> For the complete documentation index, see [llms.txt](https://docs.amply.tools/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.amply.tools/recipes/feature-feedback-capture.md).

# Feature feedback capture

Ask a targeted feedback question after a user has used a new feature twice — while the memory is fresh and the sample is qualified.

**Use this when** you have shipped a new feature and need real signal on whether it is landing before committing to more work on it. **Don't use this when** the feature has not shipped to enough users yet; the popup firing is cheap, but drawing conclusions from ten answers is not.

## Goal

You ship a new section. Support is quiet, analytics shows some usage, and you have no idea whether users love it, find it confusing, or cannot find what they were looking for. Running a user-research round takes two weeks. This recipe drops a three-button popup on users who have engaged with the feature enough to have an opinion, captures the answer, and ships it to your analytics tool. You get a coarse but honest read in 48 hours.

## Setup

### In the dashboard

* Create a campaign `new-section-feedback`.
* Trigger: event `NewSectionUsed` with `usage_count = 2`.
* Conditions: `new_section_feedback_given != true`.
* Action: fire a deeplink to your in-app feedback popup, e.g. `yourapp://popup/new-section-feedback`. The popup asks "How's the new section?" with three buttons: "Love it", "Confusing", "Couldn't find what I wanted". See [Custom popups](/user-guide/custom-popups.md) for the popup-as-deeplink pattern.
* Each button tap is handled in-app: the app tracks the answer event and dismisses the popup. No further navigation.
* Frequency: once per user, ever — enforced by the `new_section_feedback_given != true` condition in the audience, not a native frequency cap.

### In the app (engineering hand-off)

* Increment a usage counter and fire an event each time the feature is used:

  ```kotlin
  val count = currentCount + 1
  amply.setCustomProperty("new_section_usage_count", count)
  amply.track("NewSectionUsed", mapOf("usage_count" to count))
  ```
* On each popup button tap, track the answer and mark the user as answered:

  ```kotlin
  amply.track("NewSectionFeedback", mapOf("answer" to "love_it"))
  amply.setCustomProperty("new_section_feedback_given", true)
  ```
* Forward `NewSectionFeedback` to your analytics tool. That is where the team will read the split.

## How it runs

1. User opens the new section for the first time. App increments the counter and fires `NewSectionUsed { usage_count: 1 }`. No campaign matches — the event trigger requires `usage_count = 2`.
2. Later that day, user opens the new section again. `usage_count = 2`. `new-section-feedback` matches.
3. Custom popup appears: "How's the new section?"
4. User taps "Confusing." App fires `NewSectionFeedback { answer: "confusing" }` and sets `new_section_feedback_given = true`.
5. The popup closes. The user continues using the app.
6. Over the next week, several hundred users answer. The product team reads the "Confusing" share in analytics and opens a ticket on whichever screen ranks worst for that cohort.

## Metrics to watch

* Response-rate of the popup. A healthy range is 40-70%. Under that and the moment is wrong or the copy is off.
* Answer distribution. The absolute numbers matter less than the shape: "Couldn't find what I wanted" high means the information architecture is off.
* Correlation with retention. Do "Love it" responders have higher 30-day retention than "Confusing" responders? That is the test of whether the feedback is predictive.
* Time to first answer after feature launch. Fast feedback is the point of this recipe.

## Related

* [Custom popups](/user-guide/custom-popups.md) — building the three-button popup
* [Campaigns](/user-guide/campaigns.md) — event-triggered campaigns with usage-count conditions
* [Tracking events](/developer-guide/tracking-events.md) — firing `NewSectionUsed` and `NewSectionFeedback`
* [User attributes](/concepts/user-attributes.md) — marking `new_section_feedback_given` to prevent re-asking
* [Feedback capture on negative rating](/recipes/feedback-capture-on-negative-rating.md) — the rating-driven cousin of this recipe
* [AI-assisted integration](/getting-started/ai-assisted-integration.md) — describe this campaign in plain language and have your AI assistant build it