Data & decision systems / PROPOSED CONCEPT
Customer feedback insights.
Themes from reviews and surveys, with the quotes behind them.
Proposed concept — not a released product or client work.
The opportunity
A real need.
A considered response.
Feedback is spread across review sites, surveys and support tickets, and few teams have time to read it all. A feedback view groups it into themes and links every theme to the original comments, so decisions rest on evidence.
DESIGNED AROUND
Marketing, product and service teams reading customer reviews, surveys and support notes.
The experience
What this could make possible.
Original comments behind every theme
Trends by product or location
Shareable summary for the team
01
Import reviews and survey answers
→02
Group comments into themes
→03
Check themes against the comments
→04
Share and act on the findings
Under the surface
The engineering
behind the experience.
Architecture is a starting hypothesis. Discovery and representative tests decide what belongs in the first build.
POTENTIAL CONNECTIONSReview platforms or exportsSurvey toolSupport desk
01Architecture to explore+
- Batch analysis with a theme list people review
- Links from every theme to its source comments
- Removal of personal details before analysis
02Integration dependencies+
Review platforms or exports, Survey tool, Support desk. Confirm access, data ownership, update frequency and failure behaviour during discovery.
03Validation and human control+
Check theme accuracy on a labelled sample and the share of themes the team acts on. Themes describe what customers wrote, not a statistically representative survey. Personal details are removed before analysis.
A useful first step
Start small.
Learn something real.
Six months of reviews for one product line, with a person checking a sample of every theme.
Evidence to look for
Check theme accuracy on a labelled sample and the share of themes the team acts on.
A boundary to design for
Themes describe what customers wrote, not a statistically representative survey. Personal details are removed before analysis.
Proposed scope, not a delivery commitment. Data, permissions, operational constraints and sector requirements need review before implementation.
Connected capabilities
Data Engineering & Decision SystemsGenerative AI & LLM DevelopmentAI Evaluation & OptimisationResearch behind the direction
AnthropicDemystifying evals for AI agents ↗Microsoft ResearchGraphRAG and dynamic community selection ↗These sources inform technical possibilities. They do not demonstrate a Tomatrix deployment or endorse this proposed product.
From possibility to a conversation
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your starting point.
Add a little context. Preview a practical brief, then keep it for a conversation with Tomatrix.
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PRODUCT EXPLORATION: Customer feedback insights Status: Proposed concept — scope and feasibility to be agreed. Our context: To be discussed. Who this could help: Marketing, product and service teams reading customer reviews, surveys and support notes. A useful first pilot: Six months of reviews for one product line, with a person checking a sample of every theme. What to evaluate: Check theme accuracy on a labelled sample and the share of themes the team acts on. Important boundary: Themes describe what customers wrote, not a statistically representative survey. Personal details are removed before analysis. Integrations to explore: Review platforms or exports, Survey tool, Support desk Concept reference: /products/customer-feedback-insights
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