From reviews to ranked gaps

Signal Vector helps you move from raw App Store feedback to product opportunities you can inspect, compare, save, and monitor.

Step 1

Choose a market

Start with a focused category or competitor set instead of chasing broad trends.

Step 2

Read the reviews

Collect public App Store reviews and ratings from the apps that define that space.

Step 3

Find the patterns

Group repeated complaints, requests, and workflow friction into clear themes.

Step 4

Score the gaps

Rank each gap by frequency, intensity, rating pressure, demand, and build complexity.

Step 5

Check the evidence

Open each signal to inspect the reviews, category context, and scoring rationale.

Step 6

Monitor changes

Save promising gaps and keep watching the category as new review pain appears.

What you get

Evidence first, ideas second.

The workflow is designed to keep you close to the source material: real reviews, repeated pain, and transparent scoring. It should help you decide what is worth deeper research, not hand you a vague app idea.

Research operating loop

A compact view of how raw review data becomes a scored, reviewable opportunity signal.

Phase	Input	Output	Action
Scope	Category or app set	Focused review corpus	Pick the categories and competitors worth tracking.
Cluster	Recent App Store reviews	Complaint clusters	Group similar complaints and feature requests.
Score	Clusters and app metadata	Opportunity score	Compare frequency, rating pressure, intensity, and build effort.
Review	Ranked opportunities	Research decision	Inspect review evidence before saving or ignoring a signal.
Monitor	Saved opportunities	Monitoring queue	Watch saved markets as new review pain appears.

Signal Vector