Click-to-Install Timing Benchmarks 2026: iOS vs Android

Across 250k+ matched click-install pairs processed on Linkrunner over the past month, the median time from click to install was 2.4 minutes on Android and 37 minutes on iOS. The 90th percentile stretched to roughly 20 days on Android and 18 days on iOS.

That five-hundred-fold spread between median and tail is what most attribution-window settings ignore. It is also the reason most teams cannot answer the simple question "how long does our attribution actually take?" without pulling raw data and computing it themselves.

This post lays out the benchmark, explains why Android resolves so much faster than iOS, and shows you how to validate your own click-to-install distribution before you change a window setting.

What Click-to-Install Time Actually Measures

Click-to-install time is the elapsed time between a user clicking a tracked ad and the resulting install being recorded by the attribution platform. It is not the same as time-to-first-session, time-to-activation, or time-to-revenue.

What goes into the measurement:

• Click event timestamp from the ad network or your click router
• Install event timestamp from SDK first open, Install Referrer broadcast, or SKAN postback
• The matching logic that connects them, deterministic via referrer or device id, probabilistic via fingerprint

What can distort the number:

• Clock skew between the click server and the device
• ATT consent prompts on iOS that delay the first SDK open
• Slow store loads, paused downloads, devices on patchy connections
• Reattributions for users who already had the app, where the "click" is recent but the "install" is months old

For this benchmark we excluded reattribution events and capped the delta at 30 days, which is the longest click attribution window most ad networks honour.

The Benchmark: 250k+ Matched Click-Install Pairs Across 80+ Apps

Headline figures from the rolling 30-day window ending 27 April 2026:

Methodology note: matched click-install pairs across 80+ Linkrunner projects spanning gaming, fintech, eCommerce, and subscription apps. Project-level identifiers were stripped before aggregation. Reattribution events excluded. Window: April 2026.

Three observations the table does not capture:

• The tail is dominated by store-page browsers who tap an ad, get distracted, and complete the install days later
• Median Android numbers shift heavily based on whether Install Referrer is configured cleanly; a broken Install Referrer setup can push the median past 24 hours on its own
• iOS median is dragged up by ATT consent flows and delayed first opens after fresh installs

Why Android Resolves Faster Than iOS

Android resolves faster because Google Play Install Referrer delivers click context within seconds of first open, while iOS depends on slower probabilistic matches and delayed SKAN postbacks.

The mechanics behind the gap:

• Install Referrer broadcasts the click metadata to the SDK as soon as the app opens for the first time. For paid Android installs with a clean integration, click and install timestamps line up almost instantly.
• iOS has no equivalent. SKAN 4.0 postbacks arrive 24-72 hours after install. Probabilistic fingerprinting needs the device to open the app and complete a match before the install registers. ATT consent prompts on first launch add another delay.
• The long tail looks similar on both platforms because store-page browsing behaviour is human, not platform-specific. Tap, browse, get interrupted, install later.

If your iOS median sits above two hours, fingerprinting is probably falling back to the slower path because the deterministic match window expired. If your Android median sits above one hour, Install Referrer is almost certainly misconfigured; Linkrunner's Meta Install Referrer setup doc covers the most common breakage modes. For broader context on how privacy changes reshaped both timelines, our post-IDFA attribution guide and the SKAN 4.0 decoding framework walk through the underlying mechanics.

What This Means for Your Attribution Window Settings

The benchmark argues for two adjustments most teams have not made:

1. A 24-hour click window is too tight on iOS. Median iOS click-to-install is 37 minutes, but the long tail extends to days. A one-day click window misses real conversions in subscription, travel, and gaming apps where users browse before installing. Move to 7 days minimum on iOS.
2. A 30-day click window inflates view-through credit on Android. Android resolves the vast majority of legitimate clicks within hours. Anything credited at days 5-30 is more likely a returning user, organic install, or fingerprint mismatch than a genuine click-driven install. Tighten to 7-14 days unless your vertical has long consideration cycles.

Vertical-specific guidance:

• Gaming and casual apps: 7-day click window on both platforms
• Subscription and trial-led apps: 14 days on iOS, 7 days on Android
• eCommerce and food delivery: 1-3 day click window matches actual impulse-driven behaviour
• Travel and hospitality: extended windows (up to 30 days) make sense given multi-week consideration

For a deeper treatment of how to set windows by vertical, see our attribution windows guide.

How to Validate Click-to-Install Timing in Your Own MMP

You can pull this from any MMP that exposes raw exports. The minimum-viable cut:

1. Export installs from the last 30 days with click timestamp, install timestamp, project id, and platform
2. Compute install_time minus click_time in seconds for each row
3. Calculate median and 90th percentile per platform
4. Compare against the benchmark above

Red flags worth investigating immediately:

• Android median above 24 hours: Install Referrer is probably broken
• iOS median above 6 hours: fingerprinting fallback is dominating, or ATT prompt placement is delaying first open
• P90 above 30 days: reattribution events are leaking into your fresh-install distribution and skewing the long tail

Platforms like Linkrunner expose this distribution in the dashboard alongside the cross-customer benchmark, which avoids writing SQL or stitching exports by hand. If your team prefers to live in raw data, our attribution discrepancy diagnostic guide covers the full troubleshooting path, and the list of underused MMP metrics that predict churn and LTV names two timing signals worth pulling alongside this one.

FAQ

What counts as "the click" if a user taps the same ad twice?

Most MMPs credit the most recent click within the attribution window. If a user taps on Monday and again on Wednesday before installing, the Wednesday click owns the install.

Is a longer click-to-install time a sign of fraud?

Not by itself. Fraud often looks like the opposite, with click-to-install times of a few seconds because bots simulate click and install in the same script. Outlier P90s are usually consideration-cycle behaviour, not fraud.

How does view-through attribution change these numbers?

View-through skips the click entirely, so it does not appear in this benchmark. View-through windows are typically 24 hours and need a separate measurement workflow.

Does Apple Search Ads click-to-install time differ from other iOS networks?

Apple Search Ads tends to resolve faster than other iOS networks because the click and install both happen inside the App Store. Median click-to-install for ASA traffic looks closer to the Android pattern.

Should this benchmark replace the default attribution windows in my MMP?

No. Use it to challenge your defaults, then validate against your own raw data before changing settings. Window changes affect comparability across historical campaigns and should be made deliberately.

What to Do Next

The single highest-value action this week: pull a click-to-install distribution from your MMP raw export, compare your median against the benchmark, and flag any platform where the gap is more than 10x. That gap is almost always an Install Referrer misconfiguration on Android, an ATT consent flow placement issue on iOS, or a reattribution event leaking into your fresh-install data.

If you would like to see your own click-to-install distribution alongside the cross-customer benchmark without writing SQL, request a demo from Linkrunner and we will walk you through the timing dashboard for your own project.