TAOI

The Architecture of Information

TAOI: Personalized Yelp Results

| Jorge Arango

The architecture of information:

Per TechCrunch, Yelp announced earlier this week that it will allow users to personalize search results:

Once you’ve made your selections, those preferences will start affecting the search results you see. The personalization should be obvious because the results will be identified as having “many vegetarian options” or “because you like Chinese food.” The homepage will also start highlighting locations that it thinks you would like.

Seems like an obvious feature, especially for a system like Yelp that aims to connect users with places they will like. A short video explains how it works:

A baseline 21st Century tech literacy skill: Training the algorithms that personalize your search results. (For designers: Watch for emerging user interface standards for such training mechanisms. I was intrigued by Yelp’s use of the heart icon to signify personalization.)

Yelp will let users personalize their homepage and search results

TAOI: Following Topics on Twitter

| Jorge Arango

The architecture of information:

According to a report on The Verge, Twitter is testing a means for users to follow topics in much the same way that they follow Twitter accounts. Topics would include sports and entertainment, and would be determined algorithmically.

Why is Twitter doing this?

The move represents Twitter’s latest effort to help users find the best content on the platform even if they don’t know which accounts to follow. For years, the company has sought to make it easier for people to find value in Twitter, which can be foreboding for newcomers.

This sounds like something you can already do with hash tags. However, as the report points out, this feature may not be easily discoverable for new users. It makes sense to surface topics over (or at least in parallel) to accounts, since “interests” can be as much (or more) fodder for conversation than what we traditionally think of as accounts. (I.e., Loci representative of — and curated by — either individuals or organizations.) Still, this sounds like an important change to Twitter’s conceptual model.

Twitter tests letting users follow topics in the same way they follow accounts

TAOI: Disneyland App

| Jorge Arango

The architecture of information:

Digital experiences are changing our understanding of physical environments. Google Maps gives you the ability to walk around a new city as though you’d known it for a long time. And should you develop a sudden hankering for ice cream, Yelp allows you to locate the nearest gelateria. The most noticeable change comes from layering information on the environment. For example, when trying to decide between two neighboring restaurants you’re no longer constrained to judging them solely by their appearance; you can also peruse their reviews in Yelp. Restaurant A has four-and-a-half stars, whereas restaurant B has three — A it is!

The number of stars is information about the place. You won’t find it in the physical place itself, but in its representation in an information environment which you access through your magical pocket-sized slab of glass. We’ve grown used to these augmented interactions with physical space, and mostly take them for granted. But recently I had one such interaction with an app I hadn’t used before, and which stood out to me for 1) its clarity of purpose and 2) the degree to which that purpose changed the experience of the place. I’m referring to the Disneyland app.

My family and I visited Disneyland a few weeks ago. We hadn’t been in five years, and the Disneyland app was one of the novelties since our last visit. The app presents a map of the Disney theme parks. As such it mostly replaced the parks’ old (and sometimes beautiful) paper-based maps. Thanks to the phone’s sensors, the Disneyland app makes it easy to figure out where you are, where to go next, and how to get there. But the app adds an additional key piece of information to the experience that can’t be had with paper-based maps: attraction wait times. Over every representation of an attraction in the park, you see a little callout that indicates how long you’ll have to wait in line to experience that ride or show:

Disneyland app

This piece of information is always available at all levels of zoom in the map. It’s the definitive element of the experience: in these maps, attraction wait times have the highest visual priority. As a result, wait times become the defining factor in sequencing the exploration of the park. The apps preferred answer to the question “What should we do next?” is always “Whatever is closest that has the shortest lines.”

This is an interesting choice that recalls the park’s old ticket levels. A long time ago, each Disneyland attraction required a separate ticket. Not all attractions used the same tickets; there were several levels ranging from A to E. “E-tickets,” such as the Haunted Mansion, were the most popular and desirable. These were considered the park’s premium attractions; their tickets were worth more than the others. This economic scheme influenced how visitors experienced the park. Ticket “coupon books” only included a limited number of E-tickets as compared to the lower denominations. Guests could buy more tickets inside the park, but having a limited number of the various level tickets affected choices. (I remember visiting Walt Disney World when it had a similar scheme, and hearing things like, “let’s visit this ride next, we have to use up our C-tickets.”)

The Disneyland app creates a similar economy by making attraction wait times the key informational element of the experience. When you’re trying to decide between two rides, knowing you’ll have to wait 65 minutes in line in one versus 15 minutes in another could be the key factor in your choice. (It was for my wife and me. Children get very cranky after waiting in long lines all day!) Our choosing to go on the ride with the lower wait times would contribute to slightly increasing that ride’s wait times and lowering the wait times for the more popular rides. I don’t have data, but my expectation is that this would help even out wait times throughout the park.

That is, of course, if all other things are equal — which they aren’t. The Haunted Mansion is a much more elaborate and compelling experience than Dumbo the Flying Elephant. Also, some rides have higher throughput than others. So the choice of riding one rather than the other doesn’t come down solely to which has the shortest waits.

That said, for someone like myself, who knows Disneyland very well, having this extra bit of information made the experience of visiting the park much better. In our two days at Disneyland, my family and I experienced more of the park than we’d ever been able to before. We also had more fun, since we spent a lower percentage of our time there in queues. But I wonder about the effect on folks who are less familiar with the parks. Will the emphasis on wait times drive them to prioritize less popular attractions over the park’s highlights? Adding feedback mechanisms to a system influences the way the system works. In what unexpected ways does this app change the experience of visiting Disneyland?

TAOI: The “Agony” of Browsing Amazon

| Jorge Arango

The architecture of information:

As I’ve noted before, as software eats more of the world we’re likely to see more stories about how poor information architecture is hurting businesses. Along these lines, a recent opinion piece in Bloomberg claims browsing for products in Amazon is “agonizing”:

Try clicking through Amazon’s beauty products section to the pages for foundation, one of the (ahem) foundations of any makeup line. It’s a notoriously tricky item to buy online or in stores because people must match the shade to their skin tone. I found hunting for foundation on Amazon comically impossible.

There are 200 pages of products grouped seemingly with little reason. It’s not possible to narrow the product listings by liquid or powder foundation — equivalent to not giving people the choice between boxers or briefs.

Today is the second of two “Amazon Prime Days,” when the retailer presents many products at a deep discount. I’m in search of a new pair of sunglasses, so I’ve perused the site’s offers a couple of times since yesterday. The findings in the Bloomberg piece correspond with my experience: Amazon is relatively easy to use if you know what you’re looking for, less so if you’re browsing.

As the piece notes, it’s hard to state precisely how much (if any) this is hurting Amazon’s business. Speaking from my own experience, I find myself using other information environments as my first resort for browsing for products more often than not. (It’s not just bad IA; lately I also find Amazon’s UI slow to load and clumsy to operate.)

Amazon Shopping Is Easy. Browsing Is Agonizing.

TAOI: Podcasts on Spotify

| Jorge Arango

The architecture of information:

Last week, Apple announced the end of its venerable iTunes application on the Mac. In its stead, the next version of macOS will feature three applications: Music, Podcasts, and TV.

This change is long-coming. Managing media such as music, podcasts, and movies is one of the uses of computers that requires regular folks to think like information architects; they must consider categorization schemes, the nomenclature of artist names, the integrity of their metadata, and so on. (Most people lack the language to describe the challenges in these terms, of course.) By separating media types into their own applications (as has long been the case in iOS), Apple eliminates the confusion inherent in presenting different types of stuff that nevertheless share similar structural underpinnings.

Now Spotify seems to be moving in a similar direction. According to an article on The Verge, an upcoming release of the app will more clearly separate podcasts from other types of audio types. It will also introduce a clearer structure for podcasts:

Podcasts on Spotify are currently only organized by shows that users follow, unplayed shows, and downloaded shows, which is to say it’s chaotic. In the new design, the podcast category will be broken up into three sections: episodes, downloads, and shows.

Image: Spotify
Image: Spotify

I haven’t yet seen the new design myself (nor am I a Spotify user.) However, this strikes me as yet another example of how businesses are using information architecture as a way of making their products and services more competitive. As I’ve said before, good IA is good business.

Spotify’s officially separating podcasts and music in premium users’ libraries

TAOI: OmniFocus Tags

| Jorge Arango

The architecture of information:

I recently ran across this video for the latest version of my favorite task management app, OmniFocus:

“Tags” is the leading feature of version three of the app, and this video highlights its power: it’s all about giving end users the power to create personalized information structures that allow us to be more productive. Another example of information architecture as a key product differentiator.

TAOI: YouTube Subscriber Counts

| Jorge Arango

The architecture of information:

A headline on The Verge: YouTube is changing how subscriber counts are displayed, possibly shifting its culture.

One of the most famous aphorisms in management is Peter Drucker’s observation that “if you can’t measure it, you can’t improve it.” This phrase succinctly captures an important idea: when deciding the way forward, data is your friend. Rather than discussing directions in the abstract, this concept encourages us to break down problems into impartial facets we can trace over time.

However, as useful as it is, there’s a flip side to this concept: with a compelling enough measure, we can lose sight of the ultimate “it” we’re trying to improve. The point of losing weight isn’t to read a lower number on a scale; it’s to get healthier. The number is a proxy for health — and an imperfect one at that. “Health” is a complex subject with lots of nuances. Articulating it as a single number can make it easier to understand, but oversimplifies a complex whole.

We compound the problem when we base incentives on these numbers. Let’s say you’re promised a $500 bonus if you lose a certain amount of weight by a particular date. At that point “health” is twice abstracted: your goal is now neither health nor weight but the money. The numbers start to become more important than the ultimate thing we want to achieve. The map is not the territory, but we’re being incentivized to navigate the map.

We hope to get to the goal on the real ground the map represents. But sometimes we don’t. Sometimes the map is so compelling that it becomes the territory. This has happened with measures in social media such as follower counts on Twitter.

Back to The Verge article. High-level summary: After a recent kerfuffle between two “creators,” YouTube is changing how its system displays subscriber counts. Creators compete for subscribers, and their fortunes wax and wane accordingly. In this system, follower counts are a proxy for popularity. It’s an imperfect measure, but it’s clear and compelling, and so emerges as the locus of attention for an economy of influence. I didn’t realize it until reading about this issue, but there’s a secondary market on these stats: websites like Social Blade exist solely to track how these people are doing relative to each other. It’s a big deal.

But what’s the ultimate goal here? What social function is this system enabling? (What’s the equivalent of “health”?) Is it entertainment? Commerce? Both?

TAOI: IDAGIO

| Jorge Arango

The architecture of information:

IDAGIO is a music streaming service. It competes with the likes of Spotify and Apple Music — big players with deep pockets! But IDAGIO is different: it only streams classical music.

If you’re into classical music, you know the other music streaming services aren’t good at classical. Not because of the quality of the recordings, but because they’re set up for pop music, which is usually consumed in single tracks. Classical music, on the other hand, is usually presented in “works,” compositions that consist of several tracks. Structuring information in this way is the first feature IDAGIO highlights on its homepage:

The best search
Unlike other streaming services, we organise music by work not track. Compare all recordings of your favourite work, browse different interpretations, and find the latest albums.

Information architecture as strategic differentiator.

TAOI: Adding More Context to Tweets

| Jorge Arango

The architecture of information:

According to a report on The Verge, Twitter will soon start testing new ways of displaying tweets that should give them more context. Some features clarify messages’ positions in conversations using reply threads:

I’m more intrigued by two other features: availability indicators and context tags. The former are green bubbles next to the user’s name that indicate whether s/he is online and using the app at any given time. (Much like other chat systems do.) The latter are tags that allow users to indicate what a tweet refers to. Having a bit more context on what a tweet is about should help avoid non-sequiturs. (I assume it would also make it easier to filter out things you don’t want to bother with.)

Image: Twitter
Image: Twitter

Features like these should drive engagement in Twitter and add clarity for users; a case of alignment between the company’s goals and those of its users.

Twitter is rolling out speech bubbles to select users in the coming weeks