Analytics is about getting your team the data insights it needs to build better products and make the right decisions for your company.
But if your team can’t understand that data, then this is all for naught. Software like Amplitude can make your data easy to understand, but each member of your team still needs basic data skills to get the most value out of what they’re looking at.
You’re seeing those download counts for your app start to rise. More and more people are signing up, logging in, and taking first steps. Your app looks like it’s on its way to success.
But it may not be time to celebrate just yet. While downloads and first-time visits are exciting, they only tell a fraction of your app’s story; it’s important to measure how many users actually find long-term value in your app.
By analyzing long-term metrics, you’ll get a better idea of exactly how valuable users consider your app for continued use weeks and months after launch. The most important of these metrics are:
- Retention rate: The rate at which users continue to use your app over time.
- Engagement: How many times a user performs a specific action.
- Usage interval: The frequency with which you expect people to naturally use your app.
Here we’ll show why measuring this mobile user data helps you track your own progress and see how you stack up against other successful apps. You’ll learn how to plan the long-term trajectory of your app’s development, and ensure that it’s a long trajectory for users too.
This article is an excerpt from the first volume of The Product Analytics Playbook: Mastering Retention. Retention is the one metric that matters for sustainable growth. The Playbook is a comprehensive guide to understanding user retention that provides a novel framework for analyzing retention at every stage of the user journey. You can find other excerpts from the Playbook here.
Google “how to improve user retention” and you’ll come across hundreds if not thousands of tactics and strategies on how to do exactly that. There’s an overwhelming wealth of information on the kinds of marketing and product changes you can experiment with to get the boost in retention that you want.
What’s missing, however, is a systematic framework for improving retention that companies can continuously iterate on, as well as one that will work for companies at any stage of growth. Over the past several months, we came up with framework to accomplish exactly that.
Once you’ve determined your product’s critical event and its usage frequency, you can apply The Retention Lifecycle Framework to your users. (For a refresher on critical events and usage frequency, be sure to check out our previous Retention Playbook excerpts.)
Earlier this month, we reached an exciting milestone here at Amplitude: we’ve now tracked over 1 trillion user actions.
Using some of that user behavior data, we shared a new way to think about retention–bracket retention–for apps that are not daily usage, instead of the industry standard “N Day” calculation.
We also hosted “Best Practices and Lessons Learned from 1 Trillion Events Tracked,” during which Amplitude CEO Spenser Skates shared four additional lessons he learned over the course of four years at Amplitude.
If you missed Spenser’s webinar a couple weeks ago, not to worry. We’ll be recapping those lessons in today’s post.
To view a recording of the webinar, you can also go here.
Within 24 hours of its U.S. App Store release, Pokemon GO became the biggest game of 2016.
Pokemon GO broke the record for first-week downloads and became the fastest app ever to reach number one on the Top Grossing Apps chart.
Then public interest plummeted. Google Trends show a spike in public interest in the game—followed by a steep decline in the weeks after:
But Pokemon GO isn’t as short-lived as this spike and fall would suggest. Sure, the fad might have been over quickly—but the game is continuing to prove that it can be successful long after the hype.
After the Rio Olympics, Stratechery’s Ben Thompson wrote an article questioning the fate of live sports. With streaming viewership up, Nielsen ratings down, and 50 million people just watching highlights on Snapchat, he urged media executives to consider whether sports in general was “must-see TV today, just another stream on Snapchat tomorrow.”
But Thompson’s nuclear scenario—advertisers fleeing the networks, the networks collapsing, and Snapchat or another platform taking over—assumes that the NFL and other sports leagues aren’t going to fight back.
Your active users probably aren’t growing exponentially. That’s okay. What’s not okay is deluding yourself with the illusion of month-over-month, exponential growth.
When you fudge your growth models, you’re not just deluding yourself and your team. You’re not just giving potential investors the signal that you don’t know what you’re doing.
You’re setting yourself back in the search for a real, repeatable engine of exponential growth.