This is a guest post by Samir Addamine, Founder and Chairman, FollowAnalytics
We all know that the odds are stacked against branded apps. It has been established, for instance, that 90% of branded apps have fewer than 10,000 downloads. If you launch a new app today, you are one among 4 million or so.
With a 0.1% chance, the Chargers are more likely to win the Super Bowl.
Those odds are getting worse. The average U.S. smartphone owner downloads zero new apps a month, according to comScore. Even the top apps saw a 20% drop in downloads from May 2015-May 2016. Consumers spend most of their smartphone time within apps and spend 84% of their app time within just five apps.
Still, the rewards are so great for branded apps that most companies haven’t given up hope. A branded app can give your brand presence on a device that consumers stare at for roughly three hours a day and can allow you to learn more about such loyal customers.
The problem is that if marketers pull off the impressive feat of getting consumers to download their app, they often fail to make the app engaging. As result, most are unused and eventually, deleted. It doesn’t have to be this way. If brands apply the same rigor to making their apps engaging that they do to marketing, then more consumers will opt to keep it.
Improving Branded Apps
The first generation of branded apps were fairly dumb and limited in function. However, eight years after the App Store launched, it’s no longer good enough to merely offer a branded app; that app has to be genuinely useful.
Since consumers don’t keep apps they don’t use, it’s important to see and what messaging or feature resonate with them and make updates accordingly. One technique is A/B testing. This is common practice in marketing and product development, but brands usually approach A/B testing manually and not very scientifically.
To truly determine which features are best, you need to look at all possible variables and that requires artificial intelligence. That’s because you’re not just looking at which messages and features are resonating best overall, but which ones are resonating with which segments. When those segments get granular then the possibilities increase exponentially, which is why machine learning can help.
Another factor that brands don’t usually consider for their apps is tone. How does your app communicate with your consumers. Is it flippant? Chatty? Deadly serious? This is another area where AI-enhanced A/B testing can help. Over time, brands can learn that some tones work better with some segments and then adjust accordingly. Such information has value beyond the app but can help the brand formulate its overall communication.
Finally, it’s important to monitor app performance to ensure that consumers are getting a positive view of the brand. If the app is crashing, you’re going to lose customers. But if you know that certain customers stopped using the app for that reason, you might want to communicate with them that you’re aware of the problem and will offer them a discount on their next purchase to make amends.
The App is a Proxy for Your Brand
Marketers often look at branded apps as a vehicle for communicating with consumers, which it is, but it’s also a proxy for your brand. If an app crashes or is poorly designed, consumers blame the brand, not the app.
That’s why brands should put at least as much thought and resources into increasing app retention as they do to marketing their apps. To liken marketing to football once more, marketers may feel like they scored a touchdown when a consumer downloads their app, but the reality is they’re only at the 1-yard line.