Solution

Customer Insights Engine

For CX, product and support leaders buried in feedback volume: calls, tickets and surveys turned into counted, cited themes that route to the team that owns them.

Call transcriptsSupport ticketsSurvey responsesChat logsEmails
Every theme links to the actual feedbackPII redacted before analysis runsThemes counted, not guessed

The problem

Why this exists

Weeks

The tenth mention arrives first

Product hears about a problem weeks after ten customers described it. The signal was in the transcripts nobody had time to read.

Drift

Manual tagging lies over time

Different agents tag the same complaint differently, so emerging issues get mislabeled and the trend lines stop meaning anything.

Post-mortem

Churn signals found afterward

The complaint that predicted a churned account is discovered in the account review — after the account is gone.

The product, not a promise

A feedback stream you can interrogate

Customer Insights Engine — workspace
Theme — billing: duplicate chargeMentions counted · trending upcited
Sentiment by channelCalls · chat · email · surveyscited
Feature request clusterRanked by volume and sentimentcited
PII redactionApplied before analysiscited
New theme emerging in this week's calls — classification queued for reviewverify
HUMAN-APPROVED BEFORE IT POSTS

How it works

File in. Answer out.

  1. 1

    Ingest

    Audio calls, chat logs, emails, tickets and survey responses flow in from every channel.

  2. 2

    Protect

    Personally identifiable information is detected and redacted before analysis.

  3. 3

    Classify

    Feedback is transcribed, translated and clustered into topics and sub-topics by intent.

  4. 4

    Quantify

    Sentiment and volume per theme become metrics that correlate with NPS and churn.

  5. 5

    Distribute

    Each department gets its own signals — product sees bugs, support sees SLA themes, sales sees risks.

Who it's for

Built for the people who own the outcome

Insights analyst

Stop tagging tickets; start reading the results.

  • Every channel classified by intent, consistently, without manual tagging
  • Theme volumes and sentiment trends computed instead of sampled
  • Any number on the dashboard opens to the redacted feedback behind it

VP of Product

A roadmap argument backed by counted customer evidence.

  • Feature requests quantified by volume and sentiment, with receipts
  • A spike in a complaint theme alerts engineering the day it starts
  • Feedback trends correlated with NPS movement, so you know why a score moved

Data protection officer

Customer voice analyzed without exposing customer identity.

  • PII detected and redacted before any analysis runs
  • Deploys in your cloud with your existing access controls
  • Reviewers see redacted evidence, and every access is logged
SaaSBankingInsuranceTelecomRetailHealthcare
Omnichannelcalls, tickets, email, surveys, social
PII-redactedbefore any analysis runs
Quantifiedthemes counted, not guessed
Traceableevery theme links to the actual feedback

Voice-of-customer programs fail on volume, not intent. The feedback exists — in call recordings, support tickets, survey comments, chat logs — but manual analysis cannot keep pace, so tagging is inconsistent, emerging issues get mislabeled, and the complaint that predicted a churned account is found afterward, in the post-mortem. Product teams hear about a problem weeks after the tenth customer mentioned it.

The Customer Insights Engine reads it all. It ingests interactions from every channel, transcribes and translates audio, and classifies each piece of feedback into specific topics and sub-topics — capturing intent rather than matching keywords. Non-actionable noise is filtered out, and personally identifiable information is detected and redacted before analysis begins, so the pipeline is privacy-safe by default.

From qualitative noise to operational metrics

The output is numbers a business can run on. Complaint themes are counted and trended, so a spike in “login failure” mentions alerts engineering the day it starts rather than at the quarterly review. Feature requests are quantified by volume and sentiment, giving product a data-backed roadmap argument. Feedback trends correlate with operational metrics, which is how you learn exactly why an NPS score moved — and churn-risk signals surface while there is still time to intervene. Insights route directly to the department that owns them, without a reporting layer in between.

Every theme has receipts

Aggregated sentiment is easy to dismiss until you can read the underlying feedback. Here, every theme, score and alert links back to the actual interactions that produced it — the transcript passage, the ticket, the survey comment. When the dashboard says billing complaints doubled, the evidence is one click away, redacted but real. That traceability moves customer insight from an interesting chart to a basis for decisions: teams act on it because they can verify it.

Objections, answered

What teams ask us first

How do I know the themes are real and not model invention?

Every theme, score and alert links back to the interactions that produced it — the transcript passage, the ticket, the survey comment. When the dashboard says billing complaints doubled, the evidence is one click away, redacted but readable. Uncertain classifications are flagged for review rather than silently filed.

We already have a feedback taxonomy. Do we have to start over?

No. Your topics, sub-topics and routing rules are the starting configuration; the engine classifies into your structure and proposes new themes when feedback stops fitting it. You approve taxonomy changes — they never happen silently.

Customer feedback is full of personal data. How is privacy handled?

PII is detected and redacted before analysis begins, so the pipeline is privacy-safe by default. The platform deploys in your cloud environment, access follows your permission model, and every view of underlying feedback is logged.

How long until the first insights?

Days. Connect the channels, and historical calls, tickets and surveys classify as they ingest — no re-tagging project, no waiting for new feedback to accumulate. The first themes come from the backlog you already have.

Bring a month of raw feedback.

Watch calls, tickets and surveys become counted, cited themes in a live demo — including at least one theme you did not know you had.

Request a demo