See whether the problem repeats across users and competing apps instead of relying on one anecdote.
Understand what existing products fail to deliver and where users express rating or pricing pressure.
Turn the strongest evidence into assumptions, experiments, and a provisional decision.
Signal Vector shortens the research loop without pretending that review evidence proves an entire business. Each stage makes the next uncertainty explicit.
Start with a market or competitor set and identify repeated user pain worth investigating.
Open the complaint clusters, score drivers, weak competitors, and representative reviews.
Record the riskiest assumptions and choose an experiment, monitoring plan, or pass decision.
Begin by confirming that the problem repeats across real users and current alternatives. Then test the riskiest assumptions around urgency, willingness to switch or pay, reachability, and your ability to deliver a better outcome.
Reviews are strong problem evidence because they document lived product friction. They do not prove demand for your exact solution, pricing, distribution, or retention, so they should start validation rather than end it.
A useful signal names a specific recurring pain, shows representative source reviews, separates from weaker alternatives, and is narrow enough to turn into an assumption or experiment.
Continue the research
Start with ranked opportunities and source reviews. Upgrade only when you need full briefs, exports, monitoring, and history.