Daphne Tideman, growth advisor and consultant for subscription apps, explains why most retention problems are actually activation problems, how to distinguish vanity activation metrics from ones that predict real retention, and why the aha moment should start in your ads, not just your product.

Daphne walks through her evolution from treating activation as a simple funnel step to seeing it as a layered, behavioral process spanning the first 7 to 30 days. She shares real examples from growth audits where onboarding completion rates looked great but users vanished by day two, and breaks down the "time to first value" vs. "time to core value" framework for thinking about activation in stages. She also makes a case for monthly subscriptions as a faster learning tool for startups, and explains why revenue is a terrible North Star metric.

What you'll learn:

Why onboarding completion is often a vanity metric that hides activation failures
How to identify whether your retention problem is actually an activation problem
Why "any action vs. no action" comparisons overstate the value of weak activation metrics
How to build mini aha moments into onboarding before the paywall
How to use the "time to first value" vs. "time to core value" framework
Why monthly subscriptions can help startups learn faster about activation
How to test whether an activation metric is predictive or just correlated
When user interviews beat quantitative analysis for defining activation
Why extending onboarding can drop completion rates but improve retention
How to diagnose activation vs. retention vs. acquisition problems
Why revenue as a North Star metric leads teams to extract value instead of create it

Key Takeaways:

Onboarding completion is a vanity metric. An app had over 90% onboarding completion on both platforms, but most users were gone by day two. The onboarding was too short and easy to click through. When they extended it and built in value-delivering steps before the paywall, completion dropped but retention improved.
Your retention problem is probably an activation problem. For most apps, losing users in the first 30 days isn't a retention failure. It's an activation failure. Daphne argues we even mislabel it: "day two retention" and "day seven retention" describe periods when you're still activating users, not retaining them. True retention problems show up when users were active early but trickle off later.
Activation should start in the ad. Showing the job to be done and the transformation in your ad creative builds trust before users even open the app. A coding app's best performing ad showed someone coding in a lift, making viewers think "I could find time for that too."
Correlation isn't causation in activation metrics. Any action will always look better than no action. The real work is finding which behaviors, at what volume and timing, predict retention across cohorts and channels.
Mini aha moments beat one big moment. Instead of trying to engineer a single big aha moment (which is often technically difficult), build multiple smaller moments of perceived value. These can be as simple as a personalized plan, a visual showing the outcome, or a first small win before the paywall.
Monthly plans help you learn faster. For startups without much data, monthly subscriptions force users to make a renewal decision every month, which generates faster signal on who is truly activated vs. who is coasting on inertia.
Revenue is a terrible North Star metric. It pushes teams toward extracting value from users rather than creating it. Activation and usage metrics better align the team's incentives with user outcomes.

Links & Resources

Daphne Tideman's Growth Ways newsletter: https://growthwaves.substack.com/
Daphne Tideman on LinkedIn: https://www.linkedin.com/in/daphnetideman/

00:00 Intro and Daphne's path from e-commerce to app growth consulting
01:20 How activation thinking evolves from 2D to 3D
04:20 Common activation mistakes: oversimplifying and picking the wrong metric
05:50 Why standard metrics weren't predicting retention
07:20 Onboarding completion as a vanity metric: 90% completion, gone by day two
10:20 Activation vs. monetization: which to fix first
13:20 Building mini aha moments into onboarding and ads
17:50 User interviews and the role of emotions in activation
20:20 Your retention problem is actually an activation problem
23:20 Time to first value vs. time to core value framework
27:20 How to test whether an activation metric is real or vanity
29:20 Starting with user interviews vs. data when you lack scale
31:50 Correlation vs. causation: finding the right activation threshold
34:20 Learning from failed experiments
36:50 Diagnosing activation vs. retention vs. acquisition problems
39:20 Why activation problems are more common than retention problems
42:20 Matching subscription models to use cases
44:50 Biggest activation mistake apps make right now
45:50 Lightning round: pricing wins, hot takes, and best activation results