be exhaustive, sometimes because certain changes may be obvious (” The font used doesn’t follow our guidelines” ) and sometimes because the team may have a lot of internal knowledge such that some of the whys may be implied.

Therefore, the above equation serves as a mnemonic to reflect and enhance the practice rather than a strict template for feedback. 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

Well-grounded content is the foundation of feedback, 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, and tone alone can determine whether content is rejected or welcomed.

Since our goal is to be understood and to have a positive working environment, tone is essential to work on. I’ve tried to summarize the necessary soft skills over the years using a formula that resembles that of the content receptivity equation.

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

The term “timing” describes the moment when the feedback occurs. To-the-point feedback doesn’t have much hope of being well received if it’s given at the wrong time. 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 later? Polishing work in progress? Each of these needs varies. The right timing will make it more likely that your feedback will be well received.

Attitude is the equivalent of intent, and in the context of person-to-person feedback, it can be referred to as radical candor. Before writing, it’s important to make sure the person we’re writing will actually benefit them and improve the overall project. This might be a hard reflection at times because maybe we don’t want to admit that we don’t really appreciate that person. Hopefully that’s not the case, but it can happen, and that’s okay. Acknowledging and owning that can help you make up for that: how would I write if I really cared about them? How can I avoid being passive aggressive? How can I encourage constructive behavior?

Form is relevant especially in a diverse and cross-cultural work environments because having great content, perfect timing, and the right attitude might not come across if the way that we write creates misunderstandings. 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 back, I was asking for some feedback on how I give feedback. I was given some sound advice, but I also got a surprise comment. They pointed out that when I wrote” Oh, ]… ]”, I made them feel stupid. That’s not what I meant to say! I felt really bad, and I just realized that I provided feedback to them for months, and every time I might have made them feel stupid. I was horrified … but also thankful. I quickly changed my spelling mistake by adding “oh” to my list of replaced words (your choice between aText, TextExpander, or others ) so that when I typed “oh,” it was immediately deleted.

Something to highlight because it’s quite frequent—especially in teams that have a strong group spirit—is that people tend to beat around the bush. It’s important to keep in mind that having a positive attitude doesn’t necessarily mean passing judgment on the feedback; rather, it simply means that even when you give difficult, or difficult feedback, you do so in a way that’s respectful and constructive. The nicest thing that you can do for someone is to help them grow.

We have a great advantage in giving feedback in written form: it can be reviewed by another person who isn’t directly involved, which can help to reduce or remove any bias that might be there. The best, most insightful moments for me came when I shared a comment and asked a trusted person how it sounds, how can I do it better, or even” How would you have written it”? I discovered that by seeing the two versions side by side, I’ve learned a lot.

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 reviewing it and leaving a comment. 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? Are you coming from a high-level perspective, or are you figuring out the details? Are there regressions? Which user’s point of view are you addressing when offering your feedback? Is the design iteration at a point where it would be okay to ship this, or are there major things that need to be addressed first?

Even if you’re giving feedback to a team that already has some background information on the project, providing context is helpful. And context is absolutely essential when giving cross-team feedback. If I were to review a design that might be indirectly related to my work, and if I had no knowledge about how the project arrived at that point, I would say so, highlighting my take as external.

We frequently concentrate on the negatives and attempt to list every possible improvement. That’s of course important, but it’s just as important—if not more—to focus on the positives, especially if you saw progress from the previous iteration. Although this may seem superfluous, it’s important to remember that design has a number 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. In the longer term, sharing positive feedback can help prevent regressions on things that are going well because those things will have been highlighted as important. 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.

Another way that you can improve your feedback is to depersonalize the feedback: the comments should always be about the work, never about the person who made it. 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.

In terms of actionability, one of the best approaches to help the designer who’s reading through your feedback is to split it into bullet points or paragraphs, which are easier to review and analyze one by one. You might also consider breaking up the feedback into sections or even across multiple comments if it is longer. Of course, adding screenshots or signifying markers of the specific part of the interface you’re referring to can also be especially useful.

One approach that I’ve personally used effectively in some contexts is to enhance the bullet points with four markers using emojis. A red square indicates that it is something I consider blocking, a yellow diamond indicates that it needs to be changed, and a green circle provides a thorough, positive confirmation. I also use a blue spiral � � for either something that I’m not sure about, an exploration, an open alternative, or just a note. 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—I anticipate one to go forward and the other to go back when I see these two buttons. 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 think the page is solid, and this is good enough to be our release candidate for a version 1.0.
• � � 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. Do we need to explore a different color?
• Considering the number of items on the page and the overall page hierarchy, it seems to me that the tiles should use Subtitle 2 instead of Subtitle 1. This will keep the visual hierarchy more consistent.
• � � Background—Using a light texture works well, but I wonder whether it adds too much noise in this kind of page. What is the purpose of using that?

What about giving feedback directly in Figma or another design tool that allows in-place feedback? 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 final note: say the obvious. We don’t say something because we sometimes think it’s obvious that something is either good or wrong. Or sometimes we might have a doubt that we don’t express because the question might sound stupid. Say it, that’s fine. You might have to reword it a little bit to make the reader feel more comfortable, but don’t hold it back. Good feedback is transparent, even when it may be obvious.

Another benefit of asynchronous feedback is that written feedback automatically monitors decisions. Especially in large projects,” Why did we do this”? There’s nothing better than open, transparent discussions that can be reviewed at any time, and this could be a question that arises from time to time. For this reason, I recommend using software that saves these discussions, without hiding them once they are resolved.

Content, tone, and format. Although each of these subjects offers a useful model, focusing on improving eight of the subjects ‘ focus points, including observation, impact, question, timing, attitude, form, clarity, and actionability, is a lot of work to complete at once. One effective approach is to take them one by one: first identify the area that you lack the most (either from your perspective or from feedback from others ) and start there. 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 Brie Anne Demkiw and Mike Shelton for reviewing the first draft of this article.

” Any opinion”? is perhaps one of the worst ways to ask for suggestions. It’s obscure and unfocused, and it doesn’t give a clear picture of what we’re looking for. Getting good opinions starts sooner than we might hope: it starts with the demand.

Starting the process of receiving feedback with a question may seem counterintuitive, but it makes sense if we consider that receiving feedback can be considered a form of pattern research. In the same way that we wouldn’t perform any studies without the correct questions to get the insight that we need, the best way to ask for feedback is also to build strong issues.

Design criticism is not a one-time procedure. Sure, any great comments process continues until the project is finished, but this is especially true for layout because architecture work continues iteration after iteration, from a high level to the finest details. Each stage requires its unique set of questions.

And suddenly, as with any great research, we need to examine what we got up, get to the base of its perspectives, and take action. Iteration, evaluation, and problem. This look at each of those.

The query

Being available to input is important, but we need to be specific about what we’re looking for. Any comments,” What do you think,” or” I’d love to hear your view” at the conclusion of a presentation are likely to generate a lot of divergent thoughts, or worse, to make people follow the lead of the first speaker. And next… we get frustrated because vague issues like those can change a high-level moves review into folks rather commenting on the borders of buttons. Which theme may be significant, so it might be difficult to get the team to choose the one you wanted to concentrate on.

But how do we get into this scenario? It’s a combination of various components. One is that we don’t often consider asking as a part of the input approach. Another is how healthy it is to assume that everyone else will agree with the problem and leave it alone. Another is that in nonprofessional debate, there’s usually no need to be that exact. In summary, we tend to undervalue the value of the issues, and we don’t make any improvements to them.

The work of asking good questions guidelines and focuses the criticism. It’s even a form of acceptance because it specifies what kind of opinions you’d like to receive and how you’re open to them. It puts people in the right emotional position, especially in situations when they weren’t expecting to give opinions.

There isn’t a second best method to request comments. It simply needs to be certain, and sensitivity can take several shapes. The one of stage over level is a design for design criticism that I’ve found to be particularly helpful in my coaching.

” Stage” refers to each of the steps of the process—in our event, the design process. The type of input changes as the customer research moves on to the final design. But within a single stage, one might also examine whether some assumptions are correct and whether there’s been a suitable language of the amassed opinions into updated designs as the job has evolved. The layers of user experience could serve as a starting point for potential questions. What do you want to know: Project objectives? User requirements? Functionality? the content Interaction design? Information architecture UI design? navigation planning Visual design? branding?

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

• Functionality: Is it desirable to automate account creation?
• 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: On this page, we have two competing pieces of information. Is the structure effective in communicating them both?
• User interface design: What do you think about the top-most error counter, which ensures that you can see the next error even when the error is outside 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. Exist any recommendations for resolving this?
• Visual design: Are the sticky notifications in the bottom-right corner visible enough?

The other axis of specificity is determined by how far you’d like to go with the information 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 helpful from one iteration to the next when it’s crucial to highlight the areas that have changed.

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

A quick fix is to get rid of the generic qualifiers from questions like “good,” “well,” “nice,” “bad,” “okay,” and” cool.” For example, asking,” When the block opens and the buttons appear, is this interaction good”? is possible to appear specific, but the “good” qualifier can be found in 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 uncommon, but it can occur. 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 perhaps 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 broad, and some areas may have already been thoroughly explored. In these situations, it might be useful to explicitly say that some parts are already locked in and aren’t open to feedback. Although it’s not something I’d recommend in general, I’ve found it helpful in avoiding falling into rabbit holes like those that could lead to further refinement but aren’t what’s important right now.

Asking specific questions can completely change the quality of the feedback that you receive. People who have less refined critique abilities will now be able to provide more useful feedback, and even experienced designers will appreciate the clarity and effectiveness gained from concentrating solely on what is required. 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. Many design tools have inline commenting, but many of them only display changes as a single fluid stream in the same file. In addition, these kinds of design tools automatically update shared UI components, make conversations disappear and require designs to always display the most recent version, unless these would-be useful features were manually disabled. 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 most effective way to go about designing critiques, but even if I don’t want to be too prescriptive, it might 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 type of 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 a number of benefits:

• 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 accessible for upcoming review, and conversed conversations are also always available.
• It creates a record of how the design changed over time.
• Depending on the tool, it might also make it simpler to collect and act on feedback.

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 from there, there can develop additional feedback techniques ( such as live critique, pair designing, or inline comments ).

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

1. The goal
2. The layout
3. The list of changes
4. The querys

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. In other words, I would copy and paste this into every iteration post to make it work. 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. The most recent iteration post will have everything I need if I want to know about the most recent design.

This copy-and-paste part introduces another relevant concept: alignment comes from repetition. Therefore, repeating information in posts helps to ensure 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 essence, it’s any design work. 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.

Because it makes it easier to refer to the objects, it might also be helpful to have clear names on them. Write the post in a way that helps people understand the work. It’s not much different from creating a strong 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.

Finally, as mentioned earlier, a list of the questions must be included in order to help you guide the design critique in the desired direction. Doing this as a numbered list can also help make it easier to refer to each question by its number.

Not every iteration is 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 begin coming to a decision and improving it until the design process is complete and the feature is ready.

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 start a discussion, or it might be a cumulative list of every feature that was added over the course of each iteration until the full picture is achieved.

Over time, I also started using specific labels for incremental iterations: i1, i2, i3, and so on. Although this may seem like a minor labeling tip, it can be useful in many ways:

• Unique—It’s a clear unique marker. Everyone knows where to go to review things, and it’s simple to say” This was discussed in i4″ with each project.
• 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. Exploratory, incomplete, or partial should be the definition of an argument.
• Future proof—It resolves the “final” naming problem that you can run into with versions. No more files with the title “final final complete no-really-its-done” Within each project, the largest number always represents the latest iteration.

The wording release candidate (RC ) could be used to indicate when a design is finished enough to be worked on, even if there are some areas that still need improvement and, in turn, require more iterations, such as” with i8 we reached RC” or “i12 is an RC” to indicate when it is finished.

The review

What typically occurs during a design critique is an open discussion that can be very productive between two people. This approach is particularly effective during live, synchronous feedback. However, using a different approach when we work asynchronously is more effective: adopting 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 significant advantages, making asynchronous feedback particularly effective, especially around these friction points:

1. It removes the pressure to reply to everyone.
2. It lessens the annoyance caused by swoop-by comments.
3. It lessens our personal stake.

The first friction point is having to press yourself to respond to each and every comment. Sometimes we write the iteration post, and we get replies from our team. It’s simple, straightforward, and doesn’t cause any issues. 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. If the respondent is a stakeholder or a person directly involved in the project, this might be especially true. We need to accept that this pressure is absolutely normal, and it’s human nature to try to accommodate people who we care about. When responding to all comments, it can be effective, but when we consider a design critique more like user research, we realize that we don’t need to respond to every comment, and there are alternatives in asynchronous spaces:

One is to let the next iteration speak for itself. When the design changes and we publish a follow-up iteration, that’s the response. You might tag all the people who were involved in the previous discussion, but even that’s a choice, not a requirement.
• Another option is to respond politely to acknowledge each comment, such as” Understood. Thank you”,” Good points— I’ll review”, or” Thanks. In the upcoming iteration, I’ll include these. 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 option is to quickly summarize 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 swoop-by comment, which is the kind of feedback that comes from a member of a team or non-project who might not be aware of the context, restrictions, decisions, or requirements, or of the discussions from earlier iterations, is the second friction point. 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 frequently prompt the simple thought,” We’ve already discussed this,” and it can be frustrating to have to keep saying the same thing over and over.

Let’s begin by acknowledging again that there’s no need to reply to every comment. However, a brief response with a link to the previous discussion for additional information is typically sufficient if responding to a previously litigated point might be helpful. Remember, alignment comes from repetition, so it’s okay to repeat things sometimes!

Swoop-by commenting has two benefits: first, they might point out something that isn’t clear, and second, they might serve as a reference point for someone who is first viewing the design. Sure, you’ll still be frustrated, but that might at least help in dealing with it.

The personal stake we might have in relation to the design could be the third friction point, which might cause us to feel defensive if the review turned out to be more of 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 ). In the end, putting everything in aggregate form helps us to prioritize our work more.

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 must examine it and come up with a rationale for your choice, but sometimes “no” is the best choice.

As the designer leading the project, you’re in charge of that decision. In the end, everyone has their area of specialization, and the designer is the one with the most background and knowledge to make the right choice. 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 Mike Shelton and Brie Anne Demkiw for their initial review of this article.

We’ve been conversing for a long time. Whether to present information, perform transactions, or just to check in on one another, people have yammered aside, chattering and gesticulating, through spoken discussion for many generations. Only recently have conversations started to be written, and only recently have we outsourced them to the system, a device that exhibits a significantly higher affinity for written communications than for the vernacular rigors of spoken language.

Laptops have trouble because between spoken and written speech, talk is more primitive. Machines must wrestle with the complexity of human statement, including the disfluencies and pauses, the gestures and body speech, and the variations in expression choice and spoken dialect, which may impede even the most skillfully crafted human-computer interaction. In the human-to-human situation, spoken language also has the opportunity of face-to-face call, where we can easily interpret visual interpersonal cues.

In contrast, written language develops its own fossil record of dated terms and phrases as we report it and retain utilization long after they are no longer relevant in spoken communication ( for example, the welcome” To whom it may concern” ). Because it tends to be more consistent, smooth, and proper, written word is necessarily far easier for devices to interpret and know.

Spoken dialect is not a pleasure in this regard. Besides the visual cues that mark conversations with emphasis and personal context, there are also linguistic cues and outspoken behaviors that mimic conversation in nuanced ways: how something is said, never what. Our spoken language conveys much more than the written word could ever contain, whether it be rapid-fire, low-pitched, or high-decibel, sarcastic, stilted, or sighing. So when it comes to voice interfaces—the machines we conduct spoken conversations with—we face exciting challenges as designers and content strategists.

Voice Compositions

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 ( ). We typically strike up a discussion in the following ways:

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

A single conversation from beginning to end that achieves some outcome for the user, starting with the voice interface’s first greeting and ending with the user exiting the interface, also fits into these three categories, which I refer to as transactional, informational, and prosocial. 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 it may not always be one 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. Additionally, there is a debate about whether users actually prefer organic human conversations that start with prosocial voiceovers and then seamlessly transition to 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 different types of conversations we can have with one another that a voice interface can also have easily, including one that is transactional and one that is informational, teaching us something new ( “discuss a musical” ).

Transactional voice interactions

When you order a Hawaiian pizza with extra pineapple, you’re typically having a conversation and a voice interaction when you’re tapping buttons on a food delivery app. 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 ).

How are things going, Alison?

Burhan: Hi, welcome to Crust Deluxe! It’s chilly outside. How can I help you?

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

Burhan: Sure, what size?

Large, Alison.

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 will cost$ 13.55 and take 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. Conversations that are transactional have certain characteristics: they are direct, precise, and cost-effective. They quickly dispense with pleasantries.

Informational voice interactions

Meanwhile, some conversations are primarily about obtaining information. Alison might visit Crust Deluxe with the sole intention of placing an order, but she might not want to leave 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. We’re after much more than just a prosocial mini-conversation at the beginning, even though we do it once more to establish politeness.

How are things going, Alison?

Burhan: Hi, welcome to Crust Deluxe! It’s chilly outside. How can I help you?

Alison: Can I ask a few questions?

Burhan: Of course! Go right ahead.

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

Burhan: Absolutely! On request, we can make any pie halal. We also have lots of vegetarian, ovo-lacto, and vegan options. Do you have any other dietary restrictions in mind?

Alison: What about gluten-free pizzas?

Burhan: For both our deep-dish and thin-crust pizzas, we can definitely make a gluten-free crust for you, without a problem. Anything else I can answer for you?

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

Burhan: Anytime, come back soon!

This dialogue is radically different. Here, the goal is to get a certain set of facts. Informational conversations are research expeditions to gather data, news, or facts, or they are investigative quests for the truth. Voice interactions that are informational might be more long-winded than transactional conversations by necessity. Responses are typically longer, more in-depth, and carefully communicated so that the customer is aware of the important lessons.

Voice Interfaces

Voice interfaces essentially use speech to assist users in accomplishing their objectives. But simply because an interface has a voice component doesn’t mean that every user interaction with it is mediated through voice. We’re most concerned in this book with pure voice interfaces because multimodal voice interfaces can lean on visual components like screens as crutches, which are completely dependent on spoken conversation and lack any visual component, making them much more nuanced and challenging to deal with.

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.

IVR ( interactive voice response ) 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. We became familiar with the first real voice interfaces that could actually be spoken to without having to deal with overburdened customer service representatives as a result of the development of interactive voice response ( IVR ) systems.

IVR systems allowed organizations to reduce their reliance on call centers but soon became notorious for their clunkiness. Similar to the corporate world, these systems were primarily created as metaphorical switchboards to direct customers to a real phone agent (” Say Reservations to book a flight or check an itinerary” ), and chances are you’ll have 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).

IVR systems have a reputation for having less scintillating conversations than we’re used to in real life ( or even in science fiction ), despite being extremely repetitive and monotonous.

Screen readers

The invention of the screen reader, a tool that converts visual content into synthesized speech, was a development of IVR systems in parallel. For Blind or visually impaired website users, it’s the predominant method of interacting with text, multimedia, or form elements. Perhaps the closest thing we have today to an out-of-the-box implementation of content delivered through voice is represented by screen readers.

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 ( ). The first IBM Screen Reader for text-based computers was created by Jim Thatcher in the same year, which was 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. Screen readers started facilitating quick 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 with the introduction of semantic HTML and especially ARIA roles in 2008, enabling speedy interactions with the pages. In other words, screen readers for the web “provide mechanisms that translate visual design constructs—proximity, proportion, etc. —into useful information,” according to Aaron Gustafson in A List Apart. ” At least they do when documents are authored thoughtfully” ( ).

There is a big draw for screen readers: they’re challenging to use and relentlessly verbose, despite being incredibly instructive for voice interface designers. 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. Working with web-based interfaces takes a cognitive toll for many screen reader users.

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

I disliked the operation of Screen Readers from the beginning. Why are they designed the way they are? It makes no sense to present information visually before converting it to audio only after that. 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, users of the visual interface have the advantage of freely scurrying around the viewport to find information without getting too close to it. Blind users, meanwhile, are obligated to listen to every utterance synthesized into speech and therefore prize brevity and efficiency. Users with disabilities who have long had no choice but to use clumsy screen readers might find that voice interfaces, especially more contemporary voice assistants, provide a more streamlined experience.

Voice assistants

Many of us immediately associate voice assistants with the popular subset of voice interfaces found in living rooms, smart homes, and offices with the film A Space Odyssey or with Majel Barrett’s voice as the omniscient computer from 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 because of their assistive potential, they are quickly gaining more and more attention from accessibility advocates.

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 created their vision for a” semantic web agent” that would carry out routine tasks like” checking calendars, making appointments, and finding locations” ( hinter paywall ). It wasn’t until 2011 that Apple’s Siri finally entered the picture, making voice assistants a tangible reality for consumers.

There are a lot of variations in the programmability and customization of some voice assistants compared to others ( Fig. 1 ). As a result of the breadth of voice assistants available today ( Fig. 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. There are no other means by which developers can interact with Siri at a low level, aside from predefined categories of tasks like sending messages, hailing rideshares, making restaurant reservations, and other things, so even now it isn’t possible to program Siri to perform arbitrary functions.

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, developers who feel stifled by the limitations of Siri and Cortana are increasingly using programmable voice assistants that are capable of customization and extensibility. 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. Users today have the option to choose from among the thousands of custom-built skills available in the Google Assistant and Amazon Alexa ecosystems.

As businesses like Amazon, Apple, Microsoft, and Google continue to occupy their positions, they’re also selling and open-sourcing an unheard array of tools and frameworks for designers and developers that aim to make creating voice interfaces as simple 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. In contrast, many development platforms, like Google’s Dialogflow, now support omnichannel features, allowing users to create a single conversational interface that then becomes 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. Voice content must be free-flowing and organic, contextless and concise in order to preserve what makes human conversation so compelling in the first place. Everything written content is not.

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. We’re most concerned with the audiobook content being delivered as a requirement rather than an option.

For many of us, our first foray into informational voice interfaces will be to deliver content to users. One issue is that any content we already have isn’t in any way suitable for this new environment. So how do we make the content trapped on our websites more conversational? And how do we create fresh copy that works with voice movements?

Lately, we’ve begun slicing and dicing our content in unprecedented ways. Websites are, in many ways, massive vaults of what I call macrocontent: lengthy prose that can last for miles in a browser window while extending 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:

An example of microcontent can be a day’s weather forecast [sic], the arrival and departure times for an airplane flight, an abstract from a lengthy publication, or a single instant message. __ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

I would update Dash’s definition of microcontent to include all instances of bite-sized content that transcends 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. The best way to learn how your content can be stretched to the limits of its potential is through microcontent, which will inform both established and new delivery channels.

As microcontent, voice content is unique because it’s an example of how content is experienced in time rather than in space. We can instantly look at a digital sign for an instant and be informed when the next train is coming, but voice interfaces keep our attention captive for so long that we can’t quickly evade or skip, a feature that 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.

Our voice content’s legibility and discoverability in general both depend on how it manifests in terms of perceived space and time.