Founders' letter
Charlie Hopkins-Brinicombe
Co-founder (Sales & marketing things)
Jason Louro
Co-founder (Technical things)
Since the rise of coding agents, the number of new apps launching on the stores has exploded. Pre-2025, the number of iOS apps released each month grew 2-3% TTM YoY. Now, it's more like 25%, with no sign of slowing. [1]
However, the demand for apps has not kept pace. The market is flooded with competition, and users are willing to switch apps just as fast as they release new AI features. Every dollar spent on acquisition, and every new user it brings, is now more valuable than ever.
At the same time, the price of attention has never been higher. In 2026, the average US adult received 46 push notifications per day with an average CTR of just 3.4%, showing how traditional engagement channels are becoming more saturated and less effective. [2]
The growth equation has shifted from acquisition to retention. Today, the most successful apps are not just those that can acquire lots of users quickly, but are the ones that can find novel ways to keep users coming back without relying on traditional engagement channels.
Trophy sits at the frontier of this new battleground, providing app builders with the toolkit to power native, in-app gamification experiences that build the kind of real habit loops that notification sequences cannot.
We put this report together to show how apps are embracing this new reality using gamification to build habits that stick, and to highlight the opportunities for app builders to use it to win in this new era.
Charlie & Jason
Sources: [1] Sensor Tower, [2] Business Of Apps.
Methodology
Overview of the dataset
The data in this report is drawn from the apps using Trophy's platform, drawing on a combined total of over 1.5M users and over 250M individual user interactions.
- Scope: Qualifying apps that use Trophy above a minimum usage threshold. Some data is limited to the apps that use specific features relevant for the analysis.
- Time frame: The 12 months ending August 2026.
Anonymization and data privacy
All figures are anonymized and aggregated to prevent any single app from being identifiable. Segments that are too small to publish safely are omitted or rolled into a larger group so no single app can be inferred.
Statistical practices
Unless noted, charts will use median and percentile views as follows:
- Median (p50): the midpoint of the distribution.
- 75th percentile (p75): the value below which 75% of the dataset falls.
- 95th percentile (p95): the value below which 95% of the dataset falls.
- 99th percentile (p99): the value below which 99% of the dataset falls.
On occasion we use proxy metrics like 'achievement difficulty' to provide a measure of a feature that makes sense in the context of aggregate data. Where such metrics are used we clearly explain the meaning and the context.
Causation & correlation
Particular attention has been paid to ensure fair reporting in a way that does not causally imply a relationship between the behavior of a specific feature, and a certain outcome.
Key insights
34%
Initial streak loss rate
34% of new users lose their streak between 3 and 5 days after sign up.
2.5x
Streak impact on daily activity
Typical daily activity of users with at least a 15-day streak is 2.5x higher than those who only reach a 2-day streak in the first 30 days.
4.5x
Freeze impact on streak length
Streak freezes increase average streak length by 4.5x after 21 days, but have no impact on short-term streak length.
3.4x
Rise in leaderboard competitiveness
Competition on repeating leaderboards is 3.4x higher than on perpetual leaderboards with the top 10% ranks changing 8x more often.
Report preview
Streaks and habit loops
Trophy measures a streak as two or more consecutive days of 'streak-eligible activity' (activity that is configured to count towards a streak).
Streak length after signup
The chart shows streak length percentiles on each day up to 30 days after user sign up. The dashed line represents an unbroken (or 'perfect') streak.
Percentiles of streak length by day after signup
What stands out
The data shows habitual usage patterns are hard to maintain with the median streak length consistent at 3 days and just 10% of users reaching a streak of 10 days or more. Perfect streaks are reserved for the top 1% of users who start strong but also tail off by day 22.
Key takeaways
- Set realistic expectations for your streaks feature, and accept that most users will not achieve a perfect streak.
- Users who maintain long streaks are outliers, identify them, listen to them, and turn them into advocates.
First streak survival
The chart shows the share of streaks that reach certain lengths before loss. Only first streaks after sign up are counted. Later streaks after a loss are not counted.
Share of first streaks by length
What stands out
The data shows that just over half (51.2%) of first streaks survive to day 3, dropping harshly thereafter. Zero first streaks survive by day 30.
Key takeaways
- Focusing on day 3 streak survival will have the biggest impact on overall first streak length. This is where the steepest loss occurs and where the largest gains can be made.
When streaks break
The chart shows the share of streak losses by ISO 8601 weekday.
Share of streak losses by weekday
What stands out
The data shows that Wednesday accounts for 21.1% of losses, more than any other weekday, followed by Friday at 18.5%. Sunday accounts for 6.7%, the lowest loss rate.
Key takeaways
- Teams should measure and understand their unique streak loss patterns to improve average streak length.
- Streak loss prevention mechanics such as reminders and notifications should be optimized for the weekdays with the highest loss rates.
Achievements and milestones
The data includes two types of achievements. First, Trophy milestone achievements unlock when a user hits a threshold of activity against a specific user interaction, following a ladder structure with each rung representing a higher threshold of activity. Second, custom achievements are defined and managed by apps, only tracked in Trophy upon completion.
Time to first unlock by achievement type
The chart shows the share of users by when they first unlock a Trophy milestone achievement versus a custom achievement in the first 30 days after sign up.
Share of users by time to first achievement unlock
What stands out
The data shows 43.1% of users unlock a custom achievement on day 1, versus 18.2% who unlock a Trophy-powered milestone. After day 1, custom first-unlocks stop; milestone unlocks continue through the month. 36.6% unlock a milestone in the first 30 days.
Key takeaways
- Most apps choose to front-load custom achievements to encourage early engagement and stickiness, based on actions linked to onboarding tasks or other critical user interactions.
- Users steadily unlock Trophy milestone achievements from day 2 onwards enforcing progression paths.
Leaderboards and social competition
Trophy leaderboards rank users against each other. Repeating leaderboards reset on a schedule. Perpetual leaderboards are all-time rankings.
Competitiveness by leaderboard type
The chart compares the competitiveness of repeating and perpetual leaderboards.
Displacement and winner retention by leaderboard type
What stands out
The data shows perpetual leaderboards are the least competitive: only 5.4% of users are displaced, and 91.2% of winners are still there the next day. Repeating leaderboards see more frequent new winners and increased displacement.
Key takeaways
- Repeating leaderboards help new users compete through regular ranking resets, keeping leaderboards fresh and increasing displacement.
- Perpetual leaderboards are less efficient at promoting a competitive environment, but are still useful in cases like streak rankings that aren't meant to be reset.
Winner displacement by leaderboard type
The charts follow users who were in the top 10% of a leaderboard, showing how their position changes over the next 7 days. Higher percentiles are closer to first place.
Perpetual winners over the next 7 days
Repeating daily winners over the next 7 days
What stands out
The data shows perpetual winners stay at the top: among those still listed, the median is 5th the next day and 3rd after 7 days, and 99% remain in the top tenth the next day. On repeating daily boards the median winner falls to 54th the next day, and only 17% are still in the top tenth.
Key takeaways
- Repeating daily leaderboards rotate winners more frequently, making them more competitive than perpetual leaderboards.
- Repeating leaderboards ensure new users have a chance to compete with existing users.