Search, discovery and marketing

One of the clearest places to see this problem of ‘too much’ is Yelp. I’ve been fascinated by how many companies are effectively trying to unbundle Yelp, despite that fact that (unlike Craigslist) it’s a modern technology company that does most of the things one would expect it to. But where people unbundling Craigslist generally try to peel off a category and deliver a modern experience, the people going after restaurant listings are often doing so with constraint. That is, instead of giving you every single restaurant that’s within 2 miles and that lots of people liked, they give you 10 restaurants. … People are attacking crowdsourced universal scale with constraint, curation and personal preference.

Looking at these companies, it strikes me that actually, saying that ‘Yahoo’s directory didn’t scale’ misses the point. What we’re really seeing is a trade-off between two problems. You can have a list, solving discovery and recommendation, but once the domain gets big then your list is either unusably long or partial and incomplete (and perhaps uneconomic to maintain). Or you can have a searchable index of everything but you’re on your own working what’s good and finding things you didn’t know to search for.

Search, discovery and marketing from Benedict Evans

Curation also works best in places where taste matters — the “best” book, the “best” restaurant. An algorithm can’t provide social validation beyond “the most popular.” What’s interesting about Yelp is that their focus on user generated content  means it’d be hard for them to add sources of curation outside of their users — there’s no list of restaurants with Michelin stars, or James Beard winners, and there probably can’t be one without undermining the core conceit of the platform.

Killing the Creative Class

In Culture Crash: The Killing of the Creative Class, Scott Timberg explores the convergence of forces which have combined to “eviscerate the creative class” — those people who make, produce, review, and sell culture; he includes everyone from record store clerks to authors.

While I sympathize with Timberg, and share some of his nostalgia for the late 20th century, I deeply disagree with his assessment of what we’ve lost, and how we lost it. At a high level, Timberg blames the rise of the internet for the decline of the creative class, through piracy, disintermediation, and mass retail.

His piracy arguments feel tired; the point has been argued elsewhere (see this, this, this, and this). While counterintuititve, there isn’t much evidence to suggest that modern piracy substantially harms most artists; the rise of high-quality distribution services massively undercut piracy (see: Spotify).

On disintermediation, his description of record, book, and movie store clerks is striking. They were “men who’d given up something else do [this work] out of love for the music.” He describes they as having a moral commitment. It is as if cultured clerks are modern-day monks, dedicated to art instead of God.

But the decline of Western civilization’s long-time keeper, the Catholic Church (and with it, monks & monastaries) no more sounded a death-knell for our culture than the rise of the Internet over the past three decades has.

In particular, Timberg fails to place the creative class he mourns in the context of history: Mass-produced culture is a new phenomena. There were few book clerks before Gutenberg. Motzart and Michelangelo produced culture with funding from noble patrons, not from a creative middle-class. Art and culture will need to change in response to new technologies and social mores, but it will survive.

I suspect we will see a shrinking professional creative class, but a flowering of amateurs. I’m not concerned about the production of culture, but I’m less clear on how culture is discovered. Timberg suggests that the canon of classics is undersiege, and its hard to disagree. There are fewer “expert” voices saying what should be consumed, and its harder to find the signal in the noise.

This isn’t necessarily negative. Old cultural gatekeepers often enforced mass culture — disadvantaged or fringe artists could be locked out. But I find it hard to believe that The New York Times Bestseller List is the best way to identify our cultural canon.

In part, this is because I think why something is recommended is just as important as what was recommended.

For many pieces of culture, the story and recommendation is a critical part of providing value. What is the story of this piece? How does it fit into the larger movement? What is its place in history? Am I supposed to like it? I suppose I believe that culture benefits from a hint of elitism. And I’m not sure that algorithms can provide an elite judgement anytime soon.

For many, the consumption of culture isn’t too different from the consumption of wine: We take pleasure, backstory, and price — in addition to the culture itself.

Computer algorithms can provide recommendations (as shown by Netflix), and will improve. But the algorithms that undergird machine-learning recommendations work by finding counterintuitive and subtle links between people and the culture recommended — I don’t believe exposing these recommendations would be compelling to most users.

Some companies have two separate algorithms: one to produce a recommendation, and one to produce a compelling set of reasons. This should eventually produce compelling rationales (assuming “success” is properly defined and fed into the algorithm — easier said than done), but if people don’t have faith in the algorithm, it can’t impart greater meaning and value to pieces of culture.

So I’m not sure how we can protect this judgement.

I don’t think recommendations do well in a winner-take-all marketplace, and instititutions like Michelin or Pitchfork are struggling to remain viable as businesses.

In part, these publications and cultural touchstones are being replaced by user generated content [UGC]. But UGC-centric sites struggle with authority — is a lengthy review from a Yelp elite reviewer more important to Yelp than a review from Michelin? Should a university professor and expert in a subject have more power than a long-time Wikipedia editor to edit Wikipedia?

The issue might not be insurmountable — Stack Overflow seems to have resolved some of these issues, and FourSquare is playing with interesting mesasures of “expertise” — but there are no comparable cultural organizations.

Where do we go from here? I’m not sure.

Do mobile user education right

Redlaser 4.0 Mock

When we were designing RedLaser 4.0, one of our biggest questions was now to handle navigation. In particular, we weren’t sure where to put the button that launched our barcode scanner. It’s a critical function, but we were adding more features, so we needed to make sure it stood out.

We put it at the very center of our navigation bar, with a giant scan icon. We made the background red, so that it would really pop.

Sure, the app wouldn’t boot straight into the scan mode — we wanted users to see all the new features — but we were sure we’d done the next best thing.

The design failed, horribly, in testing. One user, a long-time RedLaser user, spent fifteen minutes trying to figure out how to launch scanning. She later told us she hadn’t even noticed the button.

This is a common story in mobile: Complex user interfaces are extremely hard, and a UX change can backfire in unexpected ways. If a button isn’t explicitly labeled and visible above the fold on the home page, it will get exponentially less usage.

This is a challenge: Phone screens are too small to show an explicit user interface for all but the simplest apps.

RedLaser isn’t alone in facing this issue. Swarm is a gorgeously designed app from Foursquare. It is the culmination of FourSquare’s efforts to re-envision and dramatically simplify the check in process. To do this, by default it continually broadcasts your current neighborhood to your connections. FourSquare realizes that while this behavior is critical to the app, it can also be really creepy: you don’t always want your friends to know when they’re nearby.

A very important part of the interface, then, is turning this tracking off. It’s easy, but also a new interaction element: You swipe left-to-right across the top bar and it changes your state:

FourSquare

While this interaction approach is easy and smooth, Swarm’s challenged because it isn’t a kind of interaction users expect — and there’s no explicit text to let you know it is even an option. Even savvy mobile users find it hidden:

This leaves developers two choices: Build simpler apps, or teach users.

It looks like many of the largest companies in mobile are choosing the former. The triumph of Whatsapp is its focus and simplicity — and it is followed by focused apps from eBay, LinkedIn, Amazon, Google, and more. A single-purpose app can create a focused, simple, user-interface.

A single-purpose app, however, just creates different problems: User acquisition, and user retention. Big mobile companies with their own ecosystems can use apps to feed each other (just like clicking an eBay link in RedLaser will send users to the eBay app). The vast majority of mobile players don’t have this luxury, and user acquisition can be brutally hard. So when you’ve convinced a user to download your app, it needs to be a must-open, home-page-worth app — and this frequently will mean complexity.

Most app developers can’t afford to fragment their user base. So complex apps need to get user education right.

User education, however, is hard. The most common approach is to show an overlay on launch, calling out a few critical buttons. In Swarm, FourSquare insisted every user disable and then re-enable location tracking before permitting wider use of the app. Others require users to watch short videos or swipe through pages of text.

None of this works. Most users in a new app want to get up and running as quickly as they can. We’ve all been guilty of furiously button mashing through tutorials, trying to get to the meat of the app. So what should a designer or product lead do?

The most impressive user education system I’ve encountered is, surprisingly, for the app Secret. Secret is a social sharing app whitest people anonymously broadcast information.

Secret uses three complementary approaches to user education

Method 1: The traditional tutorial

Secret starts with a traditional user education flow When a user opens the app for the first time, they need to swipe through a series of screens describing the basic operation of the app. This happens before registration, which is important so that users get a sense of how the app works and aren’t driven to close or delete immediately. These screens are extremely simple, focusing on concepts rather than on specific functionality.

At RedLaser, we found people swipe through this kind of screen extremely quickly. The default assumption should be that the average user will not see this content.

HighlightsMethod 2: In-line education

Secret’s first innovation in user training is inline education. The key interface for the app is a user’s secret feed. When a user pauses to read a secret, it is blurred out and a single, focused, explanation of a user interface element appears. These messages are contextually relevant — they only appear when the user pauses to read a message that could benefit from further explanation.

The advice is effective and powerful because it is highly relevant to the user’s current situation. The messages either suggests a specific action the user can actually take on the secret they’re reading right then, or it provides context for the secret (if not from a friend) which makes the secrets more valuable.

Exiting these messages requires a click in a small area, and the exit button changes location (following the messages), which means that users can’t quickly skip through the messages.

Inline-NotesMethod 3: Spaced Retrieval Therapy

Secret’s final training method is spaced retrieval therapy. In SRT, you regularly re-expose people to information to lock it into their minds.

Secret uses this for key pieces of information: How to like secrets by swiping left to right (critical because this determines whether and how secrets are shared), and permissions requests.

This information is displayed inline, just like a normal secret, which means users are less likely to block the content out (as in banner blindness).

It isn’t clear when Secret decides to show this information. To most effectively train people about interfaces, they should display the information on a regular pattern with decreasing frequency (e.g., after 1 day, 3 days, 7 days, 14 days, 30 days, etc.). If a user positively responds to the content (for example, by taking the action without prompting), the frequency of reminders can become less frequently.


For other posts on mobile, read about the trend of increasing apps per company and iOS 8’s major pro-privacy changes.

App Disaggregation’s Physical Limit: 30 apps per device

eBay Marketplaces: 3 apps (Core, Fashion, Motors)
Facebook: 5 apps (Core, Messenger, Whatsapp, Instagram, Paper)
LinkedIn: 3 apps (Core, Contacts, Recruiter, and until a few days ago, CardMunch)
Google: 36 apps (ridiculous)

Across mobile, the companies most serious about mobile are disaggregating their features sets and building new, more focused, apps. There are compelling reasons to split up your apps:

  • Apps get one chance to get key permissions from the user — push and geo, in particular. With multiple apps, you can ask multiple times, and users might have a clearer understanding of why the permissions are necessary. And if one of a company’s apps annoys users, the users are less likely to totally cut out that company (by revoking permissions in all apps).
  • Smartphone screens are small — even on the largest Android devices. Focused apps can have simpler user interfaces, without hidden features. If a button isn’t visible, most users will never find it. This is why Facebook removed their slide out navigation panel and why Venmo’s right nav surprised me. RedLaser has a left navigation, but we find that users are orders of magnitude less likely to use any features there.
  • Updates take time on iOS. If you’re testing new features which might anger customers or be unstable, it’s better to test in less important apps and eventually roll the best and most stable features into the core experience.

However, most users don’t have many apps on their devices: Surveys suggest users have only gone from 31 to 33 apps on their devices over the past five years. (See my data here.) Moreover, most of these apps are likely games.

Average Apps per Device

If users don’t have more apps, who is using these more focused apps? A few hypotheses:

  • Power-users use anything other than the core apps (and maybe Whatsapp). App manufacturers can create power tools for some users without distracting most of their user base.
  • Apps from powerhouse developers are beating out smaller companies. eBay/Facebook/Google/etc. have a larger share of the install base than they did 4-5 years ago.
  • None of the ancillary apps have significant install bases. They’re purely used for experimentation, and all the successful features will be rolled into the core apps.
  • The cohort of users with smartphones in 2010 might have many more apps installed in 2014 — but the average is weighted down by new late-adopting smartphone users.

I suspect all these explanations hold a bit of truth. It’ll be an interesting place to watch — particularly because discoverability of installed apps becomes a huge issue once users have 100+ apps. I’m already at the point where any apps off my home screen are accessed via Apple’s built in search feature or Siri.

Top PMs are top trusted advisors

I’m a huge fan of Quora. I have no idea if it is sustainable as a business (and get a bit flabbergasted by its regular, and enormous, rounds of funding), but there are few other places where you can find reflections on the height of the author of Dinosaur Comics author Ryan North and the valuations of small, private, startups on the same website.

One of my favorite answers is from a general manager at Amazon, who ponders what distinguishes a top 1% product manager from a top 10% product manager. I’m particularly struck that the respondent (Ian) goes beyond the typical trite description of the role — “Product owner,” “mini-CEO” — and lays out very detailed and particular activities he thinks sets the greats apart:

  • Think big
  • Communicate
  • Simplify
  • Prioritize
  • Forecast and measure
  • Execute
  • Understand technical trade-offs
  • Understand good design
  • Write effective copy

(He goes into more detail in his answer.)

What struck me about this list is that the defining characteristics of a great product manager are also the defining characteristics of the greatest consultants I’ve known — and the greatest lawyers, and marketers. At its heart, answer suggests that a great product manager is a great trusted advisor.