The Voice of Customer Engine
Tells you what customers actually think, week after week, without surveys
How It Works
The Voice of Customer Engine continuously ingests customer feedback from all available sources. An AI theme extraction layer identifies patterns, groups similar feedback, and tracks theme frequency over time. A weekly brief surfaces the top emerging themes with supporting evidence, trend data, and suggested actions for each team function.
Step-by-Step Flow
Connect your feedback sources: support tickets, review platforms, NPS tools, social mentions
Define the theme categories relevant to your business
AI aggregates and analyzes all feedback weekly
Emerging and trending themes surface with supporting evidence
Leadership team reviews the brief and assigns action owners
Actions logged, themes tracked to measure whether resolution improves feedback
Best For
- Companies with feedback data scattered across platforms that never gets synthesized
- Product and marketing teams that want customer signal without waiting for a quarterly survey
- Support teams whose ticket patterns contain strategic insights that are not being surfaced
This is customized for your business.
Every node, tool, and logic path shown here gets adapted to your team structure, your CRM, and your existing workflows. What you see is the proven pattern. What we build together is built specifically for you.
Implementation Notes
Feedback sources connect via API or webhook: Zendesk, Intercom, and Freshdesk for support tickets; Trustpilot, G2, Capterra, and Google Reviews for review platforms; Delighted, AskNicely, or Typeform for NPS responses; and Mention.com or Sprout Social for social listening. All feedback aggregates into a central store tagged by source, date, and sentiment score. The theme extraction pipeline uses a clustering approach: embeddings generated for each feedback item, then clustered into recurring themes using k-means or hierarchical clustering with a configurable minimum cluster size (default 5 or more items per theme). Each cluster surfaces a representative quote, a frequency count, a sentiment distribution, and a week-over-week trend. Themes flagged as emerging (frequency increasing more than 30 percent week-over-week) are highlighted in the brief. The weekly brief publishes to Slack, email, or a Notion page and includes sections for each audience: product team (feature requests and friction points), marketing team (messaging gaps and competitor comparisons), and operations team (process failures and service delivery themes). Action items created from the brief are tracked against the theme in the following week's run. Prerequisites: at least two active feedback sources and a minimum of 50 feedback items per week for reliable theme detection.