Harnessing Data to Reduce User Churn

© 2016 Apteligent • www.apteligent.com

Harnessing Data to Reduce User Churn • January 2017


Agenda

Where is this data coming from?

How Crashes Impact Churn

mCommerce Example

Andrew LevyCo-Founder & Chief Strategy [email protected]@andrewmlevy


About Apteligent

Data Generated from Tens of Thousands of Apps

Userflow Failure Network Services Error Crashes Slow apps

Apteligent Data Platform


About Apteligent

Data Generated from Tens of Thousands of Apps

Transaction Failure Network Services Error Crashes Slow apps

Apteligent Data Platform Optimize Business Result

Get Ecosystem Insight

Manage App Lifecycle

• Retention/Churn

• Detect Issues• Determine root

cause• Assess impact

• Prioritize• Manage releases• Monitor vital signs

• Benchmarks and trends

• Carrier QoS

• Device adoption• Bespoke analysis

• Engagement• Monetization• Data ingestion

• Correlation• Prediction• Recommendation


How do you define

Retention?

Rolling Retention

Nth Day Retention

“Hard Churn”

Day-1 Retention: “Did they come back the next day?”

Churn is the inverse of a type of retention (closer to rolling retention)

CohortsApp Loads + Crash onlyThis report did not yet look at “first time users”


Relationship Between App Loads and Crashes : Churn


Per User Crash Rate

70% OF USERS THAT HAVE A CRASH EXPERIENCE ONE EVERY OTHER TIME THEY LOAD THE APP


Poor Performance Drives a Huge Increase in Churn

• Crashes increase churn by as much as 534%

• Users are up to 8x less likely to return the next day after a crash

• Revenue critical App Store categories like Shopping and Finance are very susceptible


App Store Categories Behave Differently

Revenue Critical Categories At the Top

Rolling Retention (“hard churn”) Nth Day Retention (“return next day”)


Rolling Retention vs N-Day Retention

Crashes Have Immediate Engagement Impact and Negative Long Term Impact on Churn


Example mCommerce Scenario

It is much more expensive to acquire a new user than to retain an existing user, anywhere from 5x to 25x

• Customer acquisition cost is $50 x 600 means $30,000 just to win back another 600• Assume $300 LTV, you just lost $180,000 in future revenue• If you had a goal to gain 300 customers, and you’ve lost 600, you’ve just tripled

your customer acquisition cost to reach that goal

Quickly isolated the issue, spent X hours of an engineers time (and $Y dollars, much less than the numbers outlined above)

A crash just caused your app to lose 600 customers


“Don't Let Your Apps Crash & Churn”Questions?

Feel free to contact me:[email protected]

Data & Analytics

Harnessing Data to Reduce User Churn