It depends on your content and brand strength. Hard paywalls work well for apps with strong brand recognition or unique content (like premium meditation or exclusive news). Soft paywalls work better for discovery-driven apps where users need to experience value first. Test both — many apps find that a soft paywall with a free trial outperforms a hard paywall by 30-50%.
Enough to demonstrate your core value but leave users wanting more. A common framework: give away 10-20% of your content library for free. The free content should be genuinely useful (not watered-down) so users trust that paid content is worth it.
If done poorly, yes. Aggressive gating that blocks users before they understand your value drives uninstalls. But thoughtful gating that introduces premium content after users are engaged actually increases both engagement and revenue. The key is timing — let users fall in love with your app before asking them to pay.
The act of ending a subscription, either by the user or automatically due to billing failure. Understanding cancellation timing and reasons is key for designing retention strategies, deflection flows, and win-back campaigns.
A short feedback form presented during the cancellation process to understand why a user is choosing to leave. These insights inform product improvements, pricing strategy, and targeted win-back efforts.
The percentage of subscribers who cancel or do not renew their subscription over a given time period. Churn can be voluntary or involuntary and is a core metric for measuring retention health and forecasting revenue growth.
The ratio of users who click on a specific call-to-action (e.g., email link, push notification, paywall button) versus those who viewed it. CTR is a key engagement metric for evaluating creative performance and funnel effectiveness. Click-through-rate originated in the email and banner ad world, where everything was on a desktop. With mobile, some companies now call this same metric tap-through-rate since people are tapping on their phone vs clicking on desktop, but at the end of the day it's really the same type of measurement.
A method of analyzing user behavior by grouping users based on shared characteristics — most often the date they first installed or subscribed. This allows teams to compare retention, LTV, and monetization trends across cohorts over time.
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