The mobile-first design methodology is great—it focuses on what really matters to the user, it’s well-practiced, and it’s been a common design pattern for years. So developing your CSS mobile-first should also be great, 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?

On your own projects, mobile-first CSS may yet be the best tool for the job, but first you need to evaluate just how appropriate it is in light of the visual design and user interactions you’re working on. To help you get started, here’s how I go about tackling the factors you need to watch for, and I’ll discuss some alternate solutions if mobile-first doesn’t seem to suit your project.

Advantages of mobile-first

Some of the things to like with mobile-first CSS development—and why it’s been the de facto development methodology for so long—make a lot of sense:

Development hierarchy. One thing you undoubtedly get from mobile-first is a nice development hierarchy—you just focus on the mobile view and get developing. 

Tried and tested. It’s a tried and tested methodology that’s worked for years for a reason: it solves a problem really well.

Prioritizes the mobile view. The mobile view is the simplest and arguably the most important, as it encompasses all the key user journeys, and often accounts for a higher proportion of user visits (depending on the project). 

Prevents desktop-centric development. As development is done using desktop computers, it can be tempting to initially focus on the desktop view. But thinking about mobile from the start prevents us from getting stuck later on; no one wants to spend their time retrofitting a desktop-centric site to work on mobile devices!

Disadvantages of mobile-first

Setting style declarations and then overwriting them at higher breakpoints can lead to undesirable ramifications:

More complexity. The farther up the breakpoint hierarchy you go, the more unnecessary code you inherit from lower breakpoints. 

Higher CSS specificity. Styles that have been reverted to their browser default value in a class name declaration now have a higher specificity. This can be a headache on large projects when you want to keep the CSS selectors as simple as possible.

Requires more regression testing. Changes to the CSS at a lower view (like adding a new style) requires all higher breakpoints to be regression tested.

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 problem of property value overrides

There is nothing inherently wrong with overwriting values; CSS was designed to do just that. Still, inheriting incorrect values is unhelpful and can be burdensome and inefficient. It can also lead to increased style specificity when you have to overwrite styles to reset them back to their defaults, something that may cause issues later on, especially if you are using a combination of bespoke CSS and utility classes. We won’t be able to use a utility class for a style that has been reset with a higher specificity.

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. But if it looks like Grid would be much better for large screens and Flexbox for mobile, these can both be done entirely independently when the CSS is put into closed media query ranges. Also, developing simultaneously requires you to have a good understanding of any given component in all breakpoints up front. This can help surface issues in the design earlier in the development process. We don’t want to get stuck down a rabbit hole building a complex component for mobile, and then get the designs for desktop and find they are equally 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 are comfortable with focusing on the mobile view, have a good understanding of the requirements for other breakpoints, and prefer to work on one device at a time, then by all means stick with the classic development order. The important thing is to identify common styles and exceptions so you can put them in the relevant stylesheet—a sort of manual tree-shaking process! 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.

Bundling versus separating the CSS

Back in the day, keeping the number of requests to a minimum was very important due to the browser’s limit of concurrent requests (typically around six). 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. This allows us to separate the CSS into multiple files by media query. The clear benefit of this is the browser can now request the CSS it currently needs with a higher priority than the CSS it doesn’t. This is more performant and can reduce the overall time page rendering is blocked.

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 make sure 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 waiting for? There is excellent user support for HTTP/2.

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.

In the following example of a website visited on a mobile breakpoint, we can see the mobile and default CSS are loaded with “Highest” priority, as they are currently needed 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. 

With bundled CSS, the browser will have to download the CSS file and parse it before rendering can start.

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. 

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

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 uptake of mobile-first CSS was a really important milestone in web development; it has helped front-end developers focus on mobile web applications, rather than developing sites on desktop and then 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 noticing small simplifications in my own CSS, as well as other developers’, and that testing and maintenance work is also a bit more simplified and productive. 

In general, simplifying CSS rule creation whenever we can is ultimately a cleaner approach than going 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.

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.

Humility, a designer’s essential value—that has a nice ring to it. What about humility, an office manager’s essential value? Or a dentist’s? Or a librarian’s? They all sound great. When humility is our guiding light, the path is always open for fulfillment, evolution, connection, and engagement. In this chapter, we’re going to talk about why.

That said, this is a book for designers, and to that end, I’d like to start with a story—well, a journey, really. It’s a personal one, and I’m going to make myself a bit vulnerable along the way. I call it:

The Tale of Justin’s Preposterous Pate

When I was coming out of art school, a long-haired, goateed neophyte, print was a known quantity to me; design on the web, however, was rife with complexities to navigate and discover, a problem to be solved. Though I had been formally trained in graphic design, typography, and layout, what fascinated me was how these traditional skills might be applied to a fledgling digital landscape. This theme would ultimately shape the rest of my career.

So rather than graduate and go into print like many of my friends, I devoured HTML and JavaScript books into the wee hours of the morning and taught myself how to code during my senior year. I wanted—nay, needed—to better understand the underlying implications of what my design decisions would mean once rendered in a browser.

The late ’90s and early 2000s were the so-called “Wild West” of web design. Designers at the time were all figuring out how to apply design and visual communication to the digital landscape. What were the rules? How could we break them and still engage, entertain, and convey information? At a more macro level, how could my values, inclusive of humility, respect, and connection, align in tandem with that? I was hungry to find out.

Though I’m talking about a different era, those are timeless considerations between non-career interactions and the world of design. What are your core passions, or values, that transcend medium? It’s essentially the same concept we discussed earlier on the direct parallels between what fulfills you, agnostic of the tangible or digital realms; the core themes are all the same.

First within tables, animated GIFs, Flash, then with Web Standards, divs, and CSS, there was personality, raw unbridled creativity, and unique means of presentment that often defied any semblance of a visible grid. Splash screens and “browser requirement” pages aplenty. Usability and accessibility were typically victims of such a creation, but such paramount facets of any digital design were largely (and, in hindsight, unfairly) disregarded at the expense of experimentation.

For example, this iteration of my personal portfolio site (“the pseudoroom”) from that era was experimental, if not a bit heavy- handed, in the visual communication of the concept of a living sketchbook. Very skeuomorphic. I collaborated with fellow designer and dear friend Marc Clancy (now a co-founder of the creative project organizing app Milanote) on this one, where we’d first sketch and then pass a Photoshop file back and forth to trick things out and play with varied user interactions. Then, I’d break it down and code it into a digital layout.

Along with design folio pieces, the site also offered free downloads for Mac OS customizations: desktop wallpapers that were effectively design experimentation, custom-designed typefaces, and desktop icons.

From around the same time, GUI Galaxy was a design, pixel art, and Mac-centric news portal some graphic designer friends and I conceived, designed, developed, and deployed.

Design news portals were incredibly popular during this period, featuring (what would now be considered) Tweet-size, small-format snippets of pertinent news from the categories I previously mentioned. If you took Twitter, curated it to a few categories, and wrapped it in a custom-branded experience, you’d have a design news portal from the late 90s / early 2000s.

We as designers had evolved and created a bandwidth-sensitive, web standards award-winning, much more accessibility-conscious website. Still ripe with experimentation, yet more mindful of equitable engagement. You can see a couple of content panes here, noting general news (tech, design) and Mac-centric news below. We also offered many of the custom downloads I cited before as present on my folio site but branded and themed to GUI Galaxy.

The site’s backbone was a homegrown CMS, with the presentation layer consisting of global design + illustration + news author collaboration. And the collaboration effort here, in addition to experimentation on a ‘brand’ and content delivery, was hitting my core. We were designing something bigger than any single one of us and connecting with a global audience.

Collaboration and connection transcend medium in their impact, immensely fulfilling me as a designer.

Now, why am I taking you down this trip of design memory lane? Two reasons.

First, there’s a reason for the nostalgia for that design era (the “Wild West” era, as I called it earlier): the inherent exploration, personality, and creativity that saturated many design portals and personal portfolio sites. Ultra-finely detailed pixel art UI, custom illustration, bespoke vector graphics, all underpinned by a strong design community.

Today’s web design has been in a period of stagnation. I suspect there’s a strong chance you’ve seen a site whose structure looks something like this: a hero image / banner with text overlaid, perhaps with a lovely rotating carousel of images (laying the snark on heavy there), a call to action, and three columns of sub-content directly beneath. Maybe an icon library is employed with selections that vaguely relate to their respective content.

Design, as it’s applied to the digital landscape, is in dire need of thoughtful layout, typography, and visual engagement that goes hand-in-hand with all the modern considerations we now know are paramount: usability. Accessibility. Load times and bandwidth- sensitive content delivery. A responsive presentation that meets human beings wherever they’re engaging from. We must be mindful of, and respectful toward, those concerns—but not at the expense of creativity of visual communication or via replicating cookie-cutter layouts.

Pixel Problems

Websites during this period were often designed and built on Macs whose OS and desktops looked something like this. This is Mac OS 7.5, but 8 and 9 weren’t that different.

Desktop icons fascinated me: how could any single one, at any given point, stand out to get my attention? In this example, the user’s desktop is tidy, but think of a more realistic example with icon pandemonium. Or, say an icon was part of a larger system grouping (fonts, extensions, control panels)—how did it also maintain cohesion amongst a group?

These were 32 x 32 pixel creations, utilizing a 256-color palette, designed pixel-by-pixel as mini mosaics. To me, this was the embodiment of digital visual communication under such ridiculous constraints. And often, ridiculous restrictions can yield the purification of concept and theme.

So I began to research and do my homework. I was a student of this new medium, hungry to dissect, process, discover, and make it my own.

Expanding upon the notion of exploration, I wanted to see how I could push the limits of a 32×32 pixel grid with that 256-color palette. Those ridiculous constraints forced a clarity of concept and presentation that I found incredibly appealing. The digital gauntlet had been tossed, and that challenge fueled me. And so, in my dorm room into the wee hours of the morning, I toiled away, bringing conceptual sketches into mini mosaic fruition.

These are some of my creations, utilizing the only tool available at the time to create icons called ResEdit. ResEdit was a clunky, built-in Mac OS utility not really made for exactly what we were using it for. At the core of all of this work: Research. Challenge. Problem- solving. Again, these core connection-based values are agnostic of medium.

There’s one more design portal I want to talk about, which also serves as the second reason for my story to bring this all together.

This is K10k, short for Kaliber 1000. K10k was founded in 1998 by Michael Schmidt and Toke Nygaard, and was the design news portal on the web during this period. With its pixel art-fueled presentation, ultra-focused care given to every facet and detail, and with many of the more influential designers of the time who were invited to be news authors on the site, well… it was the place to be, my friend. With respect where respect is due, GUI Galaxy’s concept was inspired by what these folks were doing.

For my part, the combination of my web design work and pixel art exploration began to get me some notoriety in the design scene. Eventually, K10k noticed and added me as one of their very select group of news authors to contribute content to the site.

Amongst my personal work and side projects—and now with this inclusion—in the design community, this put me on the map. My design work also began to be published in various printed collections, in magazines domestically and overseas, and featured on other design news portals. With that degree of success while in my early twenties, something else happened:

I evolved—devolved, really—into a colossal asshole (and in just about a year out of art school, no less). The press and the praise became what fulfilled me, and they went straight to my head. They inflated my ego. I actually felt somewhat superior to my fellow designers.

The casualties? My design stagnated. Its evolution—my evolution— stagnated.

I felt so supremely confident in my abilities that I effectively stopped researching and discovering. When previously sketching concepts or iterating ideas in lead was my automatic step one, I instead leaped right into Photoshop. I drew my inspiration from the smallest of sources (and with blinders on). Any critique of my work from my peers was often vehemently dismissed. The most tragic loss: I had lost touch with my values.

My ego almost cost me some of my friendships and burgeoning professional relationships. I was toxic in talking about design and in collaboration. But thankfully, those same friends gave me a priceless gift: candor. They called me out on my unhealthy behavior.

Admittedly, it was a gift I initially did not accept but ultimately was able to deeply reflect upon. I was soon able to accept, and process, and course correct. The realization laid me low, but the re-awakening was essential. I let go of the “reward” of adulation and re-centered upon what stoked the fire for me in art school. Most importantly: I got back to my core values.

Always Students

Following that short-term regression, I was able to push forward in my personal design and career. And I could self-reflect as I got older to facilitate further growth and course correction as needed.

As an example, let’s talk about the Large Hadron Collider. The LHC was designed “to help answer some of the fundamental open questions in physics, which concern the basic laws governing the interactions and forces among the elementary objects, the deep structure of space and time, and in particular the interrelation between quantum mechanics and general relativity.” Thanks, Wikipedia.

Around fifteen years ago, in one of my earlier professional roles, I designed the interface for the application that generated the LHC’s particle collision diagrams. These diagrams are the rendering of what’s actually happening inside the Collider during any given particle collision event and are often considered works of art unto themselves.

Designing the interface for this application was a fascinating process for me, in that I worked with Fermilab physicists to understand what the application was trying to achieve, but also how the physicists themselves would be using it. To that end, in this role,

I cut my teeth on usability testing, working with the Fermilab team to iterate and improve the interface. How they spoke and what they spoke about was like an alien language to me. And by making myself humble and working under the mindset that I was but a student, I made myself available to be a part of their world to generate that vital connection.

I also had my first ethnographic observation experience: going to the Fermilab location and observing how the physicists used the tool in their actual environment, on their actual terminals. For example, one takeaway was that due to the level of ambient light-driven contrast within the facility, the data columns ended up using white text on a dark gray background instead of black text-on-white. This enabled them to pore over reams of data during the day and ease their eye strain. And Fermilab and CERN are government entities with rigorous accessibility standards, so my knowledge in that realm also grew. The barrier-free design was another essential form of connection.

So to those core drivers of my visual problem-solving soul and ultimate fulfillment: discovery, exposure to new media, observation, human connection, and evolution. What opened the door for those values was me checking my ego before I walked through it.

An evergreen willingness to listen, learn, understand, grow, evolve, and connect yields our best work. In particular, I want to focus on the words ‘grow’ and ‘evolve’ in that statement. If we are always students of our craft, we are also continually making ourselves available to evolve. Yes, we have years of applicable design study under our belt. Or the focused lab sessions from a UX bootcamp. Or the monogrammed portfolio of our work. Or, ultimately, decades of a career behind us.

But all that said: experience does not equal “expert.”

As soon as we close our minds via an inner monologue of ‘knowing it all’ or branding ourselves a “#thoughtleader” on social media, the designer we are is our final form. The designer we can be will never exist.

I am a creative. What I do is alchemy. It is a mystery. I do not so much do it, as let it be done through me.

I am a creative. Not all creative people like this label. Not all see themselves this way. Some creative people see science in what they do. That is their truth, and I respect it. Maybe I even envy them, a little. But my process is different—my being is different.

Apologizing and qualifying in advance is a distraction. That’s what my brain does to sabotage me. I set it aside for now. I can come back later to apologize and qualify. After I’ve said what I came to say. Which is hard enough. 

Except when it is easy and flows like a river of wine.

Sometimes it does come that way. Sometimes what I need to create comes in an instant. I have learned not to say it at that moment, because if you admit that sometimes the idea just comes and it is the best idea and you know it is the best idea, they think you don’t work hard enough.

Sometimes I work and work and work until the idea comes. Sometimes it comes instantly and I don’t tell anyone for three days. Sometimes I’m so excited by the idea that came instantly that I blurt it out, can’t help myself. Like a boy who found a prize in his Cracker Jacks. Sometimes I get away with this. Sometimes other people agree: yes, that is the best idea. Most times they don’t and I regret having  given way to enthusiasm. 

Enthusiasm is best saved for the meeting where it will make a difference. Not the casual get-together that precedes that meeting by two other meetings. Nobody knows why we have all these meetings. We keep saying we’re doing away with them, but then just finding other ways to have them. Sometimes they are even good. But other times they are a distraction from the actual work. The proportion between when meetings are useful, and when they are a pitiful distraction, varies, depending on what you do and where you do it. And who you are and how you do it. Again I digress. I am a creative. That is the theme.

Sometimes many hours of hard and patient work produce something that is barely serviceable. Sometimes I have to accept that and move on to the next project.

Don’t ask about process. I am a creative.

I am a creative. I don’t control my dreams. And I don’t control my best ideas.

I can hammer away, surround myself with facts or images, and sometimes that works. I can go for a walk, and sometimes that works. I can be making dinner and there’s a Eureka having nothing to do with sizzling oil and bubbling pots. Often I know what to do the instant I wake up. And then, almost as often, as I become conscious and part of the world again, the idea that would have saved me turns to vanishing dust in a mindless wind of oblivion. For creativity, I believe, comes from that other world. The one we enter in dreams, and perhaps, before birth and after death. But that’s for poets to wonder, and I am not a poet. I am a creative. And it’s for theologians to mass armies about in their creative world that they insist is real. But that is another digression. And a depressing one. Maybe on a much more important topic than whether I am a creative or not. But still a digression from what I came here to say.

Sometimes the process is avoidance. And agony. You know the cliché about the tortured artist? It’s true, even when the artist (and let’s put that noun in quotes) is trying to write a soft drink jingle, a callback in a tired sitcom, a budget request.

Some people who hate being called creative may be closeted creatives, but that’s between them and their gods. No offense meant. Your truth is true, too. But mine is for me. 

Creatives recognize creatives.

Creatives recognize creatives like queers recognize queers, like real rappers recognize real rappers, like cons know cons. Creatives feel massive respect for creatives. We love, honor, emulate, and practically deify the great ones. To deify any human is, of course, a tragic mistake. We have been warned. We know better. We know people are just people. They squabble, they are lonely, they regret their most important decisions, they are poor and hungry, they can be cruel, they can be just as stupid as we can, because, like us, they are clay. But. But. But they make this amazing thing. They birth something that did not exist before them, and could not exist without them. They are the mothers of ideas. And I suppose, since it’s just lying there, I have to add that they are the mothers of invention. Ba dum bum! OK, that’s done. Continue.

Creatives belittle our own small achievements, because we compare them to those of the great ones. Beautiful animation! Well, I’m no Miyazaki. Now THAT is greatness. That is greatness straight from the mind of God. This half-starved little thing that I made? It more or less fell off the back of the turnip truck. And the turnips weren’t even fresh.

Creatives knows that, at best, they are Salieri. Even the creatives who are Mozart believe that. 

I am a creative. I haven’t worked in advertising in 30 years, but in my nightmares, it’s my former creative directors who judge me. And they are right to do so. I am too lazy, too facile, and when it really counts, my mind goes blank. There is no pill for creative dysfunction.

I am a creative. Every deadline I make is an adventure that makes Indiana Jones look like a pensioner snoring in a deck chair. The longer I remain a creative, the faster I am when I do my work and the longer I brood and walk in circles and stare blankly before I do that work. 

I am still 10 times faster than people who are not creative, or people who have only been creative a short while, or people who have only been professionally creative a short while. It’s just that, before I work 10 times as fast as they do, I spend twice as long as they do putting the work off. I am that confident in my ability to do a great job when I put my mind to it. I am that addicted to the adrenaline rush of postponement. I am still that afraid of the jump.

I am not an artist.

I am a creative. Not an artist. Though I dreamed, as a lad, of someday being that. Some of us belittle our gifts and dislike ourselves because we are not Michelangelos and Warhols. That is narcissism—but at least we aren’t in politics.

I am a creative. Though I believe in reason and science, I decide by intuition and impulse. And live with what follows—the catastrophes as well as the triumphs. 

I am a creative. Every word I’ve said here will annoy other creatives, who see things differently. Ask two creatives a question, get three opinions. Our disagreement, our passion about it, and our commitment to our own truth are, at least to me, the proofs that we are creatives, no matter how we may feel about it.

I am a creative. I lament my lack of taste in the areas about which I know very little, which is to say almost all areas of human knowledge. And I trust my taste above all other things in the areas closest to my heart, or perhaps, more accurately, to my obsessions. Without my obsessions, I would probably have to spend my time looking life in the eye, and almost none of us can do that for long. Not honestly. Not really. Because much in life, if you really look at it, is unbearable.

I am a creative. I believe, as a parent believes, that when I am gone, some small good part of me will carry on in the mind of at least one other person.

Working saves me from worrying about work.

I am a creative. I live in dread of my small gift suddenly going away.

I am a creative. I am too busy making the next thing to spend too much time deeply considering that almost nothing I make will come anywhere near the greatness I comically aspire to.

I am a creative. I believe in the ultimate mystery of process. I believe in it so much, I am even fool enough to publish an essay I dictated into a tiny machine and didn’t take time to review or revise. I won’t do this often, I promise. But I did it just now, because, as afraid as I might be of your seeing through my pitiful gestures toward the beautiful, I was even more afraid of forgetting what I came to say. 

There. I think I’ve said it. 

In reading Joe Dolson’s recent piece on the intersection of AI and accessibility, I absolutely appreciated the skepticism that he has for AI in general as well as for the ways that many have been using it. In fact, I’m very skeptical of AI myself, despite my role at Microsoft as an accessibility innovation strategist who helps run the AI for Accessibility grant program. As with any tool, AI can be used in very constructive, inclusive, and accessible ways; and it can also be used in destructive, exclusive, and harmful ones. And there are a ton of uses somewhere in the mediocre middle as well.

I’d like you to consider this a “yes… and” piece to complement Joe’s post. I’m not trying to refute any of what he’s saying but rather provide some visibility to projects and opportunities where AI can make meaningful differences for people with disabilities. To be clear, I’m not saying that there aren’t real risks or pressing issues with AI that need to be addressed—there are, and we’ve needed to address them, like, yesterday—but I want to take a little time to talk about what’s possible in hopes that we’ll get there one day.

Alternative text

Joe’s piece spends a lot of time talking about computer-vision models generating alternative text. He highlights a ton of valid issues with the current state of things. And while computer-vision models continue to improve in the quality and richness of detail in their descriptions, their results aren’t great. As he rightly points out, the current state of image analysis is pretty poor—especially for certain image types—in large part because current AI systems examine images in isolation rather than within the contexts that they’re in (which is a consequence of having separate “foundation” models for text analysis and image analysis). Today’s models aren’t trained to distinguish between images that are contextually relevant (that should probably have descriptions) and those that are purely decorative (which might not need a description) either. Still, I still think there’s potential in this space.

As Joe mentions, human-in-the-loop authoring of alt text should absolutely be a thing. And if AI can pop in to offer a starting point for alt text—even if that starting point might be a prompt saying What is this BS? That’s not right at all… Let me try to offer a starting point—I think that’s a win.

Taking things a step further, if we can specifically train a model to analyze image usage in context, it could help us more quickly identify which images are likely to be decorative and which ones likely require a description. That will help reinforce which contexts call for image descriptions and it’ll improve authors’ efficiency toward making their pages more accessible.

While complex images—like graphs and charts—are challenging to describe in any sort of succinct way (even for humans), the image example shared in the GPT4 announcement points to an interesting opportunity as well. Let’s suppose that you came across a chart whose description was simply the title of the chart and the kind of visualization it was, such as: Pie chart comparing smartphone usage to feature phone usage among US households making under $30,000 a year. (That would be a pretty awful alt text for a chart since that would tend to leave many questions about the data unanswered, but then again, let’s suppose that that was the description that was in place.) If your browser knew that that image was a pie chart (because an onboard model concluded this), imagine a world where users could ask questions like these about the graphic:

• Do more people use smartphones or feature phones?
• How many more?
• Is there a group of people that don’t fall into either of these buckets?
• How many is that?

Setting aside the realities of large language model (LLM) hallucinations—where a model just makes up plausible-sounding “facts”—for a moment, the opportunity to learn more about images and data in this way could be revolutionary for blind and low-vision folks as well as for people with various forms of color blindness, cognitive disabilities, and so on. It could also be useful in educational contexts to help people who can see these charts, as is, to understand the data in the charts.

Taking things a step further: What if you could ask your browser to simplify a complex chart? What if you could ask it to isolate a single line on a line graph? What if you could ask your browser to transpose the colors of the different lines to work better for form of color blindness you have? What if you could ask it to swap colors for patterns? Given these tools’ chat-based interfaces and our existing ability to manipulate images in today’s AI tools, that seems like a possibility.

Now imagine a purpose-built model that could extract the information from that chart and convert it to another format. For example, perhaps it could turn that pie chart (or better yet, a series of pie charts) into more accessible (and useful) formats, like spreadsheets. That would be amazing!

Matching algorithms

Safiya Umoja Noble absolutely hit the nail on the head when she titled her book Algorithms of Oppression. While her book was focused on the ways that search engines reinforce racism, I think that it’s equally true that all computer models have the potential to amplify conflict, bias, and intolerance. Whether it’s Twitter always showing you the latest tweet from a bored billionaire, YouTube sending us into a Q-hole, or Instagram warping our ideas of what natural bodies look like, we know that poorly authored and maintained algorithms are incredibly harmful. A lot of this stems from a lack of diversity among the people who shape and build them. When these platforms are built with inclusively baked in, however, there’s real potential for algorithm development to help people with disabilities.

Take Mentra, for example. They are an employment network for neurodivergent people. They use an algorithm to match job seekers with potential employers based on over 75 data points. On the job-seeker side of things, it considers each candidate’s strengths, their necessary and preferred workplace accommodations, environmental sensitivities, and so on. On the employer side, it considers each work environment, communication factors related to each job, and the like. As a company run by neurodivergent folks, Mentra made the decision to flip the script when it came to typical employment sites. They use their algorithm to propose available candidates to companies, who can then connect with job seekers that they are interested in; reducing the emotional and physical labor on the job-seeker side of things.

When more people with disabilities are involved in the creation of algorithms, that can reduce the chances that these algorithms will inflict harm on their communities. That’s why diverse teams are so important.

Imagine that a social media company’s recommendation engine was tuned to analyze who you’re following and if it was tuned to prioritize follow recommendations for people who talked about similar things but who were different in some key ways from your existing sphere of influence. For example, if you were to follow a bunch of nondisabled white male academics who talk about AI, it could suggest that you follow academics who are disabled or aren’t white or aren’t male who also talk about AI. If you took its recommendations, perhaps you’d get a more holistic and nuanced understanding of what’s happening in the AI field. These same systems should also use their understanding of biases about particular communities—including, for instance, the disability community—to make sure that they aren’t recommending any of their users follow accounts that perpetuate biases against (or, worse, spewing hate toward) those groups.

Other ways that AI can helps people with disabilities

If I weren’t trying to put this together between other tasks, I’m sure that I could go on and on, providing all kinds of examples of how AI could be used to help people with disabilities, but I’m going to make this last section into a bit of a lightning round. In no particular order:

• Voice preservation. You may have seen the VALL-E paper or Apple’s Global Accessibility Awareness Day announcement or you may be familiar with the voice-preservation offerings from Microsoft, Acapela, or others. It’s possible to train an AI model to replicate your voice, which can be a tremendous boon for people who have ALS (Lou Gehrig’s disease) or motor-neuron disease or other medical conditions that can lead to an inability to talk. This is, of course, the same tech that can also be used to create audio deepfakes, so it’s something that we need to approach responsibly, but the tech has truly transformative potential.
• Voice recognition. Researchers like those in the Speech Accessibility Project are paying people with disabilities for their help in collecting recordings of people with atypical speech. As I type, they are actively recruiting people with Parkinson’s and related conditions, and they have plans to expand this to other conditions as the project progresses. This research will result in more inclusive data sets that will let more people with disabilities use voice assistants, dictation software, and voice-response services as well as control their computers and other devices more easily, using only their voice.
• Text transformation. The current generation of LLMs is quite capable of adjusting existing text content without injecting hallucinations. This is hugely empowering for people with cognitive disabilities who may benefit from text summaries or simplified versions of text or even text that’s prepped for Bionic Reading.

The importance of diverse teams and data

We need to recognize that our differences matter. Our lived experiences are influenced by the intersections of the identities that we exist in. These lived experiences—with all their complexities (and joys and pain)—are valuable inputs to the software, services, and societies that we shape. Our differences need to be represented in the data that we use to train new models, and the folks who contribute that valuable information need to be compensated for sharing it with us. Inclusive data sets yield more robust models that foster more equitable outcomes.

Want a model that doesn’t demean or patronize or objectify people with disabilities? Make sure that you have content about disabilities that’s authored by people with a range of disabilities, and make sure that that’s well represented in the training data.

Want a model that doesn’t use ableist language? You may be able to use existing data sets to build a filter that can intercept and remediate ableist language before it reaches readers. That being said, when it comes to sensitivity reading, AI models won’t be replacing human copy editors anytime soon. 

Want a coding copilot that gives you accessible recommendations from the jump? Train it on code that you know to be accessible.

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

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

I offer a single bit of advice to friends and family when they become new parents: When you start to think that you’ve got everything figured out, everything will change. Just as you start to get the hang of feedings, diapers, and regular naps, it’s time for solid food, potty training, and overnight sleeping. When you figure those out, it’s time for preschool and rare naps. The cycle goes on and on.

The same applies for those of us working in design and development these days. Having worked on the web for almost three decades at this point, I’ve seen the regular wax and wane of ideas, techniques, and technologies. Each time that we as developers and designers get into a regular rhythm, some new idea or technology comes along to shake things up and remake our world.

How we got here

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

The birth of web standards

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

Server-side languages like PHP, Java, and .NET overtook Perl as the predominant back-end processors, and the cgi-bin was tossed in the trash bin. With these better server-side tools came the first era of web applications, starting with content-management systems (particularly in the blogging space with tools like Blogger, Grey Matter, Movable Type, and WordPress). In the mid-2000s, AJAX opened doors for asynchronous interaction between the front end and back end. Suddenly, pages could update their content without needing to reload. A crop of JavaScript frameworks like Prototype, YUI, and jQuery arose to help developers build more reliable client-side interaction across browsers that had wildly varying levels of standards support. Techniques like image replacement let crafty designers and developers display fonts of their choosing. And technologies like Flash made it possible to add animations, games, and even more interactivity.

These new technologies, standards, and techniques reinvigorated the industry in many ways. Web design flourished as designers and developers explored more diverse styles and layouts. But we still relied on tons of hacks. Early CSS was a huge improvement over table-based layouts when it came to basic layout and text styling, but its limitations at the time meant that designers and developers still relied heavily on images for complex shapes (such as rounded or angled corners) and tiled backgrounds for the appearance of full-length columns (among other hacks). Complicated layouts required all manner of nested floats or absolute positioning (or both). Flash and image replacement for custom fonts was a great start toward varying the typefaces from the big five, but both hacks introduced accessibility and performance problems. And JavaScript libraries made it easy for anyone to add a dash of interaction to pages, although at the cost of doubling or even quadrupling the download size of simple websites.

The web as software platform

The symbiosis between the front end and back end continued to improve, and that led to the current era of modern web applications. Between expanded server-side programming languages (which kept growing to include Ruby, Python, Go, and others) and newer front-end tools like React, Vue, and Angular, we could build fully capable software on the web. Alongside these tools came others, including collaborative version control, build automation, and shared package libraries. What was once primarily an environment for linked documents became a realm of infinite possibilities.

At the same time, mobile devices became more capable, and they gave us internet access in our pockets. Mobile apps and responsive design opened up opportunities for new interactions anywhere and any time.

This combination of capable mobile devices and powerful development tools contributed to the waxing of social media and other centralized tools for people to connect and consume. As it became easier and more common to connect with others directly on Twitter, Facebook, and even Slack, the desire for hosted personal sites waned. Social media offered connections on a global scale, with both the good and bad that that entails.

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

Where we are now

In the last couple of years, it’s felt like we’ve begun to reach another major inflection point. As social-media platforms fracture and wane, there’s been a growing interest in owning our own content again. There are many different ways to make a website, from the tried-and-true classic of hosting plain HTML files to static site generators to content management systems of all flavors. The fracturing of social media also comes with a cost: we lose crucial infrastructure for discovery and connection. Webmentions, RSS, ActivityPub, and other tools of the IndieWeb can help with this, but they’re still relatively underimplemented and hard to use for the less nerdy. We can build amazing personal websites and add to them regularly, but without discovery and connection, it can sometimes feel like we may as well be shouting into the void.

Browser support for CSS, JavaScript, and other standards like web components has accelerated, especially through efforts like Interop. New technologies gain support across the board in a fraction of the time that they used to. I often learn about a new feature and check its browser support only to find that its coverage is already above 80 percent. Nowadays, the barrier to using newer techniques often isn’t browser support but simply the limits of how quickly designers and developers can learn what’s available and how to adopt it.

Today, with a few commands and a couple of lines of code, we can prototype almost any idea. All the tools that we now have available make it easier than ever to start something new. But the upfront cost that these frameworks may save in initial delivery eventually comes due as upgrading and maintaining them becomes a part of our technical debt.

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

Where do we go from here?

Today’s hacks help to shape tomorrow’s standards. And there’s nothing inherently wrong with embracing hacks—for now—to move the present forward. Problems only arise when we’re unwilling to admit that they’re hacks or we hesitate to replace them. So what can we do to create the future we want for the web?

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

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

Design with care. Whether your craft is code, pixels, or processes, consider the impacts of each decision. The convenience of many a modern tool comes at the cost of not always understanding the underlying decisions that have led to its design and not always considering the impact that those decisions can have. Rather than rushing headlong to “move fast and break things,” use the time saved by modern tools to consider more carefully and design with deliberation.

Always be learning. If you’re always learning, you’re also growing. Sometimes it may be hard to pinpoint what’s worth learning and what’s just today’s hack. You might end up focusing on something that won’t matter next year, even if you were to focus solely on learning standards. (Remember XHTML?) But constant learning opens up new connections in your brain, and the hacks that you learn one day may help to inform different experiments another day.

Play, experiment, and be weird! This web that we’ve built is the ultimate experiment. It’s the single largest human endeavor in history, and yet each of us can create our own pocket within it. Be courageous and try new things. Build a playground for ideas. Make goofy experiments in your own mad science lab. Start your own small business. There has never been a more empowering place to be creative, take risks, and explore what we’re capable of.

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

Go forth and make

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

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.

Ever since I was a boy, I’ve been fascinated with movies. I loved the characters and the excitement—but most of all the stories. I wanted to be an actor. And I believed that I’d get to do the things that Indiana Jones did and go on exciting adventures. I even dreamed up ideas for movies that my friends and I could make and star in. But they never went any further. I did, however, end up working in user experience (UX). Now, I realize that there’s an element of theater to UX—I hadn’t really considered it before, but user research is storytelling. And to get the most out of user research, you need to tell a good story where you bring stakeholders—the product team and decision makers—along and get them interested in learning more.

Think of your favorite movie. More than likely it follows a three-act structure that’s commonly seen in storytelling: the setup, the conflict, and the resolution. The first act shows what exists today, and it helps you get to know the characters and the challenges and problems that they face. Act two introduces the conflict, where the action is. Here, problems grow or get worse. And the third and final act is the resolution. This is where the issues are resolved and the characters learn and change. I believe that this structure is also a great way to think about user research, and I think that it can be especially helpful in explaining user research to others.

Use storytelling as a structure to do research

It’s sad to say, but many have come to see research as being expendable. If budgets or timelines are tight, research tends to be one of the first things to go. Instead of investing in research, some product managers rely on designers or—worse—their own opinion to make the “right” choices for users based on their experience or accepted best practices. That may get teams some of the way, but that approach can so easily miss out on solving users’ real problems. To remain user-centered, this is something we should avoid. User research elevates design. It keeps it on track, pointing to problems and opportunities. Being aware of the issues with your product and reacting to them can help you stay ahead of your competitors.

In the three-act structure, each act corresponds to a part of the process, and each part is critical to telling the whole story. Let’s look at the different acts and how they align with user research.

Act one: setup

The setup is all about understanding the background, and that’s where foundational research comes in. Foundational research (also called generative, discovery, or initial research) helps you understand users and identify their problems. You’re learning about what exists today, the challenges users have, and how the challenges affect them—just like in the movies. To do foundational research, you can conduct contextual inquiries or diary studies (or both!), which can help you start to identify problems as well as opportunities. It doesn’t need to be a huge investment in time or money.

Erika Hall writes about minimum viable ethnography, which can be as simple as spending 15 minutes with a user and asking them one thing: “‘Walk me through your day yesterday.’ That’s it. Present that one request. Shut up and listen to them for 15 minutes. Do your damndest to keep yourself and your interests out of it. Bam, you’re doing ethnography.” According to Hall, “[This] will probably prove quite illuminating. In the highly unlikely case that you didn’t learn anything new or useful, carry on with enhanced confidence in your direction.”  

This makes total sense to me. And I love that this makes user research so accessible. You don’t need to prepare a lot of documentation; you can just recruit participants and do it! This can yield a wealth of information about your users, and it’ll help you better understand them and what’s going on in their lives. That’s really what act one is all about: understanding where users are coming from. 

Jared Spool talks about the importance of foundational research and how it should form the bulk of your research. If you can draw from any additional user data that you can get your hands on, such as surveys or analytics, that can supplement what you’ve heard in the foundational studies or even point to areas that need further investigation. Together, all this data paints a clearer picture of the state of things and all its shortcomings. And that’s the beginning of a compelling story. It’s the point in the plot where you realize that the main characters—or the users in this case—are facing challenges that they need to overcome. Like in the movies, this is where you start to build empathy for the characters and root for them to succeed. And hopefully stakeholders are now doing the same. Their sympathy may be with their business, which could be losing money because users can’t complete certain tasks. Or maybe they do empathize with users’ struggles. Either way, act one is your initial hook to get the stakeholders interested and invested.

Once stakeholders begin to understand the value of foundational research, that can open doors to more opportunities that involve users in the decision-making process. And that can guide product teams toward being more user-centered. This benefits everyone—users, the product, and stakeholders. It’s like winning an Oscar in movie terms—it often leads to your product being well received and successful. And this can be an incentive for stakeholders to repeat this process with other products. Storytelling is the key to this process, and knowing how to tell a good story is the only way to get stakeholders to really care about doing more research. 

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

Act two: conflict

Act two is all about digging deeper into the problems that you identified in act one. This usually involves directional research, such as usability tests, where you assess a potential solution (such as a design) to see whether it addresses the issues that you found. The issues could include unmet needs or problems with a flow or process that’s tripping users up. Like act two in a movie, more issues will crop up along the way. It’s here that you learn more about the characters as they grow and develop through this act. 

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

There are parallels with storytelling here too; if you try to tell a story with too many characters, the plot may get lost. Having fewer participants means that each user’s struggles will be more memorable and easier to relay to other stakeholders when talking about the research. This can help convey the issues that need to be addressed while also highlighting the value of doing the research in the first place.

Researchers have run usability tests in person for decades, but you can also conduct usability tests remotely using tools like Microsoft Teams, Zoom, or other teleconferencing software. This approach has become increasingly popular since the beginning of the pandemic, and it works well. You can think of in-person usability tests like going to a play and remote sessions as more like watching a movie. There are advantages and disadvantages to each. In-person usability research is a much richer experience. Stakeholders can experience the sessions with other stakeholders. You also get real-time reactions—including surprise, agreement, disagreement, and discussions about what they’re seeing. Much like going to a play, where audiences get to take in the stage, the costumes, the lighting, and the actors’ interactions, in-person research lets you see users up close, including their body language, how they interact with the moderator, and how the scene is set up.

If in-person usability testing is like watching a play—staged and controlled—then conducting usability testing in the field is like immersive theater where any two sessions might be very different from one another. You can take usability testing into the field by creating a replica of the space where users interact with the product and then conduct your research there. Or you can go out to meet users at their location to do your research. With either option, you get to see how things work in context, things come up that wouldn’t have in a lab environment—and conversion can shift in entirely different directions. As researchers, you have less control over how these sessions go, but this can sometimes help you understand users even better. Meeting users where they are can provide clues to the external forces that could be affecting how they use your product. In-person usability tests provide another level of detail that’s often missing from remote usability tests. 

That’s not to say that the “movies”—remote sessions—aren’t a good option. Remote sessions can reach a wider audience. They allow a lot more stakeholders to be involved in the research and to see what’s going on. And they open the doors to a much wider geographical pool of users. But with any remote session there is the potential of time wasted if participants can’t log in or get their microphone working. 

The benefit of usability testing, whether remote or in person, is that you get to see real users interact with the designs in real time, and you can ask them questions to understand their thought processes and grasp of the solution. This can help you not only identify problems but also glean why they’re problems in the first place. Furthermore, you can test hypotheses and gauge whether your thinking is correct. By the end of the sessions, you’ll have a much clearer picture of how usable the designs are and whether they work for their intended purposes. Act two is the heart of the story—where the excitement is—but there can be surprises too. This is equally true of usability tests. Often, participants will say unexpected things, which change the way that you look at things—and these twists in the story can move things in new directions. 

Unfortunately, user research is sometimes seen as expendable. And too often usability testing is the only research process that some stakeholders think that they ever need. In fact, if the designs that you’re evaluating in the usability test aren’t grounded in a solid understanding of your users (foundational research), there’s not much to be gained by doing usability testing in the first place. That’s because you’re narrowing the focus of what you’re getting feedback on, without understanding the users’ needs. As a result, there’s no way of knowing whether the designs might solve a problem that users have. It’s only feedback on a particular design in the context of a usability test.  

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

In act two, stakeholders will—hopefully—get to watch the story unfold in the user sessions, which creates the conflict and tension in the current design by surfacing their highs and lows. And in turn, this can help motivate stakeholders to address the issues that come up.

Act three: resolution

While the first two acts are about understanding the background and the tensions that can propel stakeholders into action, the third part is about resolving the problems from the first two acts. While it’s important to have an audience for the first two acts, it’s crucial that they stick around for the final act. That means the whole product team, including developers, UX practitioners, business analysts, delivery managers, product managers, and any other stakeholders that have a say in the next steps. It allows the whole team to hear users’ feedback together, ask questions, and discuss what’s possible within the project’s constraints. And it lets the UX research and design teams clarify, suggest alternatives, or give more context behind their decisions. So you can get everyone on the same page and get agreement on the way forward.

This act is mostly told in voiceover with some audience participation. The researcher is the narrator, who paints a picture of the issues and what the future of the product could look like given the things that the team has learned. They give the stakeholders their recommendations and their guidance on creating this vision.

Nancy Duarte in the Harvard Business Review offers an approach to structuring presentations that follow a persuasive story. “The most effective presenters use the same techniques as great storytellers: By reminding people of the status quo and then revealing the path to a better way, they set up a conflict that needs to be resolved,” writes Duarte. “That tension helps them persuade the audience to adopt a new mindset or behave differently.”

This type of structure aligns well with research results, and particularly results from usability tests. It provides evidence for “what is”—the problems that you’ve identified. And “what could be”—your recommendations on how to address them. And so on and so forth.

You can reinforce your recommendations with examples of things that competitors are doing that could address these issues or with examples where competitors are gaining an edge. Or they can be visual, like quick mockups of how a new design could look that solves a problem. These can help generate conversation and momentum. And this continues until the end of the session when you’ve wrapped everything up in the conclusion by summarizing the main issues and suggesting a way forward. This is the part where you reiterate the main themes or problems and what they mean for the product—the denouement of the story. This stage gives stakeholders the next steps and hopefully the momentum to take those steps!

While we are nearly at the end of this story, let’s reflect on the idea that user research is storytelling. All the elements of a good story are there in the three-act structure of user research: 

• Act one: You meet the protagonists (the users) and the antagonists (the problems affecting users). This is the beginning of the plot. In act one, researchers might use methods including contextual inquiry, ethnography, diary studies, surveys, and analytics. The output of these methods can include personas, empathy maps, user journeys, and analytics dashboards.

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

• Act three: The protagonists triumph and you see what a better future looks like. In act three, researchers may use methods including presentation decks, storytelling, and digital media. The output of these can be: presentation decks, video clips, audio clips, and pictures. 

The researcher has multiple roles: they’re the storyteller, the director, and the producer. The participants have a small role, but they are significant characters (in the research). And the stakeholders are the audience. But the most important thing is to get the story right and to use storytelling to tell users’ stories through research. By the end, the stakeholders should walk away with a purpose and an eagerness to resolve the product’s ills. 

So the next time that you’re planning research with clients or you’re speaking to stakeholders about research that you’ve done, think about how you can weave in some storytelling. Ultimately, user research is a win-win for everyone, and you just need to get stakeholders interested in how the story ends.