App Review Management Software
Replies in your voice • Topics from your own reviews • Zendesk, MCP and API included
Start a 14 day free trial • No credit card required
The AI learnt your voice from the replies you already wrote
Not a tone dropdown. Reviewflowz retrieves the replies you have published, including the ones you wrote by hand before you had a tool, and writes the next one from those.
Examples are picked by rating, language and recency, so a one-star in German is answered the way you answer one-stars in German.
Backtest an agent against last year’s reviews before it answers a single live one, then set rules per rating and let it run.
Replies are not metered. Answer every review on every plan.
App Store “Seit dem letzten Update werde ich beim Wechsel ins WLAN jedes Mal ausgeloggt.”
Logged out every time I switch to wifi since the last update.
“Danke für die Meldung, und sorry für den Ärger. Das Logout beim Netzwerkwechsel ist ein bekannter Fehler in 4.2.1, der Fix ist unterwegs. Schreib uns gern an support@…, dann melden wir uns, sobald er live ist.”
“Danke für die Meldung, und sorry für den Ärger…” · 2★ DE · Mar
“…der Fix ist unterwegs, wir melden uns sobald er live ist.” · 3★ DE · Jan
“Schreib uns gern an support@…” · 1★ DE · Nov
Matched on rating, language and recency. You wrote all three before you had Reviewflowz.
Every angry review lands in Zendesk with the context your agents need
A bad app review is a support ticket that happens to be public. Rating drives priority, so one and two stars arrive high and five stars stay out of the way.
Tags carry language, platform, sentiment and the AI topic, so your existing triggers route reviews the same way they route email.
The translation rides along as a private note. Your agent reads the Portuguese one-star in English.
When the agent answers the ticket, their reply is published back to the store under their name. Nobody opens a second tool.
Zendesk #48219 set from 1★ Urgent 
Google Play · v4.2.1 · Brazil “Paguei o plano anual e o app não reconhece a assinatura. Já mandei email duas vezes.”
Paid for the annual plan and the app does not recognise the subscription. Has emailed twice already.
“Desculpe pelo transtorno, Rafael. Reativei sua assinatura manualmente e te enviei um email…”
Published to Google Play as Lucia M. Nobody opened a second tool.
Topics built from your reviews, not from a list someone else wrote
A TF-IDF pass driven by an agent finds the terms that are distinctive to your app rather than common in the language, and clusters them into your own topic tree.
Sentiment is scored per mention, on the sentence that carried it, between minus one and plus one. Not a ratio of good reviews to bad ones.
“Logs me out switching networks” becomes its own subtopic instead of disappearing into a generic Bugs bucket built for every app at once.
Export every extract with its score, topic, platform, version and date, or query it from the API.
A generic tool files all four under “Bugs” and “Features”. You cannot ticket “Bugs”.
Ratings and reviews are different things, and each store reports them differently
Your store rating is snapshotted daily, per market, with the star histogram behind it. Written reviews are tracked separately, so a rating with no words never lands in a sentiment score.
App Store reports a real score and a real count per country. Google Play repeats one global count against every market, so we chart App Store counts per country and refuse to chart Play’s.
Play Store rating lines follow the market your reviews actually come from, rather than an unweighted average of incomparable countries.
Group written reviews by version to see what a release did to your rating and your volume. You get everything a platform reports, and nothing it does not.
App Store score + count per market Google Play score per market only Google returns one global count against every market. It is the same number three times, so we do not chart it. The scores are real, and those we do chart.
22,100 of those ratings came with no words. They move your score and they never touch a sentiment topic, because there is nothing in them to read.
Your reviews inside Claude, ChatGPT, or your own stack
Connect the MCP server and ask the assistant your team already uses: what complaints spiked since 4.2, which quotes to put in the release notes, how last month compares.
Read-only and OAuth-authenticated, so nothing changes in your account from a chat window.
The public API does the same for your own code: reviews, stats, exports, webhooks, with OpenAPI docs.
Customers build review pages, internal dashboards and BI pipelines straight off it.
What broke in 4.2.1? Compare complaints to the two weeks before it shipped
Comparing review topics before and after the 4.2.1 release
One thing dominates. Complaints about being logged out went from 11 mentions in the fortnight before 4.2.1 to 340 after, almost all iOS, and heavily German and Brazilian.
“Seit dem Update werde ich beim Wechsel ins WLAN jedes Mal ausgeloggt.” App Store, 2★, 14 May
Billing complaints are flat, so the annual-plan issue you fixed in 4.1.6 has stayed fixed. Your German rating dropped 0.4 over the same window; nothing else moved.
Want the 340 grouped by device, or a draft for the release notes?
Your users review you in more places than two stores
App Store and Google Play are where we are best. They are not the whole picture.
Trustpilot, Google, Facebook, the Chrome and Edge stores, G2, Capterra, Product Hunt: monitored in the same inbox, and replied to directly on the platforms that allow it.
Most app review tools stop at the stores, which is fine right up until your support team is asked about a Trustpilot score.
A French company, hosted in the EU. Two-factor can be mandatory across your account, and every credential use is logged.
App Store
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Google Play
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Product Hunt 
Trustpilot
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Google
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Facebook
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G2 
Capterra If it has got stars, we support it.
What our own users say
A live Reviewflowz widget, pulling our real reviews right now.
How serious are you about your reviews?
Set up in under five minutes. No demo required.
How is Reviewflowz different from AppFollow?
Their AI reply picks from tone presets; ours writes from the replies you have already published, and you can backtest it before it goes live. Their topics come from a fixed tag list built for every app at once, with the better analysis on a higher tier; ours are derived from your own reviews. Their coverage stops at the stores, while your users are also on Trustpilot, Google, G2 and Capterra. And we do not meter replies.
Which app platforms do you cover?
App Store, Google Play, Huawei AppGallery, macOS App Store, Microsoft Store, and the Chrome, Edge and Firefox extension stores, plus Product Hunt and AppSumo. Alongside them: Trustpilot, Google, Facebook, G2, Capterra, TrustRadius and SourceForge.
Can Reviewflowz post replies to the stores automatically?
Yes. App Store and Google Play replies post directly from Reviewflowz, as do Trustpilot, Google and Facebook. Set rules per rating and language: answer the five stars automatically, hold anything under three for a human, or route those into Zendesk instead.
How does the sentiment analysis actually work?
An agent runs a TF-IDF pass over your reviews to find the terms that are distinctive to your app rather than common in the language, builds your topic tree from them, and scores sentiment on the specific sentence that mentioned each subtopic. Only reviews with text are analysed, and every extract is exportable with its score, topic, platform and date.
Do you have an API and an MCP server?
Both. The public API covers reviews, stats and exports with bearer tokens and OpenAPI documentation. The MCP server is read-only and connects to Claude, ChatGPT or anything else that speaks MCP, over OAuth.