Conversation and feedback analytics · PUBLIC RESEARCH BRIEF
KapicheWhat turns a feedback pattern into a credible business driver?
Kapiche describes bringing together survey comments, complaints, calls, chats, emails and other customer conversations, using AI to identify themes and sentiment without manual tagging, and connecting the analysis to measures such as NPS or CSAT. It also offers dashboards and a Workbench for filtering by time, product, segment or team. Broad coverage can reveal patterns, but the same issue may be overrepresented by one channel or customer group.
Updated 2026-10-26 · Simulation results not yet generatedCHANGE ONE THING. LEARN WHAT MATTERS.
Three questions for the GTM team.
When a theme appears to drive NPS or CSAT, what account, journey-stage and time-period checks are needed before the relationship influences investment?
Set up this study →Which differences between product, support and executive views should be intentional, and which shared definitions must remain fixed so teams do not tell incompatible stories?
Set up this study →PROPOSED AUDIENCE
Who should weigh in?
North American CX leaders, customer-support leaders, insights analysts, product managers, data teams and executive stakeholders evaluating Kapiche. Include administrators who prepare data and explorers who interpret dashboards or the Workbench. Proposed audience only; no Kapiche project, conversation, score, customer record or private quote is included.
TWO TIME HORIZONS
Trial today. A habit tomorrow?
Near term · 0–90 days
Over 0–90 days, create a synthetic corpus with unequal channel volumes, response bias, repeated contacts, shifting sentiment and seeded relationships to an experience score. Compare theme discovery, segment filters, driver conclusions and cross-functional reporting choices.
Longer term · 3–12 months
Over 3–12 months, vary channel mix, survey participation, product releases and customer composition. Study whether themes and apparent drivers remain stable, whether dashboards drift apart by team and whether new evidence reverses earlier priorities.
What would make the result actionable?
Use labeled synthetic conversations with known channel and segment distributions, duplicate identities and documented score-generation rules. Reweight or resample channels, review underlying text and validate any churn, retention or revenue claim with real longitudinal outcomes.
A Gather simulation returns hypothetical customer reactions. Quantifying revenue, traffic or retention needs actual business inputs and validation against observed behavior.