To this day, my favorite mobile app is one that very few people ever used, and it was only on the market for a short time. Called Emu, it exited beta testing in 2014 and was a mobile messaging platform that looked very similar to any phone’s text-messaging system, only it happened to include an artificial intelligence (AI) engine.
The pretty good likelihood that you’ve never heard of Emu is in fact a measure of its success, and it helps explain why so many other new products, services, and technologies either go viral or fizzle out at the moments that they do. Here’s a look at why.
At the time of Emu’s launch, you still had to look at dates on a calendar to find a good time to meet. To make plans, you first had to read and respond to emails or text messages. Emu’s premise was simple yet powerful: When texting with a friend or coworker, a smart bot would jump into the conversation and automatically retrieve information while you typed. As a result, those who used the app would all find their lives a little easier to manage.
Here’s how it worked: I sent my sister a text message within the app asking her if she wanted to get together for dinner.
Me: Hey, do you want to get dinner this week?
The app automatically looked at our calendars and suggested mutual dates and times that we were free. Within the same window, a little calendar appeared with some suggestions. She chose one of the times and texted it back to me:
My sister: Sure, Saturday night?
Since we had mentioned dinner, the app geo-located us on that date and suggested a handful of restaurants that would be nearby. It also displayed Yelp reviews and reservation times on OpenTable—all within the app. No having to look up restaurants or call around to see who had open reservations. I simply texted her back:
Me: How about Café Dupont?
With that, I could click on a single button to confirm our reservation for 7 p.m. on Saturday. We sent a total of three text messages between the two of us, and with the assistance of a very clever bot, we no longer had to suffer through the process of messaging back and forth endlessly trying to find a date, time, and restaurant. Emu automated all this work for us.
And it was equally helpful if we wanted to see a movie: It would automatically find a theater that was equidistant on the date we were available, then show us movie trailers and allow us to buy tickets—again, all within the app. It had a “Marco Polo” feature, too, which allowed us to find our friends on a map as they were headed our way.
Emu’s founders didn’t race to market with their strategy. Instead, they committed to planning—and, as a result, ample testing. If we’ve learned anything from all the technological innovations launched over the past decade, it’s that new kinds of technologies break in weird and sometimes unexpected ways. That’s why Emu’s developers trained it with thousands of test messages before it was released, so they could tweak its interpretation and analysis.
This thorough testing allowed developers to challenge their assumptions about how users—not just the developers and their small group of beta testers, but average people, too—would potentially interact with the app. One thing they realized was that Emu needed to learn how to make nuanced inferences. It considered the whole message before attempting to assist, so that it was more likely to correctly identify each word’s individual context.
This is more than just a lesson about the relative perils of iterative design, or a corrective to the checkered performance history of bots in the years since Emu’s release. It’s much more fundamental than that. Rather than simply identifying a trend and developing a strategy—in this case, a mobile app—Emu’s team pressure-tested its assumptions first.
Looking back now, it’s clear how that helped Emu preemptively answer some of the key questions about its likely fate. There are a handful of those that every would-be innovator needs to answer, but these are just three that helped Emu successfully align its strategy with the future it foresaw.
Does the action you’re planning offer a unique value proposition, and is it clear to your customers? (And “customers” can be defined broadly: individual consumers, customer segments, business partners, agencies you’re collaborating with, constituent bases, etc.) Is your strategy difficult to replicate? As competitors emerge, how will you help others continue to understand what differentiates you?
In 2014, Emu was unlike anything that had entered the market. There were elements of Emu in other applications, of course—Microsoft’s Outlook would automatically add new meeting invitations sent by email to your calendar—but a bot that could manage so many processes, all within one text-messaging app, was unique.
It didn’t take long for users to recognize that. Case in point: My sister is an opera singer, not a techie. Although Emu was intended to cut down on the usual back-and-forth emails and phone calls, she couldn’t help but to call me after we’d scheduled our dinner date. She was completely blown away by Emu.
After thanking me for sharing it with her, she immediately recruited dozens of her friends to download it. It didn’t take long for potential partners to realize Emu’s value proposition to them: Local businesses, public transit, concerts, and other events could all be tied into the platform.
Your product also needs to be timely: Does your trend strategy communicate a sense of urgency, both to your staff and to your intended audience? Will there be continued demand in the marketplace? Can you create demand within your customer base? Will customers see your project as indispensable, even as the market evolves and competitors emerge?
Emu arrived just early enough to solve a problem for many early tech adopters, those people who were now tethered to their smartphones. In 2014, the myriad, daily micro-transactions heaped upon us by our devices only seemed to be increasing, and those of us who used Emu found relief from some of the new stresses they brought.
Emu was quickly becoming an indispensable app, and many of us became overnight evangelists, imploring others to download it so we could break free of email and standard texting.
Your strategy will likely need to evolve. How will you invest time and money to tracking the trend you’re riding as it changes and adjust your course? Can you stick to a reasonable development cycle as you do? Can your product’s evolution follow its intended customers as they upgrade their other technologies? Are you and your staff motivated to keep working on your trend strategy once your product has launched?
As the bot trend would evolve, so could the AI-powered engine within Emu. AI would inevitably evolve, too, competitors would of course enter the marketplace. Emu’s makers expected all this, knowing their product could be made smarter and more capable of assisting users with everyday tasks. With a small team, reasonable overhead, and a modest amount of investment, the Emu team was free to recalibrate and to continue working on its strategy after it exited private beta-testing.
How does Emu’s story end? And why haven’t you heard about it? The answer is simple: Around 100 days after Emu officially launched, Google quietly swooped in and acquired it. Given what we know to be true about how 2014, 2015, and 2016 played out, it’s not hard now to divine Google’s interest in retrospect. The same technology that allowed busy people to schedule meetings, dinner, and movies necessarily monitored our conversations. It analyzed our chats and made inferences about what we were discussing.
It was therefore a perfect opportunity for advertising—one too good for Google to pass up.
This article is adapted from The Signals Are Talking: Why Today’s Fringe Is Tomorrow’s Mainstream by Amy Webb. Copyright 2016 by PublicAffairs, an imprint of Perseus Books, LLC, a subsidiary of Hachette Book Group, Inc. It is reprinted with permission.