Dashboard and analytics
The daily action view, the longer trend view, Review Intelligence, and a glossary of every metric.
Dashboard vs Analytics
Two views, two jobs.
Dashboard is about today. What came in, what needs you, what went out. It is a to-do list with numbers on it.
Analytics is about the trend. Reply rate, ratings, sentiment and topics, and how they have moved over the date range you picked.
If you only open one each morning, open the Dashboard. Analytics is a Monday thing.
What the Dashboard shows
Four tiles at the top: Total reviews, Avg rating, Replied (with your reply rate) and Flagged spam. Below them:
- Review volume, by sentiment or by platform, and Ratings & activity.
- Rating recovery, a summary of the Rating insight page.
- Reply impact: unhappy reviews answered and drafts ready to send.
- Automation: spam reporting and auto-replies.
- What changed, Needs you, Top topics, Reviews by platform and Recent replies.
Banners at the top tell you when a connection has a problem or a spam reporting run needs you.
What Analytics shows
Four tiles: Reviews, Negative reply rate, Avg rating and Store rating (with its 7-day change). Below them:
- Sentiment and rating-share charts.
- What customers are saying, with All topics, Needs attention, Customers love and Mentioned more.
- A summary of reviews, average rating, auto-replies, and spam caught, reported and removed.
- A breakdown by platform, storefront and language.
- An All apps table: reviews, replies, reply rate, average stars, store rating, positive and negative per app.
Click an app for its own page: reviews, replies, reply rate and ratings, its workload (awaiting reply, needs review, auto-published, drafted), sentiment, volume, topics, languages, frequent keywords and recent reviews.
Review Intelligence
Review Intelligence groups what customers say into issues (distinct problems) and praise (distinct things they like), so you can act on themes instead of reading reviews one at a time.
The top shows how many issues there are, how many reviews they affect, how many are rising or new, and how much praise. Filter the list by Rising & new, Rising, New, Steady, Falling, or Too few to call.
Open an issue to see whether it is changing over time, its star distribution, which apps, versions, countries and languages it comes from, and the reviews behind it. A Feature requests card collects what customers are asking you to build.
Avg rating vs Store rating
They measure different things on purpose, so they will not always match.
Avg rating is the average stars of the written reviews in your date range that are still live on the store. Flagged spam stays in it until the store removes the review.
Store rating is what the App Store and Google Play publish for your apps today, including star-only ratings with no text. It moves on the platform's schedule, not ours.
When you are quoting a number to someone else, say which one you took it from.
Metric glossary
| Metric | What it means |
|---|---|
| Reviews | Reviews posted in the selected date range on apps that are still connected, spam included |
| Reply rate | Share of the range's reviews that got a reply sent from AI Review Sensor. Replies posted directly on the store are not counted |
| Negative reply rate | Share of unhappy reviews (negative or urgent) in the range that got a reply |
| Avg rating | Average stars of the written reviews in the range that are still live on the store. Flagged spam stays in until the store removes it |
| Store rating | The rating the App Store and Google Play publish for your apps today, star-only ratings included |
| Recent rating | Average stars of recent written reviews, compared with your all-time average |
| Urgent | Reviews marked urgent that are still waiting for a reply |
| Awaiting reply | Reviews in the range that still have no reply |
| Oldest unanswered | How long the oldest review still waiting for a reply has waited |
| Needs review | Reviews still waiting for a reply that the AI marked for a person to check first |
| Replies sent | Reviews in the range that got a reply sent from AI Review Sensor |
| Auto-published | Replies auto-reply posted on its own in the range |
| Drafted | Reply drafts written in the range that are waiting for someone to send them |
| Spam found | Reviews flagged as spam that are still live on the store or that you already reported |
| Spam reported | Flagged spam you have reported to the store |
| Spam removed | Reported spam the store has since taken down |
| Pending removal | Reported spam that is still on the store, waiting for the store's decision |
| Rating you can recover | Stars your written-review average would gain if the flagged spam still on the store were removed |
| Rating recovered | Stars your written-review average has already gained from spam the stores removed |
| Top issue | The complaint mentioned in the most reviews in the range |
| Issues | Distinct problems customers raised in the range |
| Reviews affected | Complaints in the range that belong to at least one issue |
| Rising & new | Issues mentioned clearly more often than before, plus ones that are new |
| Praise | Distinct things customers praised in the range |
| Coverage | How many connected apps brought in at least one review in the range |
Exporting
Export on the Analytics page downloads a CSV with one row per connected integration: platform, when it was connected, total reviews, replies sent, response rate, average rating, and the positive, neutral, negative and urgent counts for the range you are looking at. That is the summary: the thing you paste into a spreadsheet or a board deck.
It is not a dump of the reviews themselves. There is no self-serve export of every review and reply; the routes for data requests are in security and privacy.
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