A mobile studio with 12 apps couldn't keep up with reviews scattered across two stores. We built one pipeline that tags sentiment, drafts replies and alerts on rating dips — pushing reply rate from 8% to 92%.
Typical results
4.5
Avg portfolio rating
Under 1 day
Typical reply time
6
Fixes shipped from themes
Figures reflect typical results for this kind of automation.
The challenge
Twelve apps across the App Store and Google Play produced 400-plus reviews a month in multiple languages. Checking two consoles per app was nobody's job, so it rarely happened: only 8% of reviews ever got a reply, rating drops went unnoticed for weeks, and recurring complaints — the kind that should shape a roadmap — stayed buried in store consoles.
Before and after
Review reply rate
11.5×Average rating
+10%Rating-dip detection
−95%The automation
We connected both app stores to a single Make pipeline. Every new review is tagged by AI for sentiment, theme and language, then a suggested reply — in the reviewer's language, matching the studio's tone — lands in a Slack queue for one-click approval. If any app's daily rating average dips below its threshold, the team is alerted immediately with the reviews responsible. A weekly report clusters themes per app for the roadmap.
How it works
- 01
All reviews, one stream
New reviews from both stores flow into a single pipeline within minutes of being posted.
- 02
AI tags and drafts
Each review gets sentiment, theme and language tags, plus a suggested reply in the reviewer's language.
- 03
One-click approval
Drafts wait in a Slack queue; the team approves or tweaks, and replies post back to the store automatically.
- 04
Rating guardrails
A daily rating dip below threshold on any app triggers an instant alert with the responsible reviews attached.
- 05
Themes feed the roadmap
A weekly report clusters complaints and requests per app, turning review noise into a prioritized fix list.
Starts from
- App Store reviews
- Google Play reviews
Delivers
- Approved replies posted
- Rating-dip alerts
- Weekly theme report
The impact
Reply rate jumped from 8% to 92%, with most reviews answered inside a day. Rating dips now trigger same-day Slack alerts instead of surfacing weeks later, average portfolio rating climbed from 4.1 to 4.5 stars, and the weekly theme report turns recurring complaints into a prioritized fix list.
Questions about this automation
Which app stores does the pipeline read reviews from?
It pulls new reviews from Apple's app store and from Google Play through their developer APIs for every app in the portfolio, usually within minutes of posting. Reviews from both stores land in one stream with the app, version, rating and language attached, so nobody has to check separate consoles for each app.
Are AI replies posted automatically?
No. Each suggested reply waits in a Slack queue next to the original review, written in the reviewer's language and the studio's tone. A team member approves it as is or edits it first, and only then does the flow post it back to the store. Replies to low ratings can be routed to a senior team member.
How does the rating-dip alert work?
Each app has a threshold for its daily average rating. When the day's average falls below it, the team gets a Slack alert with the reviews behind the drop, grouped by theme and app version, which often points to a specific release. It is a multi-step build, usually rolled out in stages, starting with the review feed and reply drafts.