How to Detect App Uninstalls (Technical Guide)

Uninstall tracking is harder than it should be. iOS and Android both make it opaque on purpose to protect user privacy. But detecting uninstalls is critical because it lets you trigger recovery flows while the app is still fresh in the user's memory.

Here are the four methods that work in 2026.

Method 1: Silent push token invalidation

How it works: Your server periodically sends invisible push notifications ("silent pushes") to every registered device. If the push delivery fails because the token is invalidated, the device likely uninstalled the app.

Accuracy: 70-85%. Users who disabled push notifications register as uninstalls (they didn't uninstall, they just muted you). The false positive rate can be significant on iOS.

Latency: 24-48 hours from actual uninstall to detection.

Cost: Effectively free if you already have push infrastructure. Requires some engineering to set up the periodic silent push job and the token invalidation handler.

Best for: Teams with engineering capacity who want DIY tracking without paying for an MMP.

Method 2: Mobile measurement partner (MMP) uninstall tracking

How it works: Adjust, AppsFlyer, and Branch offer uninstall detection as part of their attribution platform. They combine silent push, network attribution signals, and other signals to produce higher-accuracy uninstall events.

Accuracy: 80-90%, higher than DIY silent push because they use multiple signals.

Latency: 24-72 hours from actual uninstall.

Cost: $2K-$15K/month depending on install volume. This is often the biggest line item in a mobile analytics stack.

Best for: Mobile apps at scale (100K+ MAU) where the accuracy and integration benefits justify the cost.

Method 3: Behavioral retention proxies

How it works: You don't try to detect uninstalls directly. Instead, you define "effective uninstall" as "no activity for X days." Common thresholds: 14 days for high-frequency apps (social, gaming), 30 days for mid-frequency (fitness, productivity), 60 days for low-frequency (travel, banking).

Accuracy: 100% correct as a category ("this user isn't engaging") but includes users who still have the app installed and might return.

Latency: By definition, matches your threshold. 14-60 days.

Cost: Free. Just requires session tracking in your analytics.

Best for: Teams that need reliable retention numbers but don't require true uninstall detection. Also useful as a fallback when other methods miss users.

Method 4: Attribution + return-user detection

How it works: Track when a previously-installed user reinstalls (via attribution). If a user reinstalls after 30+ days, they almost certainly uninstalled and re-installed.

Accuracy: Very high for the users it catches, but only catches uninstalls that convert to reinstalls (a small fraction of total).

Latency: Effectively zero when the reinstall happens.

Cost: Requires an MMP for attribution tracking.

Best for: Measuring recovery flow effectiveness, not detecting uninstalls broadly.

The stack most mobile teams end up with

For most mobile apps at scale:

• MMP (Adjust or AppsFlyer) for primary uninstall detection - most accurate, integrates with attribution
• Retention proxy as fallback and for reporting - catches users the MMP misses
• Attribution for reinstall detection and recovery flow measurement

For pre-scale mobile teams (under 100K MAU), skip the MMP and use silent push + retention proxy. It is a fraction of the cost with 80-90% of the value.

How to trigger recovery flows

Detection is only useful if you act on it. Set up a webhook that fires when an uninstall is detected:

1. MMP or silent push job detects uninstall
2. Webhook fires to your ESP (Customer.io, Iterable, Braze) or CDP (Segment, RudderStack)
3. ESP enrolls the user in the offboarding email sequence
4. First email sends within 24 hours of detection

The specific sequence to send is covered in the offboarding email guide. Post-uninstall recovery rates are 2-5%. Meaningful when you're losing thousands of users a month.

Accuracy limits to be honest about

All methods have blind spots. Set expectations accordingly:

• Silent push false positives (push disabled but app still installed): 5-15%
• Detection latency: 24-72 hours minimum
• Users who wipe their device and reinstall are undetectable as "the same user"
• iOS 14+ privacy features reduced attribution accuracy 20-30%

Perfect uninstall detection does not exist. What exists is "good enough to trigger recovery flows and understand cohort behavior."

Next steps

For the broader mobile retention playbook, see the mobile apps guide and why users uninstall your app. To score your uninstall detection and recovery setup, take the Churn Health Check.