Sistava

Voice-of-Customer Synthesis

AI Data & Analytics Team

Surveys, interviews, reviews, and tickets → themes, quotes, and action items

Your AI analytics team ingests every customer signal you produce — surveys, interview transcripts, app-store reviews, support tickets, sales-call recordings, NPS comments — and synthesizes them into themes you can act on.,Themes are evidence-linked: every claim cites the customer quotes that support it, with source and date.,Refreshable per cycle so you see what shifted between Q2 and Q3, not just what the snapshot looked like.

Benefits

How It Works

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At a Glance

Multi-source
Surveys + interviews + reviews + tickets + calls
100%
Themes linked to quotes
Trended
Sentiment over time, not snapshot
Actionable
Action items per theme

Quotes Win Arguments

FAQ

How is qualitative coded?

LLM-based open coding with human review on contested labels. Your team can train the coding scheme over time.

Can it integrate with our product analytics?

Yes — pair qualitative themes with quantitative behavior to validate the "why" behind the metric.

How is PII handled?

Customer identifiers can be masked or removed before LLM processing. Configurable per source.

Can it replace user researchers?

No — it handles synthesis at scale; researchers handle judgment, study design, and stakeholder management.