Sentiment analysis on every channel, under one taxonomy.

Customer sentiment analysis is the practice of scoring how customers feel about something and attaching that score to the thing they were talking about. The second half does the work. A sentiment number with no theme underneath it tells you the mood and gives you nothing to act on.

Most implementations score a whole document. A review that praises delivery and criticizes sizing becomes one number somewhere in the middle, and both signals are lost. Scoring at the theme level keeps them separate, so a product team can act on the part that concerns it.

Unwrap labels every entry and files it under a single taxonomy, so channel becomes a filter on one reading.

This is the part that usually breaks. A helpdesk has its own tags, a survey tool has its own scale, and a review site has stars, so the same complaint is counted three ways and the totals never agree. Reading every source under one taxonomy lets you say how sentiment on a theme is moving overall.

Traceability is the other half of the answer. Every sentiment score stays linked to the customer text it was drawn from, so any figure on a dashboard can be opened and checked against the verbatims behind it. That is what lets a sentiment number hold up in a meeting where someone disputes it.

Unprompted channels matter most here. Survey sentiment measures how customers answer when you ask, and support and review sentiment measures what they say when nobody prompts them. Both are read under the same themes, and the full source list sits on the customer feedback integrations page.

From there the theme carries its own evidence and its own audience. The verbatims explain the decline, the accounts show who it affects, follow-up runs through close the loop, and the recovery is measured in customer feedback dashboards and reporting. Detection itself is covered on real-time alerts.