About this chart

The Subscription Reactivations chart tracks how many previously churned or terminated subscriptions have been re-started by the same user over time. It helps you measure the effectiveness of win-back campaigns, detect organic re-engagement patterns, and understand whether former subscribers are returning to your app.

A reactivation occurs when a subscription transitions from a non-active state back to an active state. This includes voluntary re-subscriptions after cancellation, but also billing retry recoveries — when a subscription is suspended due to a payment failure and later restored by the app store after a successful retry. The only exception is grace period recovery, where the subscription never actually leaves the active state and is therefore not counted as a reactivation.

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Important: Accuracy depends on subscriber history import

Purchasely can only identify a reactivation if it knows the user previously held a subscription. This requires the complete subscription history of your users — including lapsed subscribers — to be imported into the platform.

If this full import has not been performed, Purchasely may not recognize that a user is a returning subscriber and could count their subscription as a new activation instead of a reactivation, leading to understated reactivation numbers and overstated activation numbers.

This is the most common reason for discrepancies between Purchasely's reactivation metrics and the ones reported by the App Store or Google Play, which by definition have the complete transaction history for every user.

⚠️ Change from dashboard v1: counting subscriptions, not subscribers

The previous version of this dashboard counted unique subscribers (users). Dashboard v2 now counts unique subscriptions, each identified by a unique subscription ID.

This changes the numbers in two ways:

• Restored subscriptions across devices: In v1, when a subscription was restored on a new device by a different anonymous user, it was counted multiple times — once for each anonymous user associated with it. In v2, the subscription is counted only once regardless of how many devices or anonymous users it passes through.
• Multiple subscriptions per user: In v1, a user holding two active subscriptions simultaneously was counted once (one user). In v2, each subscription is counted individually, so the same user contributes two to the total.

Example: Alice holds both a monthly Music plan and a yearly Premium plan. In v1, Alice counted as 1 subscriber. In v2, she counts as 2 active subscriptions. Conversely, if a single subscription was restored across 3 anonymous devices in v1, it appeared as 3 subscribers — in v2 it correctly counts as 1 subscription.

How to read the chart

The chart displays a bar chart with overlaid trend lines. Each bar represents a time period (day, week, or month) depending on the selected granularity.

Below the chart, a data table lists each period with its corresponding reactivation count for precise reference.

Controls

Show

Filter reactivations by subscription type:

Grouped by

Break down reactivation data by a dimension to compare segments side by side:

Granularity

Use the Daily / Weekly / Monthly selector to control the time resolution of each bar.

• Daily — One bar per day. Best for spotting short-term spikes after a specific campaign or event.
• Weekly — One bar per week. Good for smoothing out day-to-day noise while retaining detail.
• Monthly — One bar per month. Best for long-term trend analysis and executive reporting.

Filters

Click Filters to narrow the data. You can combine multiple filters.

Common use cases

• Measure win-back campaign performance — After launching a win-back push notification or email campaign, use the daily granularity to check for a spike in reactivations in the days following the campaign. Group by Audience to see which user segments responded best.
• Compare reactivation quality across offer types — Use the Show dropdown to compare Free vs. Paid vs. Full-price reactivations. A high proportion of full-price reactivations suggests strong product-market fit, while heavy reliance on free trials may indicate users are not yet convinced of the value.
• Identify platform differences — Group by Platform to see if iOS and Android users reactivate at different rates. Differences may point to platform-specific billing behaviors or varying effectiveness of re-engagement surfaces.
• Evaluate paywall effectiveness for churned users — Group by Screen or Placement to determine which paywall designs or in-app locations are most effective at converting returning users. This can inform dedicated win-back paywall strategies.
• Track seasonal re-engagement patterns — Use monthly granularity over a long date range to spot seasonal trends. Some apps see reactivation spikes around New Year, back-to-school, or other events relevant to their user base.
• Benchmark reactivation trends against churn — Monitor the trend line and average line together. A rising trend line alongside stable or declining churn suggests your retention and win-back efforts are working. If both reactivations and churn are rising, you may be cycling the same users through repeated churn-and-return loops.

Frequently asked questions

What counts as a reactivation?

A reactivation is recorded whenever a subscription transitions from a non-active state back to an active state. This includes: voluntary re-subscriptions after cancellation or expiration, billing retry recoveries where the subscription was suspended before being restored, and any other scenario where a previously inactive subscription becomes active again. The only case that does not count as a reactivation is a grace period recovery, because the subscription never leaves the active state during the grace period.

Does a billing retry recovery count as a reactivation?

Yes. When a subscription payment fails and the subscription is suspended (e.g., account hold on Google Play, or equivalent on the App Store), the subscription leaves the active state. When the store successfully retries the charge and restores the subscription, this transition from non-active to active is counted as a reactivation.

The only exception is grace period recovery: during the grace period, the user retains access and the subscription remains active while the store retries the payment. If the payment succeeds during this window, no reactivation is recorded because the subscription was never suspended.

Why might reactivation numbers differ between Purchasely and the app stores?

Purchasely identifies a reactivation by checking whether the user previously held a subscription. To do so accurately, it needs the complete subscription history of your users — including lapsed subscribers — to be imported into the platform. If this full import has not been performed, Purchasely may not know that the user is a returning subscriber and could count the subscription as a new activation rather than a reactivation. This leads to understated reactivation numbers (and overstated activation numbers) compared to the App Store or Google Play, which by definition have the complete transaction history for every user.

Why are reactivation numbers on Android less accurate than on iOS?

The App Store provides an API that allows fetching the full transaction history for any user, including lapsed subscriptions. This makes it possible to import your complete iOS subscriber base into Purchasely and accurately distinguish reactivations from first-time activations.

Google Play, however, does not expose lapsed subscription history through its APIs. If a user's previous subscription expired before they were known to Purchasely, there is no way to retrieve that past transaction. Purchasely will then count their next subscription as a new activation rather than a reactivation.

This is a Google Play platform limitation, not a Purchasely one. In practice, reactivation metrics on Android may be understated compared to iOS, where full history import is possible.

Are high reactivation numbers always a good sign?

Not necessarily. A healthy reactivation rate shows that your product has lasting appeal and your win-back efforts are effective. However, if reactivations are growing in parallel with churn, it may indicate a revolving-door pattern where the same users repeatedly churn and return. In that case, focus on understanding why users leave in the first place rather than celebrating their return.

Can a single user generate multiple reactivations?

Yes. If a user churns, reactivates, churns again, and reactivates again, each return is counted as a separate reactivation event. Monitoring users with multiple reactivations can help you identify pricing or value-perception issues.

Why do I see a spike in reactivations without running any campaign?

Organic reactivations can happen for several reasons: app store featuring, seasonal interest in your app category, OS-level subscription management prompts reminding users of lapsed subscriptions, or external events that make your product relevant again. Group by Country or Platform to see if the spike is concentrated in a specific segment.

How should I use the trend and average lines?

The average line gives you a baseline for what "normal" reactivation volume looks like over the selected period. The trend line shows whether reactivations are generally increasing or decreasing. If the trend line sits above the average, reactivations are accelerating. If it dips below, they are slowing down. Use both together to distinguish a temporary spike from a sustained improvement.