Mobile Analytics Guide with 50+ Resources for App Makers
The entire mobile analytics field is dedicated to the nuances of user behavior. From acquisition and retention to inactivity and funnel analysis, businesses are investing heavily in capturing and measuring metrics about their mobile users.
The problem? The web is full of sales pitches and not enough quality information about analytics for mobile apps. We’re aiming to change that. The resources below have been carefully curated from our own experience and that of a few trusted individuals and businesses. This is the ultimate resource for learning more about app analytics from A to Z.
We’ll be updating it as we find other great information.
What is Mobile Analytics?
Mobile analytics is the practice of collecting user behavior data, determining intent from those metrics and taking action to drive retention, engagement, and conversion. The field includes the mobile web, but tends to focus on analytics for native iOS and Android applications.
Analysis that used to happen in Excel and SQL has largely been replaced by a handful of tools that make adhering to analytics best practices significantly easier. Consumer and business applications tend to face the same set of challenges in their mobile marketing and retention, so this guide is designed to address both.
Getting Started with Mobile Analytics
Before you dive into the mobile data world it’s worth understanding where some of the most advanced mobile companies get started. A good foundation will inform the rest of your mobile strategy, so don’t overlook the basics. The articles in this section are designed to set the stage for the rest of the resources in this guide.
App crashing and poor performance lead to bad reviews and serious churn. Here are some suggestions to monitor and address mobile app performance.
How to Analyze Mobile User Behavior
From 30,000 feet, analytics for mobile is simply listening to the data collected in your app. User behavior analysis is more complex in practice, of course, but it’s often overcomplicated. Our approach to app analytics is straightforward and data-informed. Here are some of the world’s best resources for analyzing the troves of data you can collect about your mobile users.
The core of behavioral analytics is events. Here’s how to think about creating events that align with your marketing and product goals.
Knowing when a user started is important, but the actions they take in your app give you a much deeper understanding of your users and how they interact with your product. That’s where behavioral cohorts come in.
Here’s a simple way that analytics can uncover the key to your users’ behavior and help you with app growth.
You’re competing to chart in the App Store and grab the attention of your potential users—and the competition’s never been tougher.
If you haven’t stopped caring about vanity metrics—unique views, app downloads, registrations, etc.—you should.
Hubspot’s senior manager of growth and analytics Dan Wolchonok explains how to collect useful feedback from your mobile users.
Justin Mares discusses a three-phase approach to building a product. It’s written for any software business, but has especially useful implications for mobile apps.
User Retention: The Foundation of Mobile Apps
Retention is notoriously hard to measure and its importance is even harder to quantify. A strong retention strategy creates a healthy business and a mobile app that people love using. Retention analytics is an ongoing and evolving challenge for every app maker. Here are some of the best examples and resources from our years of experience in the trenches.
QuizUp became the fastest growing game in App Store history. Here’s how they retain more than 3.5 million users.
Why do most startups still concentrate all their resources on acquisition? Because it’s a cakewalk compared to retention. But it’s time for that to change.
Cohort analysis is how you’ll identify how well your users are being retained and the primary factors that will drive growth for your app.
The average Android app loses about 80% of its daily active users within the first three days, and about 90% by the first month. Here’s how to change that.
Growth-oriented companies know the importance of holding on to existing users just as well as they know the cost of acquiring them. So what is their biggest hurdle when it comes to diagnosing and improving user retention?
Cleaner data leads to better analysis, says Dan Wolchonok. We couldn’t agree more.
Apptimize explains some overlooked best practices that can help you get more out of your current mobile app and its users.
Your ability to retain customers is often a reflection of your entire business, writes Appcues’ Ty Magnin. Here’s a lean, efficient way to think about retention.
Mobile Analytics Case Studies
Implementing a data-informed analytics process for mobile apps is easier said than done. With that in mind, we took a look at how a few different businesses solved their own onboarding and retention challenges with data and careful experimentation. Like web analytics, the best mobile analytics strategies are straightforward and flexible—here’s how the pros do it.
When your product doesn’t have traction, you might want to try rebranding.
Every time Tinder facilitates a successful match and that match leads to a meaningful relationship, they lose two customers. Here’s how they approach retention as both a goal and an enemy.
The key to building a really great product painkilling, says Nir Eyal. Does your product scratch an itch that your users have?
Square has a suite of products that rely on a data-informed culture and a handful of key metrics.
Getting users to complete their first purchase is a key to success for any ecommerce app. Instacart relied on analytics to identify all the ways to optimize the process.
Avoiding Common Analytics Mistakes
Bad data, bias, misinterpretation—there are so many ways that mobile app metrics can lead you astray if you aren’t careful. Here are some posts to help you identify all the mistakes that you can (and should) avoid to make the most of your app’s analytics.
As data-driven as we try to be, all organizations are essentially and necessarily human-driven. And humans, naturally, are riddled with irrationality and biases.
You may think you have a handle on your user behavior, but unless your analytics are fully cross-platform you’re not going to be getting the full picture.
How do you explain apps that soar in popularity for a day, then tumble back down into obscurity? Data, of course.
Fear, uncertainty, and doubt (FUD) is all too common in the mobile analytics world. Here are a few things to think about when you hire your next analytics vendor.
Few businesses actually understand what it means to have a fully integrated culture of data.
The biggest challenge in understanding your analytics today isn’t the data itself or how it’s presented. It’s adjusting for bias.
Andrew Chen explains why mobile apps understand acquisition to succeed but not retention.
Avinash Kaushik on why numbers rarely tell the truth. Skepticism is every analysts’ best friend.
Great products aren’t enough writes Andrew Chen. Here’s a new way to think about launching and growing an app.
Mobile Analytics Tools of the Trade
To actually start collecting data about your users, gathering insights, and executing on them, you need the right tools. Here are five that we recommend for any high-performance mobile analytics toolchain.
Segment – for tracking events and moving data
Redshift – for data warehousing
Google Tag Manager – for tag management
Apptimize – for A/B testing and feature flags
Amplitude – product analytics for web and mobile products, including cross-platform tracking
Mobile Analytics Experts to Follow
If you want to get better at building growth, you need to constantly be learning from those who came before you. With these podcasts and blogs, you’ll be getting new perspectives on your own challenges and learning about what works (and what doesn’t) from the experts in the field.
5 Best Analytics Podcasts
Here are our favorite podcasts about analytics for the times you’re driving, operating heavy machinery, or doing something that requires two hands and focus (like eating ice cream).
RAMP By InsightSquared
The Digital Analytics Power Hour
Analytics & Growth Blogs