Reply to App Store and Google Play reviews from one place, with AI drafts that learn from the replies you already posted. There are four ways to run it, and most teams combine them:

Connect your app profiles first (here's how for the App Store). And one worry you can drop now: bare star ratings never come through the stores' review APIs, so every review that reaches you has text to answer.

Every method below runs on the same engine, so it's worth thirty seconds here. When a new review comes in, the default AI agent finds 5 to 10 reviews in your history that look very similar, matched on rating and language, so a 1-star complaint never learns from a 5-star thank-you. It then takes the replies you posted to those reviews and uses them as the example to follow, with one as the style anchor. The draft mirrors them: tone, length, sentence rhythm, formality. That includes replies you posted on the stores before ever using Reviewflowz, which is why a fresh account still sounds like you. And if you have no reply history at all, it still drafts, then gets better with every reply you post.

You can also create custom agents with your own prompt, signature, and language policy. My honest advice: don't. A custom prompt replaces that retrieval with your instructions plus your 5 most recent replies, so you're trading what you actually wrote for what you think you write. The default is more objective, because it finds similar reviews and drafts a very similar reply. You already solved the prompting problem, one posted reply at a time.

One platform detail is handled for you: Google Play caps replies at 350 characters. Drafts target 320, anything longer gets condensed automatically, and the editor checks the length before posting.

Automate the reviews you already know how to answer, and keep a human on the rest. That's the whole philosophy. If a message shows up every week and you've answered it well ten times, the agent has everything it needs to answer it an eleventh time. The edge cases are where you want oversight, so don't hand those over.

Automation is a Reply flow. You pick the app profiles it covers, the star ratings it answers, and optionally the languages it sticks to. Then you pick an agent, or keep the default. That's the split: rating, language, and profile. Most teams split on star rating, automate the high ratings, and keep eyes on the low ones.

Anything the flow doesn't catch simply stays unreplied and waits in the reply queue. The queue and your helpdesk run independently, so a review can open a Zendesk ticket and sit in the queue at the same time.

You keep oversight after the fact too. Every auto-posted reply records which agent sent it, through which flow, and when. The queue's Unread bucket collects auto-posted replies for review, and a thumbs up or down clears them. On paid plans there's no cap on reply volume. Trials cap at 20 replies total, and flows pause and notify you when they hit it.

If your support team lives in Zendesk, the review lifecycle can live there too. A new review opens a ticket with the priority already set from the star rating: 1 and 2 stars come in high, 3 medium, 4 and 5 low. The ticket arrives tagged with language, platform, sentiment, and the review's AI topic tags. The review is already translated, with the translation attached as a private note, so your agent reads in one language and replies in another. When the reviewer updates their review, the ticket reopens.

The reply works the way your agents already work: a public comment on the ticket gets cleaned up (signatures, footers, and images stripped) and published as the actual store reply, attributed to that agent. We built this loop with teams running real volume: Qonto runs 28k reviews across 8 profiles through it. Here's how to connect Zendesk.

Zendesk isn't the only helpdesk we support. Zoho Desk, Intercom, Front, LiveAgent, Freshdesk, Help Scout, and Gorgias all receive the same enriched tickets, with the priority, the tags, and the translation in the ticket body. The difference is the reply: posting back to the store from a ticket comment is Zendesk only. On the other helpdesks, you reply from the queue or from Slack.

If your team lives in a channel rather than a helpdesk, reviews can land there tagged and translated, and you answer without leaving. Hit Reply on the review card and a compose window opens. Suggest an AI answer pre-fills the draft, you edit what needs editing, and submit posts straight to the store. The posted reply echoes back into the thread, so everyone sees it's handled. Teams works the same way: Reply on the card opens an input, with the same AI button.

Setup guides: review alerts on Slack and connecting Microsoft Teams.

Everything ends up here. Replies in the sidebar opens the Reply Queue, a dedicated view of every review that needs an answer. It opens on the Unread bucket, and you can switch to reviews with no reply yet, replies per teammate, replies per agent, or everything at once.

The loop per review is short. The AI draft generates when the card loads, so you read the review with the answer already written. Edit it, regenerate it (in another language if you want), skip it for 24 hours, or submit. Submit posts to the store immediately: there's no separate approval step. If a post fails, the card tells you, and you resubmit.

It's also where you keep the agent honest. Auto-posted replies queue up as Unread until you rate them with a thumbs up or down, so nothing the AI sent goes unseen.

For the two platforms in this article, both post directly from the queue. One difference: a posted Google Play reply can be edited from Reviewflowz later, an App Store reply can't, so fix those in App Store Connect if you ever need to.

Running volume across several profiles? Book a demo here.

If you'd rather see it on your own reviews first, start the free trial: 14 days, no credit card.