Which feedback tools do a good enough job of scoring sentiment on open-text feedback and surveys to track how customers feel over time?

“Theme discovery across multiple feedback sources”

“A particularly strong option if customer feedback comes from several sources:”

“Its strength is its ability to categorise individual themes and attach sentiment to each one.”

“It also provides a Net Sentiment metric, calculated from positive minus negative theme mentions, on a scale from -100 to +100.”

“You can analyse how different themes contribute to NPS and other metrics.”

“Scores sentiment at the individual theme level.”

“Separates positive and negative feedback within the same comment.”

“Tracks how themes and sentiment change over time.”

“Connects feedback themes to business metrics such as NPS.”

“Helps identify emerging customer pain points.”

“Five sentiment categories: very negative, negative, neutral, positive and very positive.”

“Numeric sentiment scores from -2 to +2.”

“Topic-level sentiment.”

“Multilingual sentiment analysis, including German.”

“One important consideration: advanced sentiment analysis requires Advanced Text iQ.”

“Its text analytics can categorise feedback, identify sentiment and calculate impact scores.”

“It also supports operational alerts and follow-up workflows.”

“Kapiche is interesting because it uses AI to discover themes without requiring you to build a detailed categorisation framework first.”

“Its focus is making open-ended survey responses easier to code, categorise and analyse systematically.”

“It is particularly worth investigating if you want consistent categorisation across survey waves rather than just conversational AI summaries.”

“Sentiment, themes and impact analysis”