Feedback Insight Tool

The tool ingests textual feedback from surveys, reviews, and support interactions and returns structured analytics. It computes a sentiment score, identifies dominant topics, and tracks how these signals evolve over time. Conceptually, it treats feedback as a collection of statements that convey opinion, emotion, and needs, then aggregates these signals into interpretable metrics. This enables teams to quantify qualitative input and tie it to product decisions. Beneficiaries include product managers, CX teams, and UX researchers who need fast, repeatable insight without bespoke NLP projects. Unique value lies in a ready-to-use pipeline with configurable sources, date ranges, and language handling, plus straightforward export formats for downstream analytics. Core features include text ingestion, sentiment scoring, topic clustering with weights, time-series trend computation, and export to CSV/JSON. Use cases cover post-release sentiment shifts, topic spikes after campaigns, and prioritization of improvements based on data depth. The tool supports privacy-preserving aggregation and API access for automation. It is designed to complement qualitative research with quantitative signals, facilitating cross-team alignment and faster action on customer feedback.