Group reviews describing the same failed outcome even when customers use different language.
Compare frequency, intensity, ratings context, demand, and implementation effort.
Trace every opportunity summary back to representative source-review excerpts.
Signal Vector shortens the research loop without pretending that review evidence proves an entire business. Each stage makes the next uncertainty explicit.
Start with recent public reviews from a focused group of competing iOS apps.
Group repeated complaints, requests, workflow friction, and pricing resistance.
Rank the strongest patterns and open the source evidence before acting.
Signal Vector groups semantically related complaints and requests, then scores the resulting opportunity using frequency, intensity, rating pressure, competitor weakness, demand signals, and estimated build complexity.
No. Summaries accelerate triage, but the source review excerpts and score drivers remain attached so you can inspect the evidence before relying on a conclusion.
A useful pattern repeats across reviews or apps, describes a specific failed outcome, and has enough context to support a testable product hypothesis. One dramatic review is not enough.
Continue the research
Start with ranked opportunities and source reviews. Upgrade only when you need full briefs, exports, monitoring, and history.