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Review to Feature Mapper

Turn app store and G2 reviews into a prioritized feature backlog — free

Paste reviews from any source and get a grouped feature request list with demand scores, so you can build what users actually want instead of what you assume.

Get your result in under 10 seconds.

No account required

Example output

Request Clustering:Groups similar feature requests using semantic similarity into named themes.
Demand Scoring:Scores each theme by mention frequency and sentiment intensity.
User Story Output:Auto-generates a "As a user, I want…" story for each top-ranked theme.

How It Works

Paste Input

Copy and paste your data into the input field

Get Result

Instant results in under 10 seconds

Share

Copy result or share a direct link

The Problem

Reading 500 reviews to extract feature requests takes a full sprint

Gut-feel roadmaps get challenged in every stakeholder meeting without data

What It Does

1

Request Clustering

Groups similar feature requests using semantic similarity into named themes.

2

Demand Scoring

Scores each theme by mention frequency and sentiment intensity.

3

User Story Output

Auto-generates a "As a user, I want…" story for each top-ranked theme.

4

CSV Backlog Export

Downloads the prioritized list as a CSV ready to import into Jira or Linear.

Share your result

Every result gets a unique shareable link. Show your colleagues.

owlematic.pro/share/abc123

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Frequently Asked Questions

Where can I get review text to paste?

App Store Connect exports, G2 CSV downloads, or copy-paste from any review page work fine.

How accurate is the clustering?

Clustering uses TF-IDF + cosine similarity. Accuracy is high for 50+ reviews; fewer reviews may over-cluster.