Category: Blog

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.

Computers have issues because conversation is more important than written speech, between spoken and written. To have productive conversations with us, machines may struggle with the messiness of mortal speech: the disfluencies and pauses, the gestures and body language, and the variations in word choice and spoken dialect that is stymie even the most carefully crafted human-computer interaction. Speaking English also has the advantage of face-to-face contact, which enables us to view visual social cues in the human-to-human scenario.

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 speech is not a pleasure in this regard. There are also linguistic cues and outspoken behaviors that mimic conversation in complex ways: how something is said, never what. These are also visual cues that ornament conversations with emphasis and psychological context. Whether rapid-fire, low-pitched, or high-decibel, whether satirical, awkward, or groaning, our spoken speech conveys much more than the written word had ever muster. As designers and content managers, we face exciting difficulties when it comes to tone interfaces, the machines we use to communicate over the phone.

Voice-to-voice relationships

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 require something to be done, such as a deal ).
• we want to know something ( information of some sort ), or
• We are social creatures and seek out a conversation partner ( for the purpose of chat ).

These three categories, which I refer to as transactional, technical, and prosocial, also apply to basically every voice interaction: a solitary conversation that starts with the voice interface’s initial greeting and ends with the user leaving the interface. Notice here that a discussion in our individual sense—a talk between people that leads to some result and lasts an arbitrary length of time—could encompass many interpersonal, technical, and interpersonal voice interactions in succession. In other words, a voice interaction is a conversation, but it may not always be one voice interaction.

Most voice interfaces are more gimmicky than captivating in purely prosocial conversations because machines are unable to yet be truly interested in our progress and engage in the kind of glad-handing behavior that people crave. There’s also ongoing debate as to whether users actually prefer the sort of organic human conversation that begins with a prosocial voice interaction and shifts seamlessly into other types. In Voice User Interface Design, Michael Cohen, James Giangola, and Jennifer Balogh advise sticking to user expectations by imitating how they interact with other voice interfaces rather than trying too hard to be human, which could lead to alienation ( ).

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. The conversation quickly shifts from an initial smattering of neighborly small talk to the actual task at hand, which is ordering a pizza ( generously topped with pineapple, as it should be ).

Alison: Hey, how’s it going?

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

Alison, can I get a pineapple-onion pizza in Hawaii?

Burhan: Yes, but what size?

Alison: Large.

Burhan: Anything else?

Alison: No thanks, that’s it.

Burhan: Something to drink?

Alison, I’ll have a bottle of Coke.

Burhan, you know what. That’ll be$ 13.55 and about fifteen minutes.

A service rendered or a product delivered is the desired outcome of the transaction, and each progressive disclosure in this transactional conversation reveals more and more of it. Conversations that are transactional have certain characteristics: they are direct, concise, and cost-effective. They quickly dispense with pleasantries.

Informational voice interactions

While some conversations are primarily about obtaining information, some are. Though Alison might visit Crust Deluxe with the sole purpose of placing an order, she might not actually want to walk out with a pizza at all. She might be interested in trying halal or kosher dishes, gluten-free options, or something else entirely. We’re after much more than just a prosocial mini-conversation at the beginning, even though we do it once more to establish politeness.

Alison: Hey, how’s it going?

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

Alison: Can I ask a few questions?

Burhan: Of course! Continue straight ahead.

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

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 pizzas that are gluten-free?

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

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

Burhan: Anytime, come back soon!

This is a very different dialogue. Here, the goal is to obtain a particular set of facts. Informational conversations are research expeditions to gather data, news, or facts in search of the truth. Voice interactions that are informational might be more long-winded than transactional conversations by necessity. In order for the customer to understand the key takeaways, responses are typically longer, more in-depth, and carefully communicated.

Voice Interfaces

At their core, voice interfaces employ speech to support users in reaching their goals. However, just 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

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

IVR systems made it easier for businesses to cut down on call centers, but they soon gained notoriety for their clunkiness. When you call an airline or hotel company, which is a common practice in the corporate world, these systems were primarily intended as metaphorical switchboards to direct customers to a real phone agent (” Say Reservations to book a flight or check an itinerary” ), which are more likely to happen when you call one. 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 are the norm

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

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

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

There’s a big deal with screen readers: they’re difficult to use and relentlessly verbose, despite being incredibly instructive for voice interface designers. Screen readers may not be able to read websites ‘ visual structures, which can occasionally lead to awkward pronouncements that list every manipulable HTML element and make an announcement about every formatting change. For many screen reader users, working with web-based interfaces exacts a cognitive toll.

Accessibility advocate and voice engineer Chris Maury examines why the screen reader experience is not appropriate for users who rely on voice in Wired:

I hated the way Screen Readers operated from the beginning. Why are they designed the way they are? It makes no sense to present information visually and then only to have that information translated into audio. All the effort and thought that goes into creating the ideal user experience for an app is wasted, or worse, having a negative effect on blind users ‘ experience. ( )

Well-designed voice interfaces can often beat lengthy screen reader monologues in terms of speeding up users ‘ movements. 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-overseers are

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

Before the earliest IVR systems found success in the enterprise, Apple published a demonstration video in 1987 depicting the Knowledge Navigator, a voice assistant that could transcribe spoken words and recognize human speech to a great degree of accuracy. Then, in 2001, Tim Berners-Lee and others created their vision for a” semantic web agent” that would carry out routine tasks like” checking calendars, making appointments, and finding locations” ( hinter paywall ). Apple’s Siri only became a reality until 2011 when it finally made voice assistants a reality for consumers.

Thanks to the plethora of voice assistants available today, there is considerable variation in how programmable and customizable certain voice assistants are over others ( Fig 1.1 ). At one extreme, everything but vendor-provided features are locked down. For instance, when Apple’s Siri and Microsoft’s Cortana were released, they couldn’t extend their existing capabilities. There are no other means of developers communicating with Siri at a low level, aside from predefined categories of tasks like messaging, hailing rideshares, making restaurant reservations, and other things, which are still possible today.

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 constrained by the limitations of Siri and Cortana are increasingly using programmable voice assistants that are extensibable and customizable. Google Home enables the programming of arbitrary Google Assistant skills, while Amazon offers the Alexa Skills Kit, a developer framework for creating custom voice interfaces for Amazon Alexa. Today, users can choose from among thousands of custom-built skills within both the Amazon Alexa and Google Assistant 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, such as Google’s Dialogflow, have omnichannel capabilities that allow users to create a single conversational interface that then becomes a voice interface, textual chatbot, and IVR system upon deployment. In this design-focused book, I don’t recommend any particular implementation strategies, but in Chapter 4 we’ll discuss some of the possible effects that these variables might have on how you construct your design artifacts.

Voice Content

Simply put, voice content is voice-transmitted content. 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 content in this book being delivered auditorically, not as an option but as a necessity.

Our first foray into informational voice interfaces will likely be to deliver content to users, for many of us. There’s only one problem: any content we already have isn’t in any way ready for this new habitat. So how can we make the content on our websites more conversational? And how do we create fresh copy that works with voice-activated text?

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

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

I 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. Informing delivery channels both established and novel, Microcontent provides the best opportunity to find out how your content can be stretched to the limits of its potential.

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

We need to make sure that our microcontent truly performs well as voice content because it is essentially composed of isolated blobs without any connection to the channels in which they will eventually end up. This means focusing on the two most crucial characteristics of robust voice content: voice content legibility and voice content discoverability.

Fundamentally, how voice content manifests in perceived time and space both affect the legibility and discoverability of our voice content.

But how can a content management system ( CMS ) be set up to reach your current and future audience? I learned the hard way that creating a content model—a concept of information types, attributes, and relationships that let people and systems understand content—with my more comfortable design-system wondering would collapse my patient’s holistic information strategy. By developing content versions that are conceptual and even join related content, you can avoid that result.

I just had the opportunity to lead a Fortune 500 company’s CMS application. The customer was excited by the benefits of an holistic information plan, including material modify, multichannel marketing, and robot delivery—designing content to be comprehensible to bots, Google knowledge panels, snippets, and voice user interfaces.

For our information to be understood by many systems, the unit needed conceptual types, which are names given based on their meaning rather than their presentation. This is crucial for an multichannel content strategy. Our goal was to allow artists to create original content that could be used wherever they felt was most useful. However, as the project progressed, I realized that the entire group had to be aware of a new design in order to support material reuse on the level that my customer needed.

Despite our best motives, we kept drawing from what we were more common with: design techniques. Unlike web-focused material strategies, an holistic information strategy doesn’t rely on WYSIWYG equipment for design and structure. Our inclination to approach the material model using our well-known design-system thinking consistently stifled our attention from one of the main objectives of a willing model: delivering content to audiences across multiple marketing channels.

Two fundamental tenets are necessary for a successful information type

We needed to explain to our designers, developers, and stakeholders that we were doing something completely different from their previous internet projects, where everyone assumed that content would fit into layouts as physical building blocks. Because it made the layouts feel more recognizable, the previous approach was more intuitive, at first, at least initially. We discovered two guiding principles that helped the group grasp how a willing model and the design processes we were familiar with were:

1. Instead of design, semantics must be used by content versions.
2. And glad models may connect elements that belong together.

Conceptual articles models

A conceptual content type uses form and attribute names that reflect the content’s intended purpose and not how it will be displayed. For instance, in a nonsemantic design, groups may produce varieties like teasers, press blocks, and cards. These types may make it simple to present information, but they do not aid in understanding the meaning of the information, which would have opened the door to the content presented in each marketing channel. To allow each distribution channel to comprehend the information and use it as it sees fit, a conceptual content type uses kind names like product, service, and testimonial.

A great place to start when creating a semantic content model is by reviewing the types and properties that Schema has defined. org, a community-driven resource for type definitions that are intelligible to platforms like Google search.

A semantic content model has several benefits:

A semantic content model decouples content from its presentation so that teams can change the website’s design without having to refactor its content, even if your team doesn’t care about omnichannel content. In this way, content can withstand disruptive website redesigns.
• A semantic content model also gives you an advantage in the market. by including structured, schema-based data. org’s types and properties, a website can provide hints to help Google understand the content, display it in search snippets or knowledge panels, and use it to answer voice-interface user questions. Without ever visiting your website, potential visitors could easily find your content.
• Beyond those practical advantages, you’ll also require an omnichannel content delivery model. Delivery channels must be able to understand the same content in order to use it across multiple marketing channels. For instance, if your content model provided a list of questions and answers, it could be used as a voice interface or by a bot to answer frequently asked questions ( FAQ ) pages.

For example, using a semantic content model for articles, events, people, and locations lets A List Apart provide cleanly structured data for search engines so that users can read the content on the website, in Google knowledge panels, and even with hypothetical voice interfaces in the future.

Content models that connect

Instead of slicing up related content across disparate content components, I’ve come to the realization that the best models are those that are semantic and also connect related content components ( such as a FAQ item’s question and answer pair ). Content that needs to be reused by multiple delivery channels can be connected to each other without having to assemble those pieces again in a good content model.

Consider creating an essay or article. An article’s meaning and usefulness depends upon its parts being kept together. Without the context of the entire article, would one of the headings or paragraphs have any meaning on their own? Our well-known design-system thinking on our project frequently led us to want to develop content models that would divide content into distinct chunks to fit the web-centric layout. Similar effects could have been felt to an article that had its headline removed. Content that belonged together became challenging to manage and nearly impossible for multiple delivery channels to understand because we were cutting content into separate pieces based on layout.

To illustrate, let’s look at how connecting related content applies in a real-world scenario. The client’s design team created a challenging layout for a software product page that included numerous tabs and sections. Our instincts were to follow the content model’s. Shouldn’t we make adding any number of tabs in the future as simple and flexible as possible?

Because our design-system instincts were so well-known, it appeared that we needed a “tab section” content type so that multiple tab sections could be added to a page. Each tab section would display various kinds of information. One tab might provide the software’s overview or its specifications. Another tab might provide a list of resources.

Our tendency to divide the content model into “tab section” pieces would have resulted in an unnecessary complex model and laborious editing procedures, as well as creating content that couldn’t possibly be understood by additional delivery channels. How would another system have resorted to counting tab sections and content blocks, for instance, if it had been able to identify a product’s “tab section” when referring to its specifications or resource list? This would have prevented the tabs from ever being rearranged, and it would have required adding logic to each other delivery channel to interpret the layout of the design system. Additionally, it would have been difficult to migrate to a new content model in response to the new page redesign if the customer had decided against displaying this content in a tab layout.

We had a breakthrough when we discovered that our customer had a specific purpose in mind for each tab: it would reveal specific information such as the software product’s overview, specifications, related resources, and pricing. When the design process began, our desire to concentrate on what was visually and historically significant had obscured the purpose of the designs. With a little digging, it didn’t take long to realize that the concept of tabs wasn’t relevant to the content model. What was important was the meaning of the content they were planning to display in the tabs.

In fact, the customer could have chosen to switch to another format, using tabs, elsewhere. In response to this realization, we decided to create content types for the software product based on the meaningful qualities the client wanted to display on the web. There were obvious semantic attributes like name and description as well as rich attributes like screenshots, software requirements, and feature lists. The software’s product information stayed together because it wasn’t sliced across separate components like “tab sections” that were derived from the content’s presentation. Any delivery channel—including future ones—could understand and present this content.

Conclusion

In this omnichannel marketing project, we discovered that the best way to maintain the content model’s semantic consistency was by ensuring that it was semantic ( with type and attribute names that reflected the content’s meaning ) and that it maintained content that belonged together ( as opposed to fragmenting it ). These two ideas made it easier for us to shape the content model based on the design. Remember: If you’re developing a content model to support an omnichannel content strategy, or even if you just want to make sure Google and other interfaces understand your content, remember:

• A design system isn’t a content model. You should maintain the semantic value and contextual structure of the content strategy throughout the entire implementation process because team members might be tempted to combine them and to make your content model resemble your design system. Without the use of a magic decoder ring, every delivery channel will be able to consume the content.
• You can still use Schema if your team is having trouble making this transition. org–based structured data in your website. The advantage of search engine optimization is a compelling argument on its own, even if additional delivery channels are not in the works.
• Remind the team that separating the content model from the design will allow them to update the designs more quickly because they won’t be hindered by the cost of content migrations. They’ll be able to create new designs without compromising the compatibility between the content and the design, and they’ll be prepared for the upcoming big thing.

You’ll help your team understand these principles by firmly defending them in their efforts to give content the attention it deserves as both your most valuable resource and your most effective way to engage with your audience.

This book will provide you with that plan of action. It covers how to incorporate safety concepts into your design work to create healthy tech, how to persuade your stakeholders that this work is required, and how to respond to criticism that what we really need is more variety. ( Spoiler: we do, but diversity alone is not the antidote to fixing unethical, unsafe tech. )

The diverse safety procedure

When you are designing for health, your goals are to:

• detect the abuse potential of your product.
• style ways to prevent the maltreatment, and
• offer assistance for harmed people to regain control and power.

The Process for Inclusive Safety is a tool to help you reach those goals ( Fig 5.1 ). It’s a method I developed in 2018 to better understand the different methods I used to create products that were designed with safety in mind. Whether you are creating an entirely new product or adding to an existing element, the Process can help you produce your product secure and diverse. Five main public areas of action are included in the Process:

• Conducting study
• Developing tropes
• Pondering issues
• Creating answers
• Testing for health

It is intended to be flexible, so teams might not want to utilize every action in all circumstances. Use the parts that are related to your special function and environment, this is meant to be something you can put into your existing style process.

And once you use it, if you have suggestions for improving it or just want to give an overview of how it helped your staff, please get in touch with me. It’s a dwelling report that I hope will continue to be a helpful and practical tool that technicians can use in their day-to-day job.

If you’re developing a product especially for a defenseless group or victims of some kind of stress, such as an app for victims of domestic violence, sexual abuse, or drug habit, make sure to read Chapter 7, which specifically addresses the issue and should be handled a little bit different. The guidelines below are for evaluating safety when designing a more basic product that will have a large customer base ( which, we now know from data, will include specific groups that should be protected from harm ). Chapter 7 concentrates on goods made especially for those who have been traumatized and are vulnerable.

Step 1: Do studies

Design research should involve a thorough evaluation of how your technology might be used for abuse as well as particular insight into the experiences of those who have witnessed and perpetrated that kind of abuse. At this stage, you and your group does investigate issues of emotional damage and abuse, and examine any other safety, security, or inclusivity issues that might be a concern for your product or service, like data security, prejudiced algorithms, and harassment.

broad-based research

Your project should begin with broad, general research into similar products and issues around safety and ethical concerns that have already been reported. A team building a smart home device would be wise to comprehend the many ways that already-existing smart home devices have been misused as abuse tools. If your product will involve AI, seek to understand the potentials for racism and other issues that have been reported in existing AI products. Nearly all different types of technology have some sort of potential or actual harm that has been covered in the media or written about by academics. Google Scholar is a useful tool for finding these studies.

Survivors as a specific field of study

When possible and appropriate, include direct research ( surveys and interviews ) with people who are experts in the forms of harm you have uncovered. In order to gain a better understanding of the subject and be better positioned to avoid traumatizing survivors, you should first interview those who work in the area of your research. If you’ve uncovered possible domestic violence issues, for example, the experts you’ll want to speak with are survivors themselves, as well as workers at domestic violence hotlines, shelters, other related nonprofits, and lawyers.

It is crucial to pay people for their knowledge and lived experiences, especially when interviewing survivors of any kind of trauma. Don’t ask survivors to share their trauma for free, as this is exploitative. You should always make the offer in the beginning, even though some survivors might not want to be paid. An alternative to payment is to donate to an organization working against the type of violence that the interviewee experienced. In Chapter 6, we’ll discuss how to approach interviews with survivors.

Specific research: Abusers

Teams aiming to design for safety are unlikely to be able to interview self-declared abductors or those who have broken laws in areas like hacking. Don’t make this a goal, rather, try to get at this angle in your general research. Describe the ways that abusers or bad actors use technology to harm others, how they use it to silence others, and how they justify or explain the abuse.

Step 2: Create archetypes

Use your research’s findings to create abuser and survivor archetypes once you’ve finished conducting your research. Archetypes are not personas, as they’re not based on real people that you interviewed and surveyed. Instead, they are based on your investigation into potential safety problems, much like when we design for accessibility: we don’t need to have identified any blind or deaf people in our interview pool to come up with a design that is representative of them. Instead, we base those designs on existing research into what this group needs. While archetypes are broad and can be more generalized, real users typically represent real users and contain many details.

The abuser archetype is someone who will look at the product as a tool to perform harm ( Fig 5.2 ). They may be attempting to overthrow, monitor, abuse, or torment someone they know personally by using surveillance or anonymous harassment.

The survivor archetype refers to a person who is being abused with the product. There are various situations to consider in terms of the archetype’s understanding of the abuse and how to put an end to it: Do they need proof of abuse they already suspect is happening, or are they unaware they’ve been targeted in the first place and need to be alerted ( Fig 5.3 )?

To capture a range of experiences, you might want to create several survivor archetypes. They may know that the abuse is happening but not be able to stop it, like when an abuser locks them out of IoT devices, or they know it’s happening but don’t know how, such as when a stalker keeps figuring out their location ( Fig 5.4). Include as many of these scenarios in your survivor archetype as you need. You’ll use these later on when you design solutions to help your survivor archetypes achieve their goals of preventing and ending abuse.

It may be useful for you to create persona-like artifacts for your archetypes, such as the three examples shown. Focus on their objectives rather than the demographic details we frequently see in personas. The goals of the abuser will be to carry out the specific abuse you’ve identified, while the goals of the survivor will be to prevent abuse, understand that abuse is happening, make ongoing abuse stop, or regain control over the technology that’s being used for abuse. Later, you’ll think about how to help the survivor’s goals and the abuser’s goals.

And while the “abuser/survivor” model fits most cases, it doesn’t fit all, so modify it as you need to. For instance, if you found a security flaw, such as the ability for someone to talk to children through a home camera system, the malicious hacker would receive the abuser archetype, and the child’s parents would receive the survivor archetype.

Step 3: Brainstorm problems

After creating archetypes, think about novel safety and abuse cases. ” Novel” means things not found in your research, you’re trying to identify completely new safety issues that are unique to your product or service. This step is intended to exhaust every effort put forth to identify potential harms your product might cause. You aren’t worrying about how to prevent the harm yet—that comes in the next step.

What other uses could your product be used for besides what you’ve already identified in your research? I recommend setting aside at least a few hours with your team for this process.

Try conducting a Black Mirror brainstorming session if you want to start somewhere. This exercise is based on the show Black Mirror, which features stories about the dark possibilities of technology. Try to figure out the most outrageous, horrible, and out-of-control ways your product could harm you in a show episode. When I’ve led Black Mirror brainstorms, participants usually end up having a good deal of fun ( which I think is great—it’s okay to have fun when designing for safety! ). I suggest time-boxing a Black Mirror brainstorm for the first half an hour, then dialing back, and using the remaining time to consider more plausible forms of harm.

After you’ve identified as many opportunities for abuse as possible, you may still not feel confident that you’ve uncovered every potential form of harm. When you’re doing this kind of work, a healthy amount of anxiety is normal. It’s common for teams designing for safety to worry,” Have we really identified every possible harm? What if something is missing, then? If you’ve spent at least four hours coming up with ways your product could be used for harm and have run out of ideas, go to the next step.

It’s impossible to say 100 % assurance that you’ve done everything right, but instead of aiming for 100 % assurance, acknowledge that you’ve taken this step and have done everything you can, and pledge to keep putting safety first in the future. Once your product is released, your users may identify new issues that you missed, aim to receive that feedback graciously and course-correct quickly.

4. Create solutions

At this point, you should have a list of ways your product can be used for harm as well as survivor and abuser archetypes describing opposing user goals. Next, it’s time to figure out how to design in accordance with the objectives of the abuser and the survivors ‘ objectives. This step is a good one to insert alongside existing parts of your design process where you’re proposing solutions for the various problems your research uncovered.

Questions to ask yourself include: What are some ways to protect your archetypes and to support your self-identity?

• Can you design your product in such a way that the identified harm cannot happen in the first place? If not, what barriers can you place to stop the harm from occurring?
• How can you make the victim aware that abuse is happening through your product?
• How can you explain to the victim what they must do to stop the problem?
• Can you identify any types of user activity that would indicate some form of harm or abuse? Could your product provide support for the user?

In some products, it’s possible to proactively recognize that harm is happening. For instance, a pregnancy app might be modified to allow users to report being assault victims, which could result in an offer to receive resources from local and national organizations. This sort of proactiveness is not always possible, but it’s worth taking a half hour to discuss if any type of user activity would indicate some form of harm or abuse, and how your product could assist the user in receiving help in a safe manner.

Nevertheless, be careful: you don’t want to do anything that could harm a user if their devices are being watched. If you do offer some kind of proactive help, always make it voluntary, and think through other safety issues, such as the need to keep the user in-app in case an abuser is checking their search history. In the next chapter, we’ll examine a good illustration of this.

Step 5: Test for safety

The final step is to evaluate the prototypes against the perspectives of your archetypes, who wants to harm the product or the victim of the harm who needs to regain control of the technology. Just like any other kind of product testing, at this point you’ll aim to rigorously test out your safety solutions so that you can identify gaps and correct them, validate that your designs will help keep your users safe, and feel more confident releasing your product into the world.

Safety testing should be performed in addition to usability testing. If you’re at a company that doesn’t do usability testing, you might be able to use safety testing to cleverly perform both, a user who goes through your design attempting to weaponize the product against someone else can also be encouraged to point out interactions or other elements of the design that don’t make sense to them.

If your final prototype or the finished product has already been released, you’ll want to conduct safety testing on both. There’s nothing wrong with testing an existing product that wasn’t designed with safety goals in mind from the onset —”retrofitting” it for safety is a good thing to do.

Keep in mind that testing for safety involves both an abuser and a survivor’s perspective, even though it might not make sense for you to do both. Alternatively, if you made multiple survivor archetypes to capture multiple scenarios, you’ll want to test from the perspective of each one.

You as the designer are probably too closely acquainted with the product and its design at this point, just like other usability testing techniques, and you know the product too well. Instead of doing it yourself, set up testing as you would with other usability testing: find someone who is not familiar with the product and its design, set the scene, give them a task, encourage them to think out loud, and observe how they attempt to complete it.

Abuse testing

The goal of this testing is to understand how easy it is for someone to weaponize your product for harm. You want to make it impossible, or at least difficult for them to accomplish their goal, unlike with usability testing. Reference the goals in the abuser archetype you created earlier, and use your product in an attempt to achieve them.

For instance, we can imagine that the abuser archetype would have the goal of discovering where his ex-girlfriend currently lives in a fitness app with GPS-enabled location features. With this goal in mind, you’d try everything possible to figure out the location of another user who has their privacy settings enabled. You might try to follow her running routes, view any information she has on her profile, view any information she has made private, and check out the profiles of any other users who are connected to her account, such as her followers.

If by the end of this you’ve managed to uncover some of her location data, despite her having set her profile to private, you know now that your product enables stalking. Reverting to step 4 and figuring out how to stop this from occurring is your next step. You may need to repeat the process of designing solutions and testing them more than once.

Testing for Survivors

Testing for Survivors involves identifying how to give information and power to the survivor. It might not always make sense based on the product or context. Thwarting the attempt of an abuser archetype to stalk someone also satisfies the goal of the survivor archetype to not be stalked, so separate testing wouldn’t be needed from the survivor’s perspective.

However, there are instances where it makes sense. For example, for a smart thermostat, a survivor archetype’s goals would be to understand who or what is making the temperature change when they aren’t doing it themselves. If you couldn’t find the information in step 4, you would need to do it again by looking for the thermostat’s history log and looking for usernames, actions, and times.

Another goal might be regaining control of the thermostat once the survivor realizes the abuser is remotely changing its settings. Are there any instructions that explain how to remove a user and change the password, and are they simple to find? For your test, you would need to try to figure out how to do this. This might again reveal that more work is needed to make it clear to the user how they can regain control of the device or account.

Stress testing

To make your product more inclusive and compassionate, consider adding stress testing. Eric Meyer and Sara Wachter-Boettcher’s Design for Real Life inspired this idea. The authors pointed out that personas typically center people who are having a good day—but real users are often anxious, stressed out, having a bad day, or even experiencing tragedy. These are known as” stress cases,” and analyzing your products to see if they respond to users in stressful circumstances can reveal areas where your design lacks compassion. Design for Real Life has more details about what it looks like to incorporate stress cases into your design as well as many other great tactics for compassionate design.

Several wealthy runners had come to the conclusion that it was impossible to run a mile in less than four hours in the 1950s. Riders had been attempting it since the later 19th century and were beginning to draw the conclusion that the human body just wasn’t built for the job.

But Roger Bannister surprised all on May 6, 1956. It was a cold, damp morning in Oxford, England—conditions no one expected to give themselves to record-setting—and but Bannister did really that, running a mile in 3: 59.4 and becoming the first people in the history books to run a mile in under four hours.

The world then knew that the four-minute hour was possible because of this change in the standard. Bannister’s history lasted just forty-six days, when it was snatched aside by American sprinter John Landy. Therefore, in the same race, three athletes managed to cross the four-minute challenge together. Since therefore, over 1, 400 walkers have actually run a mile in under four days, the current document is 3: 43.13, held by Moroccan performer Hicham El Guerrouj.

We accomplish a lot more when we think something is possible, and we only think it can be done when we see someone else doing it after all. As for man running speed, we also think there are the strictest requirements for how a website should do.

Establishing requirements for a green website

The key indicators of climate performance in most big companies are very well established, such as power per square metre for homes and miles per gallon for cars. The tools and methods for calculating those measures are standardized as well, which keeps everyone on the same site when doing economic evaluations. However, we are not required to follow any specific environmental standards in the world of websites and apps, and we have only recently developed the tools and methods to do so.

The main objective in green web layout is to reduce carbon emissions. However, it’s nearly impossible to accurately assess the CO₂ output of a website product. We can’t measure the pollutants coming out of the exhaust valves on our devices. Our sites produce far-away, invisible, and unremarkable pollutants when they leave fuel and gas-burning power plants. We have no way to track the particles from a website or app up to the power station where the light is being generated and really know the exact amount of house oil produced. So what do we accomplish then?

If we can‘t measure the actual carbon emissions, then we need to get what we can estimate. The following are the main elements that could be used as carbon pollution gauges:

1. Transfer of data
2. Electricity’s coal power

Let’s take a look at how we can use these indicators to calculate the energy use, and in turn the carbon footprint, of the sites and web applications we create.

Transfer of data

Most researchers use kilowatt-hours per gigabyte (k Wh/GB ) as a metric of energy efficiency when measuring the amount of data transferred over the internet when a website or application is used. This serves as a reliable indicator of how much power is being consumed and how much carbon is being released. As a rule of thumb, the more files transferred, the more electricity used in the data center, telecoms systems, and end users products.

The most accurate way to calculate data transfer for a second visit for web pages is to measure the site weight, which is the first time a user visits the page in kilobytes. It’s very easy to measure using the engineer equipment in any modern internet browser. Frequently, the statistics for the total data transfer of any web application are included in your web hosting account ( Fig. 2.1 ).

The great thing about website weight as a parameter is that it allows us to compare the effectiveness of web pages on a level playing field without confusing the issue with frequently changing traffic volumes.

A large scope is required to reduce page weight. By early 2020, the median page weight was 1.97 MB for setups the HTTP Archive classifies as “desktop” and 1.77 MB for “mobile”, with desktop increasing 36 percent since January 2016 and mobile page weights nearly doubling in the same period ( Fig 2.2 ). Image files account for roughly half of this data transfer, making them the single biggest contributor to carbon emissions on the typical website.

History clearly shows us that our web pages can be smaller, if only we set our minds to it. While the majority of technologies, including the underlying technology of the web like data centers and transmission networks, become more and more energy efficient, websites themselves become less effective as time goes on.

You might be aware of the project team’s focus on creating faster user experiences using the concept of performance budgeting. For example, we might specify that the website must load in a maximum of one second on a broadband connection and three seconds on a 3G connection. Performance budgets are upper limits rather than vague suggestions, much like speed limits while driving, so the goal should always be to come in within budget.

Designing for fast performance does often lead to reduced data transfer and emissions, but it isn’t always the case. Page weight and transfer size are more objective and reliable benchmarks for sustainable web design, whereas web performance is frequently more about the subjective perception of load times than it is about the underlying system’s actual efficiency.

We can set a page weight budget in reference to a benchmark of industry averages, using data from sources like HTTP Archive. We can also use competitor page weight to compare the new website to the old one. For example, we might set a maximum page weight budget as equal to our most efficient competitor, or we could set the benchmark lower to guarantee we are best in class.

We could start looking at the transferability of our web pages for repeat visitors if we want to take it one step further. Although page weight for the first time someone visits is the easiest thing to measure, and easy to compare on a like-for-like basis, we can learn even more if we start looking at transfer size in other scenarios too. For instance, repeat users who load the same page frequently will likely have a high percentage of the files cached in their browser, which means they won’t need to move all of the files back on subsequent visits. Likewise, a visitor who navigates to new pages on the same website will likely not need to load the full page each time, as some global assets from areas like the header and footer may already be cached in their browser. Moving beyond the first visit and measuring page weight budgets for scenarios beyond this level of detail can help us learn even more about how to optimize efficiency for users who regularly visit our pages.

Page weight budgets are easy to track throughout a design and development process. Although they don’t directly disclose carbon emissions and energy consumption data, they do provide a clear indicator of efficiency in comparison to other websites. And as transfer size is an effective analog for energy consumption, we can actually use it to estimate energy consumption too.

In summary, less data transfer leads to more energy efficiency, which is a crucial component of lowering web product carbon emissions. The more efficient our products, the less electricity they use, and the less fossil fuels need to be burned to produce the electricity to power them. However, as we’ll see next, it’s important to take into account the source of that electricity because all web products require some.

Electricity’s coal power

Regardless of energy efficiency, the level of pollution caused by digital products depends on the carbon intensity of the energy being used to power them. The term” carbon intensity” (gCO₂/k Wh ) is used to describe how much carbon dioxide is produced for each kilowatt-hour of electricity ). This varies widely, with renewable energy sources and nuclear having an extremely low carbon intensity of less than 10 gCO₂/k Wh ( even when factoring in their construction ), whereas fossil fuels have very high carbon intensity of approximately ₂00–400 gCO₂/k Wh.

The majority of electricity is produced by national or state grids, which combine energy from a variety of sources with different carbon intensity levels. The distributed nature of the internet means that a single user of a website or app might be using energy from multiple different grids simultaneously, a website user in Paris uses electricity from the French national grid to power their home internet and devices, but the website’s data center could be in Dallas, USA, pulling electricity from the Texas grid, while the telecoms networks use energy from everywhere between Dallas and Paris.

Although we don’t have complete control over the energy supply of web services, we do have some control over where our projects are hosted. With a data center using a significant proportion of the energy of any website, locating the data center in an area with low carbon energy will tangibly reduce its carbon emissions. Danish startup Tomorrow reports and maps the user-provided data, and a look at their map demonstrates how, for instance, choosing a data center in France will have significantly lower carbon emissions than choosing a data center in the Netherlands ( Fig. 2.3 ).

However, we don’t want to move our servers too far away from our users because it requires energy to transmit data through the telecom’s networks, and the more energy is used. Just like food miles, we can think of the distance from the data center to the website’s core user base as “megabyte miles” —and we want it to be as small as possible.

We can use website analytics to determine the country, state, or even city where our core user group is located and measure the distance from that location to the data center used by our hosting company by using the distance itself as a benchmark. This will be a somewhat fuzzy metric as we don’t know the precise center of mass of our users or the exact location of a data center, but we can at least get a rough idea.

For instance, if a website is hosted in London but the main audience is on the United States ‘ West Coast, we could look up the travel distance between London and San Francisco, which is 5,300 miles. That’s a long way! We can see how significantly lessening the distance and energy needed to transmit the data would be if it was hosted somewhere in North America, ideally on the West Coast. In addition, locating our servers closer to our visitors helps reduce latency and delivers better user experience, so it’s a win-win.

Reverting it to carbon emissions

If we combine carbon intensity with a calculation for energy consumption, we can calculate the carbon emissions of our websites and apps. The method my team developed converts the data transferred over wire when loading a website into a CO₂ figure ( Fig. ₂.4), calculating the associated electricity, and then converting that data into a figure ( Fig. ₂.4). It also factors in whether or not the web hosting is powered by renewable energy.

The Energy and Emissions Worksheet that comes with this book teaches you how to improve it and tailor the data more appropriately to your project’s unique features.

With the ability to calculate carbon emissions for our projects, we could actually expand our page weight budget and establish carbon budgets as well. CO₂ is not a metric commonly used in web projects, we’re more familiar with kilobytes and megabytes, and can fairly easily look at design options and files to assess how big they are. Although translating that into carbon adds a layer of abstraction that isn’t as intuitive, carbon budgets do focus our minds on the main thing we’re trying to reduce, and this is in line with the main goal of sustainable web design: reducing carbon emissions.

Browser Energy

Transfer of data might be the simplest and most complete analog for energy consumption in our digital projects, but by giving us one number to represent the energy used in the data center, the telecoms networks, and the end user’s devices, it can’t offer us insights into the efficiency in any specific part of the system.

One part of the system we can look at in more detail is the energy used by end users ‘ devices. The computational load is increasingly shifting from the data center to users ‘ devices, whether they are phones, tablets, laptops, desktops, or even smart TVs, as front-end web technologies advance. Modern web browsers allow us to implement more complex styling and animation on the fly using CSS and JavaScript. Additionally, JavaScript libraries like Angular and React make it possible to create applications where the” thinking” process is performed partially or completely in the browser.

All of these advances are exciting and open up new possibilities for what the web can do to serve society and create positive experiences. However, more computation in a web browser requires more energy to be used by the user’s devices. This has implications not just environmentally, but also for user experience and inclusivity. Applications that put a lot of processing power on a user’s device unintentionally exclude those who have older, slower devices and make the batteries on phones and laptops drain more quickly. Furthermore, if we build web applications that require the user to have up-to-date, powerful devices, people throw away old devices much more frequently. This not only hurts the environment, but it also places a disproportionate financial burden on society’s poorest.

In part because the tools are limited, and partly because there are so many different models of devices, it’s difficult to measure website energy consumption on end users ‘ devices. The Energy Impact monitor inside the developer console of the Safari browser is one of the tools we currently have ( Fig. 2.5 ).

You know what happens when your computer’s cooling fans start spinning so frantically that you suspect it might take off when you load a website? That’s essentially what this tool is measuring.

It uses these figures to create an energy impact rating and shows the percentage of CPU used and how long the CPU used when loading the web page last. It doesn’t give us precise data for the amount of electricity used in kilowatts, but the information it does provide can be used to benchmark how efficiently your websites use energy and set targets for improvement.

Do you find yourself designing screens with only a vague idea of how the things on the screen relate to the things elsewhere in the system? Do you leave stakeholder meetings with unclear directives that often seem to contradict previous conversations? You know a better understanding of user needs would help the team get clear on what you are actually trying to accomplish, but time and budget for research is tight. When it comes to asking for more direct contact with your users, you might feel like poor Oliver Twist, timidly asking, “Please, sir, I want some more.” 

Here’s the trick. You need to get stakeholders themselves to identify high-risk assumptions and hidden complexity, so that they become just as motivated as you to get answers from users. Basically, you need to make them think it’s their idea. 

In this article, I’ll show you how to collaboratively expose misalignment and gaps in the team’s shared understanding by bringing the team together around two simple questions:

1. What are the objects?
2. What are the relationships between those objects?

A gauntlet between research and screen design

These two questions align to the first two steps of the ORCA process, which might become your new best friend when it comes to reducing guesswork. Wait, what’s ORCA?! Glad you asked.

ORCA stands for Objects, Relationships, CTAs, and Attributes, and it outlines a process for creating solid object-oriented user experiences. Object-oriented UX is my design philosophy. ORCA is an iterative methodology for synthesizing user research into an elegant structural foundation to support screen and interaction design. OOUX and ORCA have made my work as a UX designer more collaborative, effective, efficient, fun, strategic, and meaningful.

The ORCA process has four iterative rounds and a whopping fifteen steps. In each round we get more clarity on our Os, Rs, Cs, and As.

I sometimes say that ORCA is a “garbage in, garbage out” process. To ensure that the testable prototype produced in the final round actually tests well, the process needs to be fed by good research. But if you don’t have a ton of research, the beginning of the ORCA process serves another purpose: it helps you sell the need for research.

In other words, the ORCA process serves as a gauntlet between research and design. With good research, you can gracefully ride the killer whale from research into design. But without good research, the process effectively spits you back into research and with a cache of specific open questions.

Getting in the same curiosity-boat

What gets us into trouble is not what we don’t know. It’s what we know for sure that just ain’t so.

Mark Twain

The first two steps of the ORCA process—Object Discovery and Relationship Discovery—shine a spotlight on the dark, dusty corners of your team’s misalignments and any inherent complexity that’s been swept under the rug. It begins to expose what this classic comic so beautifully illustrates:

This is one reason why so many UX designers are frustrated in their job and why many projects fail. And this is also why we often can’t sell research: every decision-maker is confident in their own mental picture. 

Once we expose hidden fuzzy patches in each picture and the differences between them all, the case for user research makes itself.

But how we do this is important. However much we might want to, we can’t just tell everyone, “YOU ARE WRONG!” Instead, we need to facilitate and guide our team members to self-identify holes in their picture. When stakeholders take ownership of assumptions and gaps in understanding, BAM! Suddenly, UX research is not such a hard sell, and everyone is aboard the same curiosity-boat.

Say your users are doctors. And you have no idea how doctors use the system you are tasked with redesigning.

You might try to sell research by honestly saying: “We need to understand doctors better! What are their pain points? How do they use the current app?” But here’s the problem with that. Those questions are vague, and the answers to them don’t feel acutely actionable.

Instead, you want your stakeholders themselves to ask super-specific questions. This is more like the kind of conversation you need to facilitate. Let’s listen in:

“Wait a sec, how often do doctors share patients? Does a patient in this system have primary and secondary doctors?”

“Can a patient even have more than one primary doctor?”

“Is it a ‘primary doctor’ or just a ‘primary caregiver’… Can’t that role be a nurse practitioner?”

“No, caregivers are something else… That’s the patient’s family contacts, right?”

“So are caregivers in scope for this redesign?”

“Yeah, because if a caregiver is present at an appointment, the doctor needs to note that. Like, tag the caregiver on the note… Or on the appointment?”

Now we are getting somewhere. Do you see how powerful it can be getting stakeholders to debate these questions themselves? The diabolical goal here is to shake their confidence—gently and diplomatically.

When these kinds of questions bubble up collaboratively and come directly from the mouths of your stakeholders and decision-makers, suddenly, designing screens without knowing the answers to these questions seems incredibly risky, even silly.

If we create software without understanding the real-world information environment of our users, we will likely create software that does not align to the real-world information environment of our users. And this will, hands down, result in a more confusing, more complex, and less intuitive software product.

The two questions

But how do we get to these kinds of meaty questions diplomatically, efficiently, collaboratively, and reliably? 

We can do this by starting with those two big questions that align to the first two steps of the ORCA process:

1. What are the objects?
2. What are the relationships between those objects?

In practice, getting to these answers is easier said than done. I’m going to show you how these two simple questions can provide the outline for an Object Definition Workshop. During this workshop, these “seed” questions will blossom into dozens of specific questions and shine a spotlight on the need for more user research.

Prep work: Noun foraging

In the next section, I’ll show you how to run an Object Definition Workshop with your stakeholders (and entire cross-functional team, hopefully). But first, you need to do some prep work.

Basically, look for nouns that are particular to the business or industry of your project, and do it across at least a few sources. I call this noun foraging.

Here are just a few great noun foraging sources:

• the product’s marketing site
• the product’s competitors’ marketing sites (competitive analysis, anyone?)
• the existing product (look at labels!)
• user interview transcripts
• notes from stakeholder interviews or vision docs from stakeholders

Put your detective hat on, my dear Watson. Get resourceful and leverage what you have. If all you have is a marketing website, some screenshots of the existing legacy system, and access to customer service chat logs, then use those.

As you peruse these sources, watch for the nouns that are used over and over again, and start listing them (preferably on blue sticky notes if you’ll be creating an object map later!).

You’ll want to focus on nouns that might represent objects in your system. If you are having trouble determining if a noun might be object-worthy, remember the acronym SIP and test for:

1. Structure
2. Instances
3. Purpose

Think of a library app, for example. Is “book” an object?

Structure: can you think of a few attributes for this potential object? Title, author, publish date… Yep, it has structure. Check!

Instance: what are some examples of this potential “book” object? Can you name a few? The Alchemist, Ready Player One, Everybody Poops… OK, check!

Purpose: why is this object important to the users and business? Well, “book” is what our library client is providing to people and books are why people come to the library… Check, check, check!

As you are noun foraging, focus on capturing the nouns that have SIP. Avoid capturing components like dropdowns, checkboxes, and calendar pickers—your UX system is not your design system! Components are just the packaging for objects—they are a means to an end. No one is coming to your digital place to play with your dropdown! They are coming for the VALUABLE THINGS and what they can do with them. Those things, or objects, are what we are trying to identify.

Let’s say we work for a startup disrupting the email experience. This is how I’d start my noun foraging.

First I’d look at my own email client, which happens to be Gmail. I’d then look at Outlook and the new HEY email. I’d look at Yahoo, Hotmail…I’d even look at Slack and Basecamp and other so-called “email replacers.” I’d read some articles, reviews, and forum threads where people are complaining about email. While doing all this, I would look for and write down the nouns.

(Before moving on, feel free to go noun foraging for this hypothetical product, too, and then scroll down to see how much our lists match up. Just don’t get lost in your own emails! Come back to me!)

Drumroll, please…

Here are a few nouns I came up with during my noun foraging:

• email message
• thread
• contact
• client
• rule/automation
• email address that is not a contact?
• contact groups
• attachment
• Google doc file / other integrated file
• newsletter? (HEY treats this differently)
• saved responses and templates

Scan your list of nouns and pick out words that you are completely clueless about. In our email example, it might be client or automation. Do as much homework as you can before your session with stakeholders: google what’s googleable. But other terms might be so specific to the product or domain that you need to have a conversation about them.

Aside: here are some real nouns foraged during my own past project work that I needed my stakeholders to help me understand:

• Record Locator
• Incentive Home
• Augmented Line Item
• Curriculum-Based Measurement Probe

This is really all you need to prepare for the workshop session: a list of nouns that represent potential objects and a short list of nouns that need to be defined further.

Facilitate an Object Definition Workshop

You could actually start your workshop with noun foraging—this activity can be done collaboratively. If you have five people in the room, pick five sources, assign one to every person, and give everyone ten minutes to find the objects within their source. When the time’s up, come together and find the overlap. Affinity mapping is your friend here!

If your team is short on time and might be reluctant to do this kind of grunt work (which is usually the case) do your own noun foraging beforehand, but be prepared to show your work. I love presenting screenshots of documents and screens with all the nouns already highlighted. Bring the artifacts of your process, and start the workshop with a five-minute overview of your noun foraging journey.

HOT TIP: before jumping into the workshop, frame the conversation as a requirements-gathering session to help you better understand the scope and details of the system. You don’t need to let them know that you’re looking for gaps in the team’s understanding so that you can prove the need for more user research—that will be our little secret. Instead, go into the session optimistically, as if your knowledgeable stakeholders and PMs and biz folks already have all the answers. 

Then, let the question whack-a-mole commence.

1. What is this thing?

Want to have some real fun? At the beginning of your session, ask stakeholders to privately write definitions for the handful of obscure nouns you might be uncertain about. Then, have everyone show their cards at the same time and see if you get different definitions (you will). This is gold for exposing misalignment and starting great conversations.

As your discussion unfolds, capture any agreed-upon definitions. And when uncertainty emerges, quietly (but visibly) start an “open questions” parking lot. 😉

After definitions solidify, here’s a great follow-up:

2. Do our users know what these things are? What do users call this thing?

Stakeholder 1: They probably call email clients “apps.” But I’m not sure.

Stakeholder 2: Automations are often called “workflows,” I think. Or, maybe users think workflows are something different.

If a more user-friendly term emerges, ask the group if they can agree to use only that term moving forward. This way, the team can better align to the users’ language and mindset.

OK, moving on. 

If you have two or more objects that seem to overlap in purpose, ask one of these questions:

3. Are these the same thing? Or are these different? If they are not the same, how are they different?

You: Is a saved response the same as a template?

Stakeholder 1: Yes! Definitely.

Stakeholder 2: I don’t think so… A saved response is text with links and variables, but a template is more about the look and feel, like default fonts, colors, and placeholder images. 

Continue to build out your growing glossary of objects. And continue to capture areas of uncertainty in your “open questions” parking lot.

If you successfully determine that two similar things are, in fact, different, here’s your next follow-up question:

4. What’s the relationship between these objects?

You: Are saved responses and templates related in any way?

Stakeholder 3:  Yeah, a template can be applied to a saved response.

You, always with the follow-ups: When is the template applied to a saved response? Does that happen when the user is constructing the saved response? Or when they apply the saved response to an email? How does that actually work?

Listen. Capture uncertainty. Once the list of “open questions” grows to a critical mass, pause to start assigning questions to groups or individuals. Some questions might be for the dev team (hopefully at least one developer is in the room with you). One question might be specifically for someone who couldn’t make it to the workshop. And many questions will need to be labeled “user.” 

Do you see how we are building up to our UXR sales pitch?

5. Is this object in scope?

Your next question narrows the team’s focus toward what’s most important to your users. You can simply ask, “Are saved responses in scope for our first release?,” but I’ve got a better, more devious strategy.

By now, you should have a list of clearly defined objects. Ask participants to sort these objects from most to least important, either in small breakout groups or individually. Then, like you did with the definitions, have everyone reveal their sort order at once. Surprisingly—or not so surprisingly—it’s not unusual for the VP to rank something like “saved responses” as #2 while everyone else puts it at the bottom of the list. Try not to look too smug as you inevitably expose more misalignment.

I did this for a startup a few years ago. We posted the three groups’ wildly different sort orders on the whiteboard.

The CEO stood back, looked at it, and said, “This is why we haven’t been able to move forward in two years.”

Admittedly, it’s tragic to hear that, but as a professional, it feels pretty awesome to be the one who facilitated a watershed realization.

Once you have a good idea of in-scope, clearly defined things, this is when you move on to doing more relationship mapping.

6. Create a visual representation of the objects’ relationships

We’ve already done a bit of this while trying to determine if two things are different, but this time, ask the team about every potential relationship. For each object, ask how it relates to all the other objects. In what ways are the objects connected? To visualize all the connections, pull out your trusty boxes-and-arrows technique. Here, we are connecting our objects with verbs. I like to keep my verbs to simple “has a” and “has many” statements.

This system modeling activity brings up all sorts of new questions:

• Can a saved response have attachments?
• Can a saved response use a template? If so, if an email uses a saved response with a template, can the user override that template?
• Do users want to see all the emails they sent that included a particular attachment? For example, “show me all the emails I sent with ProfessionalImage.jpg attached. I’ve changed my professional photo and I want to alert everyone to update it.” 

Solid answers might emerge directly from the workshop participants. Great! Capture that new shared understanding. But when uncertainty surfaces, continue to add questions to your growing parking lot.

Light the fuse

You’ve positioned the explosives all along the floodgates. Now you simply have to light the fuse and BOOM. Watch the buy-in for user research flooooow.

Before your workshop wraps up, have the group reflect on the list of open questions. Make plans for getting answers internally, then focus on the questions that need to be brought before users.

Here’s your final step. Take those questions you’ve compiled for user research and discuss the level of risk associated with NOT answering them. Ask, “if we design without an answer to this question, if we make up our own answer and we are wrong, how bad might that turn out?” 

With this methodology, we are cornering our decision-makers into advocating for user research as they themselves label questions as high-risk. Sorry, not sorry. 

Now is your moment of truth. With everyone in the room, ask for a reasonable budget of time and money to conduct 6–8 user interviews focused specifically on these questions. 

HOT TIP: if you are new to UX research, please note that you’ll likely need to rephrase the questions that came up during the workshop before you present them to users. Make sure your questions are open-ended and don’t lead the user into any default answers.

Final words: Hold the screen design!

Seriously, if at all possible, do not ever design screens again without first answering these fundamental questions: what are the objects and how do they relate?

I promise you this: if you can secure a shared understanding between the business, design, and development teams before you start designing screens, you will have less heartache and save more time and money, and (it almost feels like a bonus at this point!) users will be more receptive to what you put out into the world. 

I sincerely hope this helps you win time and budget to go talk to your users and gain clarity on what you are designing before you start building screens. If you find success using noun foraging and the Object Definition Workshop, there’s more where that came from in the rest of the ORCA process, which will help prevent even more late-in-the-game scope tugs-of-war and strategy pivots. 

All the best of luck! Now go sell research!

Containers are used to style CSS. In fact, the whole website is made of containers, from the computer viewport to components on a webpage. However, there are times when we have a fresh element that forces us to reevaluate our design strategy.

Square features, for instance, make it fun to play with round picture areas. Mobile screen notches and electronic keyboards present difficulties in how to best manage content that stays out of sight. And two display or portable devices make us reassess how to best utilize available space in a number of various device postures.

These new evolutions of the internet system made it both more demanding and more exciting to design products. They’re fantastic options for us to leave our triangular containers.

I’d like to talk about a new feature similar to the above: the Window Controls Overlay for Progressive Web Apps ( PWAs ).

Democratic Web Apps are bridging the gap between websites and apps. They combine the best of both worlds. On the one hand, they are flexible, shareable, and stable, just like websites. On the other hand, they provide more effective features, work online, and read documents just like local apps.

PWAs are really exciting as a style area because they challenge us to consider how to combine online and native user interface. On desktop products in certain, we have more than 40 years of history telling us what software may look like, and it can be hard to break out of this mental concept.

PWAs on desktop are ultimately limited to the window they appear in, which is a rectangle with a title bar at the top.

Here’s what a typical desktop PWA app looks like:

Sure, as the author of a PWA, you get to choose the color of the title bar (using the Web Application Manifest theme_color property ), but that’s about it.

What if we could look beyond this box and reclaim the entire window of the app? Doing so would give us a chance to make our apps more beautiful and feel more integrated in the operating system.

The Window Controls Overlay offers exactly this. This new PWA functionality makes it possible to take advantage of the full surface area of the app, including where the title bar normally appears.

About the window and title bar controls

Let’s start with an explanation of what the title bar and window controls are.

The title bar, which typically contains the app’s name, appears at the top of an app window. Window controls are the affordances, or buttons, that make it possible to minimize, maximize, or close the app’s window, and are also displayed at the top.

Window Controls Overlay removes the physical constraint of the title bar and window controls areas. The title bar and window control buttons are overlayed on top of the application’s web content, allowing for full height to be the app window.

If you are reading this article on a desktop computer, take a quick look at other apps. They’re probably already doing something similar. In fact, the very web browser you are using to read this uses the top area to display tabs.

Spotify displays album artwork all the way to the top edge of the application window.

Microsoft Word uses the available title bar space to display the auto-save and search functionalities, and more.

This feature’s main goal is to give you the ability to use this space with your own content while also providing a way to account for the window control buttons. And it enables you to offer this modified experience on a range of platforms while not adversely affecting the experience on browsers or devices that don’t support Window Controls Overlay. PWAs are all about progressive enhancement, so this feature is a chance to make your app use this extra space when it’s available.

Let’s use the feature

We’ll be creating a demo app for the remainder of this article to learn more about how to use the feature.

The demo app is called 1DIV. Users can create designs using only CSS and a single HTML element in this straightforward CSS playground.

The app has two pages. The first lists your existing CSS designs:

The second page enables the creation and editing of CSS designs:

Since I’ve added a simple web manifest and service worker, we can install the app as a PWA on desktop. What it appears to be on macOS is shown below:

And on Windows:

Our app looks good, but the first page’s white title bar is a waste of space. In the second page, it would be really nice if the design area went all the way to the top of the app window.

Let’s use the Window Controls Overlay feature to make this better.

Enabling Window Controls Overlay

The film is still in its experimental phase right now. To try it, you need to enable it in one of the supported browsers.

It has currently been implemented in Chromium as a result of a collaboration between Microsoft and Google. We can therefore use it in Chrome or Edge by going to the internal about: //flags page, and enabling the Desktop PWA Window Controls Overlay flag.

Using the overlay of window controls

To use the feature, we need to add the following display_override member to our web app’s manifest file:

{ "name": "1DIV", "description": "1DIV is a mini CSS playground", "lang": "en-US", "start_url": "/", "theme_color": "#ffffff", "background_color": "#ffffff", "display_override": [ "window-controls-overlay" ], "icons": [ ... ]}

On the surface, the feature seems to be very simple to use. This manifest change is the only thing we need to make the title bar disappear and turn the window controls into an overlay.

We’ll need some CSS and JavaScript code to make the most of the title bar area in our design and ensure that all users have a great experience regardless of device or browser.

Here is what the app looks like now:

Our logo, search field, and NEW button are now partially covered by the window controls, but the title bar has been removed, which is what we wanted. Our layout now begins at the top of the window.

It’s similar on Windows, with the difference that the close, maximize, and minimize buttons appear on the right side, grouped together with the PWA control buttons:

CSS to avoid window controls

Along with the feature, new CSS environment variables have been introduced:

• titlebar-area-x
• titlebar-area-y
• titlebar-area-width
• titlebar-area-height

You can position your content where the title bar would have been by using these variables with the CSS env function to prevent it from overlapping with the window controls. In our case, we’ll use two of the variables to position our header, which contains the logo, search bar, and NEW button.

header { position: absolute; left: env(titlebar-area-x, 0); width: env(titlebar-area-width, 100%); height: var(--toolbar-height);}

The titlebar-area-x variable gives us the distance from the left of the viewport to where the title bar would appear, and titlebar-area-width is its width. (Remember, this is not equivalent to the width of the entire viewport, just the title bar portion, which as noted earlier, doesn’t include the window controls.)

By doing this, we make sure our content remains fully visible. We’re also defining fallback values (the second parameter in the env() function) for when the variables are not defined (such as on non-supporting browsers, or when the Windows Control Overlay feature is disabled).

Our header now adapts to its surroundings, and it doesn’t seem like the window control buttons were left out. The app looks a lot more like a native app.

Changing the window controls the background color so that it blends in

Now let’s take a closer look at our second page: the CSS playground editor.

Not very good. Our CSS demo area does go all the way to the top, which is what we wanted, but the way the window controls appear as white rectangles on top of it is quite jarring.

We can change the theme color of the app to fix this. There are a couple of ways to define it:

The theme_color manifest member in the web app manifest file can be used by PWAs to define a theme color. This color is then used by the OS in different ways. It serves as a background color for the title bar and window controls on desktop computers.
• Websites can use the theme-color meta tag as well. It’s used by browsers to customize the color of the UI around the web page. For PWAs, this color can override the manifest theme_color.

In our case, we can set the manifest theme_color to white to provide the right default color for our app. The OS will read this color value when the app is installed and use it to make the window controls background color white. This color works great for our main page with the list of demos.

The theme-color meta tag can be changed at runtime, using JavaScript. So we can do that to override the white with the right demo background color when one is opened.

Here is the function we’ll use:

function themeWindow(bgColor) { document.querySelector("meta[name=theme-color]").setAttribute('content', bgColor);}

With this in place, we can envision how using CSS and color transitions to smoothly transition between the list page and the demo page and make the window control buttons blend in with the rest of the app’s interface.

Dragging the window

Now, getting rid of the title bar entirely does have an important accessibility consequence: it’s much more difficult to move the application window around.

Users can drag and click their way to a sizable area in the title bar, but when using the Window Controls Overlay feature, they are limited to where the control buttons are, and must carefully place their fingers in between these buttons to move the window.

Fortunately, this can be fixed using CSS with the app-region property. This property is, for now, only supported in Chromium-based browsers and needs the -webkit- vendor prefix. 

To make any element of the app become a dragging target for the window, we can use the following:

-webkit-app-region: drag;

Additionally, it is possible to specify explicitly that an element be non-draggable:

-webkit-app-region: no-drag; 

These options can be useful for us. We can rename the entire header as a dragging target, but we can also make the NEW button and search field non-draggable so they can still be used as they normally are.

However, because the editor page doesn’t display the header, users wouldn’t be able to drag the window while editing code. So let’s take a different strategy. We’ll create another element before our header, also absolutely positioned, and dedicated to dragging the window.

...

.drag { position: absolute; top: 0; width: 100%; height: env(titlebar-area-height, 0); -webkit-app-region: drag;}

With the above code, we’re making the draggable area span the entire viewport width, and using the titlebar-area-height variable to make it as tall as what the title bar would have been. This way, our draggable area is aligned with the window control buttons as shown below.

And now to make sure our search field and button are usable:

header .search,header .new { -webkit-app-region: no-drag;}

With the above code, users can click and drag where the title bar used to be. Users are expecting to be able to move windows on their desktops, and we are not breaking this expectation, which is good.

adapting to window resizing

It may be useful for an app to know both whether the window controls overlay is visible and when its size changes. In our situation, there won’t be enough room for the search field, logo, and button to fit because the user made the window very narrow. We would need to lower them a little.

The Window Controls Overlay feature comes with a JavaScript API we can use to do this: navigator.windowControlsOverlay.

The API offers three intriguing features:

• navigator.windowControlsOverlay.visiblelets us know whether the overlay is visible.
• navigator.windowControlsOverlay.getBoundingClientRect()lets us know where the title bar’s area is located and how big it is.
• navigator.windowControlsOverlay.ongeometrychangelets us know when the size or visibility changes.

Use this to check the size of the title bar area and lower the header if necessary.

if (navigator.windowControlsOverlay) { navigator.windowControlsOverlay.addEventListener('geometrychange', () => { const { width } = navigator.windowControlsOverlay.getBoundingClientRect(); document.body.classList.toggle('narrow', width < 250); });}

In the example above, we set the narrow class on the body of the app if the title bar area is narrower than 250px. We could do something similar with a media query, but using the windowControlsOverlay API has two advantages for our use case:

• It’s only fired when the feature is supported and used, we don’t want to adapt the design otherwise.
• The title bar area is different for different operating systems, which is great because Mac and Windows have different title bar sizes. Using a media query wouldn’t make it possible for us to know exactly how much space remains.

.narrow header { top: env(titlebar-area-height, 0); left: 0; width: 100%;}

When the window is too small, we can use the above CSS code to move our header down and move the thumbnails down in accordance with this.

Thirty pixel of creative challenge

Using the Window Controls Overlay feature, we were able to take our simple demo app and turn it into something that feels so much more integrated on desktop devices. Something that transcends the traditional window restrictions and offers its users a personalized experience.

In reality, this feature only gives us about 30 pixels of extra room and comes with challenges on how to deal with the window controls. However, these additional space and those difficulties can be used to create creative challenges.

More devices of all shapes and forms get invented all the time, and the web keeps on evolving to adapt to them. To make it easier for us web authors to integrate more and more fully with those devices, new features are added to the web platform. From watches or foldable devices to desktop computers, we need to evolve our design approach for the web. Nowadays, web building enables us to think outside the rectangular box.

So let’s embrace this. Use the common technologies at our disposal and experiment with new concepts to create personalized experiences for all devices using just one codebase!

If you get a chance to try the Window Controls Overlay feature and have feedback about it, you can open issues on the spec’s repository. You can help improve this feature’s development, which is still in its early stages. Or, you can take a look at the feature’s existing documentation, or this demo app and its source code.

The mobile-first style approach is great—it focuses on what really matters to the consumer, it’s well-practiced, and it’s been a popular style design for years. But developing your CSS mobile-first should also be fantastic, too…right?

Well, not necessarily. Classic mobile-first CSS development is based on the principle of overwriting style declarations: you begin your CSS with default style declarations, and overwrite and/or add new styles as you add breakpoints with min-width media queries for larger viewports (for a good overview see “What is Mobile First CSS and Why Does It Rock?”). But all those exceptions create complexity and inefficiency, which in turn can lead to an increased testing effort and a code base that’s harder to maintain. Admit it—how many of us willingly want that?

Mobile-first CSS may yet be the best option for your own projects, but you need to first determine how ideal it is in light of the physical design and user interactions you’re working on. To help you get started, here’s how I go about tackling the elements you need to watch for, and I’ll discuss some alternative remedies if mobile-first doesn’t seem to fit your job.

Benefits of mobile-first

Some of the points to enjoy with mobile-first CSS growth —and why it’s been the de facto growth strategy for thus long—make a lot of feeling:

Development order. One thing you definitely get from mobile-first is a great development hierarchy—you only focus on the cellular view and get developing.

Tried and tested. It’s a tried-and-true method that has worked for years because it solves a problem actually also.

Prioritizes the smart see. The mobile view is the simplest and arguably the most significant because it covers all the crucial user journeys and frequently accounts for a higher proportion of user visits ( depending on the project ) ).

Stops desktop-centric growth. It can be tempting to first focus on the desktop perspective because enhancement is done using pc servers. However, considering mobile from the beginning prevents us from getting stuck eventually; no one wants to spend their time getting a site that is focused on desktops to operate on mobile devices!

Drawbacks of mobile-first

Model declarations can be set at lower breakpoints and finally overwritten at higher breakpoints:

More difficulty. The more unwanted script you inherit from lower thresholds, the higher up the order you go.

Higher CSS sensitivity. A school name declaration’s default style has then a higher specificity that has been returned to the browser’s default value. When trying to keep the CSS candidates as simple as possible, this can cause trouble on complex tasks.

Requires more analysis tests. All higher thresholds must be regression tested if modifications to CSS at a lower see ( such as adding a new style ) are to be made.

The browser can’t prioritize CSS downloads. At wider breakpoints, classic mobile-first min-width media queries don’t leverage the browser’s capability to download CSS files in priority order.

The issue of home value supersedes

Overwriting values is not necessarily essentially bad; CSS was created to do that. However, sharing incorrect values is counterproductive and can be burdensome and inadequate. When you have to replace styles to restore them to their defaults, which may cause issues after, especially if you are using a combination of bespoke CSS and power classes, it can also lead to more fashion specificity. We won’t be able to use a utility class on a style that has been increased in specificity when it was reset.

With this in mind, I’m developing CSS with a focus on the default values much more these days. Since there’s no specific order, and no chains of specific values to keep track of, this frees me to develop breakpoints simultaneously. I concentrate on finding common styles and isolating the specific exceptions in closed media query ranges (that is, any range with a max-width set). 

This approach opens up some opportunities, as you can look at each breakpoint as a clean slate. If a component’s layout looks like it should be based on Flexbox at all breakpoints, it’s fine and can be coded in the default style sheet. However, if it appears that Grid is much better for large screens and Flexbox is much better for mobile, both can be accomplished entirely independently when the CSS is entered into closed media query ranges. Additionally, having a thorough understanding of any given component in all breakpoints upfront is necessary for developing simultaneously. This can help identify issues with the design more quickly in the development process. We don’t want to travel down the rabbit hole while creating complex mobile components, only to discover that the desktop designs are just as complex and incompatible with the HTML we created for the mobile view!

Though this approach isn’t going to suit everyone, I encourage you to give it a try. There are plenty of tools out there to help with concurrent development, such as Responsively App, Blisk, and many others.

Having said that, I don’t feel the order itself is particularly relevant. If you like to work on one device at a time, are comfortable with focusing on the mobile view, and have a good understanding of the requirements for other breakpoints, then you should definitely stick to the classic development order. The key is to find common styles and exceptions so that you can include them in the appropriate stylesheet, which is a manual tree-shaking procedure! Personally, I find this a little easier when working on a component across breakpoints, but that’s by no means a requirement.

Closed media query ranges in practice

In classic mobile-first CSS we overwrite the styles, but we can avoid this by using media query ranges. To illustrate the difference ( I’m using SCSS for brevity ), let’s assume there are three visual designs:

• smaller than 768
• from 768 to below 1024
• 1024 and anything larger

Take a simple example where a block-level element has a default padding of “20px,” which is overwritten at tablet to be “40px” and set back to “20px” on desktop.

.my-block { padding: 20px; @media (min-width: 768px) { padding: 40px; } @media (min-width: 1024px) { padding: 20px; }}

.my-block { padding: 20px; @media (min-width: 768px) and (max-width: 1023.98px) { padding: 40px; }}

The subtle difference is that the mobile-first example sets the default padding to “20px” and then overwrites it at each breakpoint, setting it three times in total. In contrast, the second example sets the default padding to “20px” and only overrides it at the relevant breakpoint where it isn’t the default value (in this instance, tablet is the exception).

The goal is to: 

• Only set styles when needed. 
• Not set them with the expectation of overwriting them later on, again and again. 

To this end, closed media query ranges are our best friend. If we need to make a change to any given view, we make it in the CSS media query range that applies to the specific breakpoint. We’ll be much less likely to introduce unwanted alterations, and our regression testing only needs to focus on the breakpoint we have actually edited. 

Taking the above example, if we find that .my-block spacing on desktop is already accounted for by the margin at that breakpoint, and since we want to remove the padding altogether, we could do this by setting the mobile padding in a closed media query range.

.my-block {  @media (max-width: 767.98px) {    padding: 20px;  }  @media (min-width: 768px) and (max-width: 1023.98px) {    padding: 40px;  }}

The browser default padding for our block is “0,” so instead of adding a desktop media query and using unset or “0” for the padding value (which we would need with mobile-first), we can wrap the mobile padding in a closed media query (since it is now also an exception) so it won’t get picked up at wider breakpoints. At the desktop breakpoint, we won’t need to set any padding style, as we want the browser default value.

separating the CSS versus combining it

Due to the browser's concurrent request limit (typically around six ), it was crucial back then to keep the number of requests to a minimum. As a consequence, the use of image sprites and CSS bundling was the norm, with all the CSS being downloaded in one go, as one stylesheet with highest priority.

With HTTP/2 and HTTP/3 now on the scene, the number of requests is no longer the big deal it used to be. By using a media query, we can separate the CSS into several files. The obvious benefit of this is that the browser can now request the CSS it currently requires with a higher priority than the CSS it doesn't. This increases the speed at which pages are rendered more efficiently.

Which HTTP version are you using?

To determine which version of HTTP you're using, go to your website and open your browser's dev tools. Next, select the Network tab and check whether the Protocol column is visible. If "h2" is listed under Protocol, it means HTTP/2 is being used.

Note: to view the Protocol in your browser's dev tools, go to the Network tab, reload your page, right-click any column header ( e. g., Name ), and check the Protocol column.

Also, if your site is still using HTTP/1... WHY?!! What are you anticipating? The HTTP/2 user support is excellent.

Splitting the CSS

Separating the CSS into individual files is a worthwhile task. Linking the separate CSS files using the relevant media attribute allows the browser to identify which files are needed immediately (because they’re render-blocking) and which can be deferred. Based on this, it allocates each file an appropriate priority.

We can see that the mobile and default CSS are loaded with" Highest" priority in the following example of a website that is visited on a mobile breakpoint, since they are currently required to render the page. The remaining CSS files ( print, tablet, and desktop ) are still downloaded in case they'll be needed later, but with" Lowest" priority.

Before rendering can begin, the browser will need to download the CSS file and parse it using bundled CSS before rendering can begin.

While, as noted, with the CSS separated into different files linked and marked up with the relevant media attribute, the browser can prioritize the files it currently needs. Using closed media query ranges allows the browser to do this at all widths, as opposed to classic mobile-first min-width queries, where the desktop browser would have to download all the CSS with Highest priority. We can’t assume that desktop users always have a fast connection. For instance, in many rural areas, internet connection speeds are still slow. 

Depending on project requirements, the media queries and the number of separate CSS files will vary from project to project, but the example below might look similar.

Depending on the project’s deployment strategy, a change to one file (mobile.css, for example) would only require the QA team to regression test on devices in that specific media query range. Compare that to the prospect of deploying the single bundled site.css file, an approach that would normally trigger a full regression test.

Moving on

The adoption of mobile-first CSS was a significant development milestone because it allowed front-end developers to concentrate on mobile web applications rather than creating websites for desktop use and attempting to retrofit them to work on other devices.

I don't think anyone wants to return to that development model again, but it's important we don't lose sight of the issue it highlighted: that things can easily get convoluted and less efficient if we prioritize one particular device—any device—over others. For this reason, focusing on the CSS in its own right, always mindful of what is the default setting and what's an exception, seems like the natural next step. I've started to notice subtle simplifications in the CSS I write for myself as well as other developers, and that the testing and maintenance work is also a little more organized and effective.

In general, making CSS rule creation as simple as possible is ultimately a more effective strategy than moving around in circles of overrides. But whichever methodology you choose, it needs to suit the project. Mobile-first may—or may not—turn out to be the best choice for what's involved, but first you need to solidly understand the trade-offs you're stepping into.

However, we’re still very far from this best.

At the time, I didn’t realize yet how to functionally combine morality. Yes, I had found some tools that had worked for me in past projects, such as using checklists, notion monitoring, and “dark truth” sessions, but I didn’t manage to use those in every task. I had only partially succeeded in achieving a higher ( moral ) quality of design, which was not what I would consider to be structurally integrated because I was still struggling for time and support.

I made a deeper investigation into the main causes of business that prevent us from practicing regular social style. Today, after much research and experimentation, I believe that I’ve found the code that will let us functionally combine morality. And it’s amazingly easy! However, we must first move out to understand what we’re up against.

Control the system

Unfortunately, we’re trapped in a capitalist structure that reinforces materialism and inequality, and it’s obsessed with the dream of infinite growth. Sea levels, temperature, and our demand for energy continue to rise unquestioned, while the divide between rich and poor continues to increase. Owners expect ever-higher returns on their investments, and firms feel forced to set short-term goals that reflect this. Over the last years, those targets have twisted our well-intended human-centered mentality into a powerful system that promotes ever-higher levels of consumption. When we’re working for an organization that pursues “double-digit growth” or “aggressive sales targets” ( which is 99 percent of us ), that’s very hard to resist while remaining human friendly. Even with our best purposes, and even though we like to suggest that we create solutions for people, we’re a part of the problem.

What can we do to alter this?

We can begin by acting at the appropriate amount within the structure. Donella H. Meadows, a system scholar, previously listed ways to influence a system in order of success. When you apply these to architecture, you get:

At the lowest level of effectiveness, you can change numbers such as accessibility results or the number of layout views. However, none of that will alter a company’s course.
• Similarly, affecting buffers ( such as team budgets ), stocks ( such as the number of designers ), flows ( such as the number of new hires ), and delays ( such as the time that it takes to hear about the effect of design ) won’t significantly affect a company.
• Focusing rather on feedback rings such as management power, staff identification, or design-system purchases can help a business become better at achieving its objectives. But that doesn’t alter the goals themselves, which means that the business will also work against your ethical-design ideals.
• The next level, data flows, is what most ethical-design activities focus on then: the transfer of moral methods, tools, articles, conferences, workshops, and so on. This is where ethical design has largely remained theoretical. We’ve been focusing on the wrong system level all this time.
• Take rules, for example—they beat knowledge every time. There can be widely accepted rules, such as how finance works, or a scrum team’s definition of done. However, unofficial rules intended to maintain profits can also smother ethical design, which are frequently revealed through statements like” the client didn’t ask for it” or “don’t make it too big.”
• It is difficult to change the laws without exercising official authority. That’s why the next level is so influential: self-organization. Experimentation, bottom-up initiatives, passion projects, self-steering teams—all of these are examples of self-organization that improve the resilience and creativity of a company. It’s exactly this diversity of viewpoints that’s needed to structurally tackle big systemic issues like consumerism, wealth inequality, and climate change.
• Yet even stronger than self-organization are objectives and metrics. Our businesses strive to increase their profits, which means that everyone in the company makes an effort to increase that profit. And once I realized that profit is merely a measure, I realized how crucial a very specific, defined metric can be in the direction of a company.

The takeaway? We must first change the measurable goals of the company we work for from the bottom up if we truly want to incorporate ethics into our daily design practice.

Redefine success

Traditionally, we consider a product or service successful if it’s desirable to humans, technologically feasible, and financially viable. You tend to see these represented as equals, if you type the three words in a search engine, you’ll find diagrams of three equally sized, evenly arranged circles.

But in our hearts, we all know that the three dimensions aren’t equally weighted: it’s viability that ultimately controls whether a product will go live. So what might a more accurate representation look like:

The means are feasibility and desire, and viability is the aim. Companies—outside of nonprofits and charities—exist to make money.

A genuinely purpose-driven company would try to reverse this dynamic: it would recognize finance for what it was intended for: a means. Therefore, both feasibility and viability are effective means of achieving the company’s goals. It makes intuitive sense: to achieve most anything, you need resources, people, and money. ( Fun fact: the Italian language knows no difference between feasibility and viability, both are simply fattibilità. )

However, it is not enough to substitute viable for desirable for achieve an ethical result. Consumption is still associated with desirability because the associated activities aim to determine what people want, regardless of whether or not it benefits them. Desirability objectives, such as user satisfaction or conversion, don’t consider whether a product is healthy for people. They don’t stop us from developing products that deceive or deceive people, or do they prevent us from reducing the wealth gap in society. They are unable to restore a healthy relationship with nature.

There’s a fourth dimension of success that’s missing: our designs also need to be ethical in the effect that they have on the world.

This is hardly a new idea. Many similar models exist, some calling the fourth dimension accountability, integrity, or responsibility. What I’ve never seen before, however, is the necessary step that comes after: to influence the system as designers and to make ethical design more practical, we must create objectives for ethical design that are achievable and inspirational. There’s no one way to do this because it highly depends on your culture, values, and industry. However, I’ll share the version I created with a group of design agency coworkers. Consider it a template to get started.

Pursue well-being, equity, and sustainability

We created objectives that address design’s effect on three levels: individual, societal, and global.

An objective on the individual level teaches us that success transcends the typical area of focus on usability and satisfaction, taking into account factors like how much time and effort are required from users. We pursued well-being:

We create products and services that allow for people’s health and happiness. Our solutions are calm, transparent, nonaddictive, and nonmisleading. We respect our users ‘ time, attention, and privacy, and help them make healthy and respectful choices.

An objective on the societal level forces us to consider our impact beyond just the user, widening our attention to the economy, communities, and other indirect stakeholders. We called this objective equity:

We develop goods and services that benefit society. We consider economic equality, racial justice, and the inclusivity and diversity of people as teams, users, and customer segments. We listen to local culture, communities, and those we affect.

Finally, the global goal of maintaining harmony with humanity’s sole home is the ultimate goal. Referring to it simply as sustainability, our definition was:

We develop goods and services that reward reuse and sufficiency. Our solutions support the circular economy: we create value from waste, repurpose products, and prioritize sustainable choices. We deliver functionality instead of ownership, and we limit energy use.

In essence, ethical design ( to us ) meant achieving the wellbeing of each user and an equitable value distribution within society through a design that can sustain our living planet. When we introduced these objectives in the company, for many colleagues, design ethics and responsible design suddenly became tangible and achievable through practical—and even familiar—actions.

Measure impact

But defining these objectives still isn’t enough. What truly caught the attention of senior management was the fact that we created a way to measure every design project’s well-being, equity, and sustainability.

This overview lists example metrics that you can use as you pursue well-being, equity, and sustainability:

There’s a lot of power in measurement. As the saying goes, what gets measured gets done. Donella Meadows once provided this illustration:

The system will produce military spending if the desired system state is national security, which is defined as the amount of money spent on the military. It may or may not produce national security”.

This phenomenon explains why desirability is a poor indicator of success: it’s typically defined as the increase in customer satisfaction, session length, frequency of use, conversion rate, churn rate, download rate, and so on. But none of these metrics increase the health of people, communities, or ecosystems. What if instead we measured success through metrics for ( digital ) well-being, such as ( reduced ) screen time or software energy consumption?

There’s another important message here. Even if we set an objective to build a calm interface, if we were to choose the wrong metric for calmness—say, the number of interface elements—we could still end up with a screen that induces anxiety. The wrong metric can completely destroy good intentions.

Additionally, choosing the right metric is enormously helpful in focusing the design team. You are forced to consider what success looks like in real life and how you can demonstrate that you have met your ethical goals once you have chosen the metrics to use. It also makes you think about what we as designers have control over: what can I add or change in my design process to achieve the desired level of success? The response to this query provides a lot of focus and clarity.

And finally, it’s good to remember that traditional businesses run on measurements, and managers love to spend much time discussing charts ( ideally hockey-stick shaped ) —especially if they concern profit, the one-above-all of metrics. For good or ill, to improve the system, to have a serious discussion about ethical design with managers, we’ll need to speak that business language.

Practice daily ethical design

Only then do you have a chance to structurally practice ethical design once you have defined your objectives and have a reasonable idea of the potential metrics for your design project. It” simply” turns into a matter of using your imagination and sprinkling from the knowledge and tools that are already at your disposal.

I think this is quite exciting! The design process is presented with a whole new set of difficulties and considerations. Would a simple illustration suffice, or should you go with that energizing video? Which typeface is the most calm and inclusive? What brand-new equipment and techniques do you employ? When is the website’s end of life? How can you offer the same service to users with less focus? How can you ensure that those who are affected by decisions are present when they are made? How can you measure our effects?

The definition of success will fundamentally alter what it means to do good design.

There is, however, a final piece of the puzzle that’s missing: convincing your client, product owner, or manager to be mindful of well-being, equity, and sustainability. For this, it’s essential to engage stakeholders in a dedicated kickoff session.

Start it off or return to the pre-existing

The most crucial meeting can be overlooked, making the kickoff so simple to overlook. It consists of two major phases: 1 ) the alignment of expectations, and 2 ) the definition of success.

In the first phase, the entire ( design ) team goes over the project brief and meets with all the relevant stakeholders. Everyone gets to know one another, shares their hopes for the outcome and their contributions to it. Assumptions are raised and discussed. The goal is to reach the same level of understanding and, in turn, to prevent mistakes and surprises later on in the project.

For example, for a recent freelance project that aimed to design a digital platform that facilitates US student advisors ‘ documentation and communication, we conducted an online kickoff with the client, a subject-matter expert, and two other designers. We used a combination of canvases on Miro: one with questions from” Manual of Me” ( to get to know each other ), a Team Canvas ( to express expectations ), and a version of the Project Canvas to align on scope, timeline, and other practical matters.

The kickoff’s primary goal is the stated above. But just as important as expressing expectations is agreeing on what success means for the project—in terms of desirability, viability, feasibility, and ethics. What are the objectives in each dimension?

It is crucial to reach an understanding of what success means at this early stage because you can rely on it for the duration of the project. The design team can raise diversity as a specific success criterion during the kickoff if, for instance, they want to create an inclusive app for a diverse user group. If the client consents, the team will be able to recite that promise throughout the project. As we agreed in our first meeting, having a diverse user group that includes A and B is essential to creating a successful product. Therefore, we conduct activity X and follow the research procedure Y. Compare those odds to a scenario where the team had to request permission halfway through the project and didn’t agree to it in advance. The client might argue that that was in excess of the agreed scope, and she would be correct.

To define success, I created a round canvas known as the” Wheel of Success” for this freelance project. It consists of an inner ring, meant to capture ideas for objectives, and a set of outer rings, meant to capture ideas on how to measure those objectives. The rings are divided into five dimensions of successful design: healthy, equitable, sustainable, desirable, feasible, and viable.

We went through each dimension, writing down ideas on digital sticky notes. Then we exchanged ideas and verbally agreed on the most crucial ones. Our client, for instance, agreed that the platform’s success depends heavily on sustainability and progressive enhancement. Additionally, the subject-matter expert stressed the value of involving students from underprivileged and low-income groups in the design process.

In a project brief that adequately described these elements, we consolidated our ideas and agreed on them after the kickoff.

the project’s origin and purpose: why are we doing this project?
• the problem definition: what do we want to solve?
• the concrete goals and metrics for each success dimension: what do we want to achieve?
• the scope, process, and role descriptions: how will we achieve it?

With such a brief in place, you can use the agreed-upon objectives and concrete metrics as a checklist of success, and your design team will be ready to pursue the right objective—using the tools, methods, and metrics at their disposal to achieve ethical outcomes.

Conclusion

Over the past year, quite a few colleagues have asked me,” Where do I start with ethical design”? Create a session with your stakeholders to ( re)define success, which is what my response has always been. Even though you might not always be entirely successful in coming to terms with goals that address all responsibility objectives, that consistently beats the status quo. If you want to be an ethical, responsible designer, there’s no skipping this step.

To be even more specific: if you consider yourself a strategic designer, your challenge is to define ethical objectives, set the right metrics, and conduct those kick-off sessions. If you think of yourself as a system designer, your first step should be to understand how your industry contributes to consumerism and inequality, how finance drives business, and how to think about how to use the system to exert the most influence. Then redefine success to give those levers a new lease of life.

And for those who identify as service designers, UX designers, or UI designers, steer clear of the toolkits, meetups, and conferences for a while if you truly want to have a positive, meaningful impact. Instead, gather your colleagues and define goals for well-being, equity, and sustainability through design. Engage your stakeholders in a workshop and challenge them to think of ways to accomplish and evaluate those ethical goals. Take their input, make it concrete and visible, ask for their agreement, and hold them to it.

Otherwise, I’m genuinely sorry to say, you’re wasting your precious time and creative energy.

Of course, engaging your stakeholders in this way can be uncomfortable. Many of my colleagues expressed doubts such as” What will the client think of this”?,” Will they take me seriously”?, and “Can’t we just do it within the design team instead”? In fact, a product manager once questioned why ethics couldn’t just be a set process in design; to simply do it without making the effort to define ethical goals. It’s a tempting idea, right? We wouldn’t need to engage in contentious discussions with stakeholders about what values or which key-performance indicators to use. It would let us focus on what we like and do best: designing.

But as systems theory tells us, that’s not enough. That uncomfortable space is where we need to be if we truly want to make a difference, for those of us who aren’t from marginalized groups and have the privilege of speaking up and being heard. We can’t remain within the design-for-designers bubble, enjoying our privileged working-from-home situation, disconnected from the real world out there. If we only keep talking about ethical design and it continues to be at the level of articles and toolkits, for those of us who have the chance to speak up and be heard, we are not designing ethically. It’s just theory. By challenging them to redefine success in business, we must actively engage with our colleagues and clients.

With a bit of courage, determination, and focus, we can break out of this cage that finance and business-as-usual have built around us and become facilitators of a new type of business that can see beyond financial value. We simply need to come to terms with the right goals at the start of each design project, identify the appropriate metrics, and acknowledge that we already have everything in place to begin. That’s what it means to do daily ethical design.

For their inspiration and support over the years, I would like to thank Emanuela Cozzi Schettini, José Gallegos, Annegret Bönemann, Ian Dorr, Vera Rademaker, Virginia Rispoli, Cecilia Scolaro, Rouzbeh Amini, and many others.

As a UX professional in today’s data-driven landscape, it’s increasingly likely that you’ve been asked to design a personalized digital experience, whether it’s a public website, user portal, or native application. Yet while there continues to be no shortage of marketing hype around personalization platforms, we still have very few standardized approaches for implementing personalized UX.

That’s where we come in. After completing dozens of personalization projects over the past few years, we gave ourselves a goal: could you create a holistic personalization framework specifically for UX practitioners? The Personalization Pyramid is a designer-centric model for standing up human-centered personalization programs, spanning data, segmentation, content delivery, and overall goals. By using this approach, you will be able to understand the core components of a contemporary, UX-driven personalization program (or at the very least know enough to get started). 

Getting Started

For the sake of this article, we’ll assume you’re already familiar with the basics of digital personalization. A good overview can be found here: Website Personalization Planning. While UX projects in this area can take on many different forms, they often stem from similar starting points.      

Common scenarios for starting a personalization project:

• Your organization or client purchased a content management system (CMS) or marketing automation platform (MAP) or related technology that supports personalization
• The CMO, CDO, or CIO has identified personalization as a goal
• Customer data is disjointed or ambiguous
• You are running some isolated targeting campaigns or A/B testing
• Stakeholders disagree on personalization approach
• Mandate of customer privacy rules (e.g. GDPR) requires revisiting existing user targeting practices

Regardless of where you begin, a successful personalization program will require the same core building blocks. We’ve captured these as the “levels” on the pyramid. Whether you are a UX designer, researcher, or strategist, understanding the core components can help make your contribution successful.  

From top to bottom, the levels include:

1. North Star: What larger strategic objective is driving the personalization program? 
2. Goals: What are the specific, measurable outcomes of the program? 
3. Touchpoints: Where will the personalized experience be served?
4. Contexts and Campaigns: What personalization content will the user see?
5. User Segments: What constitutes a unique, usable audience? 
6. Actionable Data: What reliable and authoritative data is captured by our technical platform to drive personalization?  
7. Raw Data: What wider set of data is conceivably available (already in our setting) allowing you to personalize?

We’ll go through each of these levels in turn. To help make this actionable, we created an accompanying deck of cards to illustrate specific examples from each level. We’ve found them helpful in personalization brainstorming sessions, and will include examples for you here.

Starting at the Top

The components of the pyramid are as follows:

North Star

A north star is what you are aiming for overall with your personalization program (big or small). The North Star defines the (one) overall mission of the personalization program. What do you wish to accomplish? North Stars cast a shadow. The bigger the star, the bigger the shadow. Example of North Starts might include: 

1. Function: Personalize based on basic user inputs. Examples: “Raw” notifications, basic search results, system user settings and configuration options, general customization, basic optimizations
2. Feature: Self-contained personalization componentry. Examples: “Cooked” notifications, advanced optimizations (geolocation), basic dynamic messaging, customized modules, automations, recommenders
3. Experience: Personalized user experiences across multiple interactions and user flows. Examples: Email campaigns, landing pages, advanced messaging (i.e. C2C chat) or conversational interfaces, larger user flows and content-intensive optimizations (localization).
4. Product: Highly differentiating personalized product experiences. Examples: Standalone, branded experiences with personalization at their core, like the “algotorial” playlists by Spotify such as Discover Weekly.

Goals

As in any good UX design, personalization can help accelerate designing with customer intentions. Goals are the tactical and measurable metrics that will prove the overall program is successful. A good place to start is with your current analytics and measurement program and metrics you can benchmark against. In some cases, new goals may be appropriate. The key thing to remember is that personalization itself is not a goal, rather it is a means to an end. Common goals include:

• Conversion
• Time on task
• Net promoter score (NPS)
• Customer satisfaction 

Touchpoints

Touchpoints are where the personalization happens. As a UX designer, this will be one of your largest areas of responsibility. The touchpoints available to you will depend on how your personalization and associated technology capabilities are instrumented, and should be rooted in improving a user’s experience at a particular point in the journey. Touchpoints can be multi-device (mobile, in-store, website) but also more granular (web banner, web pop-up etc.). Here are some examples:

Channel-level Touchpoints

• Email: Role
• Email: Time of open
• In-store display (JSON endpoint)
• Native app
• Search

Wireframe-level Touchpoints

• Web overlay
• Web alert bar
• Web banner
• Web content block
• Web menu

If you’re designing for web interfaces, for example, you will likely need to include personalized “zones” in your wireframes. The content for these can be presented programmatically in touchpoints based on our next step, contexts and campaigns.

Contexts and Campaigns

Once you’ve outlined some touchpoints, you can consider the actual personalized content a user will receive. Many personalization tools will refer to these as “campaigns” (so, for example, a campaign on a web banner for new visitors to the website). These will programmatically be shown at certain touchpoints to certain user segments, as defined by user data. At this stage, we find it helpful to consider two separate models: a context model and a content model. The context helps you consider the level of engagement of the user at the personalization moment, for example a user casually browsing information vs. doing a deep-dive. Think of it in terms of information retrieval behaviors. The content model can then help you determine what type of personalization to serve based on the context (for example, an “Enrich” campaign that shows related articles may be a suitable supplement to extant content).

Personalization Context Model:

1. Browse
2. Skim
3. Nudge
4. Feast

Personalization Content Model:

1. Alert
2. Make Easier
3. Cross-Sell
4. Enrich

We’ve written extensively about each of these models elsewhere, so if you’d like to read more you can check out Colin’s Personalization Content Model and Jeff’s Personalization Context Model. 

User Segments

User segments can be created prescriptively or adaptively, based on user research (e.g. via rules and logic tied to set user behaviors or via A/B testing). At a minimum you will likely need to consider how to treat the unknown or first-time visitor, the guest or returning visitor for whom you may have a stateful cookie (or equivalent post-cookie identifier), or the authenticated visitor who is logged in. Here are some examples from the personalization pyramid:

• Unknown
• Guest
• Authenticated
• Default
• Referred
• Role
• Cohort
• Unique ID

Actionable Data

Every organization with any digital presence has data. It’s a matter of asking what data you can ethically collect on users, its inherent reliability and value, as to how can you use it (sometimes known as “data activation.”) Fortunately, the tide is turning to first-party data: a recent study by Twilio estimates some 80% of businesses are using at least some type of first-party data to personalize the customer experience. 

First-party data represents multiple advantages on the UX front, including being relatively simple to collect, more likely to be accurate, and less susceptible to the “creep factor” of third-party data. So a key part of your UX strategy should be to determine what the best form of data collection is on your audiences. Here are some examples:

There is a progression of profiling when it comes to recognizing and making decisioning about different audiences and their signals. It tends to move towards more granular constructs about smaller and smaller cohorts of users as time and confidence and data volume grow.

While some combination of implicit / explicit data is generally a prerequisite for any implementation (more commonly referred to as first party and third-party data) ML efforts are typically not cost-effective directly out of the box. This is because a strong data backbone and content repository is a prerequisite for optimization. But these approaches should be considered as part of the larger roadmap and may indeed help accelerate the organization’s overall progress. Typically at this point you will partner with key stakeholders and product owners to design a profiling model. The profiling model includes defining approach to configuring profiles, profile keys, profile cards and pattern cards. A multi-faceted approach to profiling which makes it scalable.

Pulling it Together

While the cards comprise the starting point to an inventory of sorts (we provide blanks for you to tailor your own), a set of potential levers and motivations for the style of personalization activities you aspire to deliver, they are more valuable when thought of in a grouping. 

In assembling a card “hand”, one can begin to trace the entire trajectory from leadership focus down through a strategic and tactical execution. It is also at the heart of the way both co-authors have conducted workshops in assembling a program backlog—which is a fine subject for another article.

In the meantime, what is important to note is that each colored class of card is helpful to survey in understanding the range of choices potentially at your disposal, it is threading through and making concrete decisions about for whom this decisioning will be made: where, when, and how.

Lay Down Your Cards

Any sustainable personalization strategy must consider near, mid and long-term goals. Even with the leading CMS platforms like Sitecore and Adobe or the most exciting composable CMS DXP out there, there is simply no “easy button” wherein a personalization program can be stood up and immediately view meaningful results. That said, there is a common grammar to all personalization activities, just like every sentence has nouns and verbs. These cards attempt to map that territory.

Picture this. You’ve joined a squad at your company that’s designing new product features with an emphasis on automation or AI. Or your company has just implemented a personalization engine. Either way, you’re designing with data. Now what? When it comes to designing for personalization, there are many cautionary tales, no overnight successes, and few guides for the perplexed. 

Between the fantasy of getting it right and the fear of it going wrong—like when we encounter “persofails” in the vein of a company repeatedly imploring everyday consumers to buy additional toilet seats—the personalization gap is real. It’s an especially confounding place to be a digital professional without a map, a compass, or a plan.

For those of you venturing into personalization, there’s no Lonely Planet and few tour guides because effective personalization is so specific to each organization’s talent, technology, and market position. 

But you can ensure that your team has packed its bags sensibly.

There’s a DIY formula to increase your chances for success. At minimum, you’ll defuse your boss’s irrational exuberance. Before the party you’ll need to effectively prepare.

We call it prepersonalization.

Behind the music

Consider Spotify’s DJ feature, which debuted this past year.

We’re used to seeing the polished final result of a personalization feature. Before the year-end award, the making-of backstory, or the behind-the-scenes victory lap, a personalized feature had to be conceived, budgeted, and prioritized. Before any personalization feature goes live in your product or service, it lives amid a backlog of worthy ideas for expressing customer experiences more dynamically.

So how do you know where to place your personalization bets? How do you design consistent interactions that won’t trip up users or—worse—breed mistrust? We’ve found that for many budgeted programs to justify their ongoing investments, they first needed one or more workshops to convene key stakeholders and internal customers of the technology. Make yours count.

​From Big Tech to fledgling startups, we’ve seen the same evolution up close with our clients. In our experiences with working on small and large personalization efforts, a program’s ultimate track record—and its ability to weather tough questions, work steadily toward shared answers, and organize its design and technology efforts—turns on how effectively these prepersonalization activities play out.

Time and again, we’ve seen effective workshops separate future success stories from unsuccessful efforts, saving countless time, resources, and collective well-being in the process.

A personalization practice involves a multiyear effort of testing and feature development. It’s not a switch-flip moment in your tech stack. It’s best managed as a backlog that often evolves through three steps: 

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 (such as Spotify’s DJ experience)

This is why we created our progressive personalization framework and why we’re field-testing an accompanying deck of cards: we believe that there’s a base grammar, a set of “nouns and verbs” that your organization can use to design experiences that are customized, personalized, or automated. You won’t need these cards. But we strongly recommend that you create something similar, whether that might be digital or physical.

Set your kitchen timer

How long does it take to cook up a prepersonalization workshop? The surrounding assessment activities that we recommend including can (and often do) span weeks. For the core workshop, we recommend aiming for two to three days. Here’s a summary of our broader approach along with details on the essential first-day activities.

The full arc of the wider workshop is threefold:

1. Kickstart: This sets the terms of engagement as you focus on the opportunity as well as the readiness and drive of your team and your leadership. .
2. 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.
3. Work your plan: This phase is all about creating a competitive environment for team participants to individually pitch their own pilots that each contain a proof-of-concept project, its business case, and its operating model.

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

Kickstart: Whet your appetite

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

Spark conversation by naming consumer examples 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. We have a catalog of these in the cards. Here’s a list of 142 different interactions to jog your thinking.

This is all about setting the table. What are the possible paths for the practice in your organization? If you want a broader view, here’s a long-form primer and a strategic framework.

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 divide connected experiences into five levels: functions, features, experiences, complete products, and portfolios. Size your own build here. This will help to focus the conversation on the merits of ongoing investment as well as the gap between what you deliver today and what you want to deliver in the future.

Next, have your team plot each idea on the following 2×2 grid, which lays out the four enduring arguments for a personalized experience. This is critical because it emphasizes how personalization can not only help your external customers but also affect your own ways of working. It’s also a reminder (which is why we used the word argument earlier) of the broader effort beyond these tactical interventions.

Each team member should vote on where they see your product or service putting its emphasis. Naturally, you can’t prioritize all of them. The intention here is to flesh out how different departments may view their own upsides to the effort, which can vary from one 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 naming your personalization gap. Is your customer journey well documented? Will data and privacy compliance be too big of a challenge? Do you have content metadata needs that you have to address? (We’re pretty sure that you do: it’s just a matter of recognizing the relative size of that need and its remedy.) In our cards, we’ve noted a number of program risks, including common team dispositions. Our Detractor card, for example, lists six stakeholder behaviors that hinder progress.

Effectively collaborating and managing expectations is critical to your success. Consider the potential barriers to your future progress. Press the participants to name specific steps to overcome or mitigate those barriers in your organization. As studies have shown, personalization efforts face many common barriers.

At this point, you’ve hopefully discussed sample interactions, emphasized a key area of benefit, and flagged key gaps? Good—you’re ready to continue.

Hit that test kitchen

Next, let’s look at what you’ll need to bring your personalization recipes to life. Personalization engines, which are robust software suites for automating and expressing dynamic content, can intimidate new customers. Their capabilities are sweeping and powerful, and they present broad options for how your organization can conduct its activities. This presents the question: Where do you begin when you’re configuring a connected experience?

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

The ultimate menu of the prioritized backlog will come together over the course of the workshop. 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 come from recipes, and those recipes have set ingredients.

Verify your ingredients

Like a good product manager, you’ll make sure—andyou’ll validate with the right stakeholders present—that you have all the ingredients on hand to cook up your desired interaction (or that you can work out what needs to be added to your pantry). 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. 

This isn’t just about discovering requirements. Documenting your personalizations as a series of if-then statements lets the team: 

1. compare findings toward a unified approach for developing features, not unlike when artists paint with the same palette; 
2. specify a consistent set of interactions that users find uniform or familiar; 
3. and develop parity across performance measurements and key performance indicators too. 

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.

Compose your recipe

What ingredients are important to you? Think of a who-what-when-why construct: 

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

We first developed these cards and card categories five years ago. We regularly play-test their fit with conference audiences and clients. And we still encounter new possibilities. But they all follow an underlying who-what-when-why logic.

Here are three examples for a subscription-based reading app, which you can generally follow along with right to left in the cards in the accompanying photo below. 

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: When there’s a newly registered user, an email is generated to call out the breadth of the content catalog and to make them a happier subscriber.
3. Winback automation: 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.

A useful preworkshop activity may be to think through a first draft of what these cards might be for your organization, although we’ve also found that this process sometimes flows best through cocreating the recipes themselves. 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.

You can think of the later stages of the workshop as moving from recipes toward a cookbook in focus—like a more nuanced customer-journey mapping. 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.

Better kitchens require better architecture

Simplifying a customer experience is a complicated effort for those who are inside delivering it. Beware anyone who says otherwise. With that being said,  “Complicated problems can be hard to solve, but they are addressable with rules and recipes.”

When personalization becomes a laugh line, it’s because a team is overfitting: they aren’t designing with their best data. Like a sparse pantry, every organization has metadata debt to go along with its technical debt, and this creates a drag on personalization effectiveness. Your AI’s output quality, for example, is indeed limited 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 definitely stand the heat…

Personalization technology opens a doorway into a confounding ocean of possible designs. Only a disciplined and highly collaborative approach will bring about the necessary focus and intention to succeed. So banish the dream kitchen. Instead, hit the test kitchen to save time, preserve job satisfaction and security, and safely dispense with the fanciful ideas that originate upstairs of the doers in your organization. There are meals to serve and mouths to feed.

This workshop framework gives you a fighting shot at lasting success as well as sound beginnings. Wiring up your information layer isn’t an overnight affair. But if you use the same cookbook and shared recipes, you’ll have solid footing for success. We designed these activities to make your organization’s needs concrete and clear, long before the hazards pile up.

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