Use case

Turn thousands of comments into a ranked list of what to fix

Corha reads and codes every piece of feedback, groups it into themes, and ranks them by impact, so you know what to act on first.

See how it works
The problem

Manual tagging does not scale

Analysing feedback by hand works until you have a few hundred items. Past that, the tagging never gets done, and the backlog of unread feedback grows.

The result is decisions based on the feedback someone happened to read, not the full picture.

How Corha helps

What you can do with Corha

Coded automatically

Corha tags and clusters thousands of tickets, calls and survey responses into themes in minutes.

Ranked by real impact

Themes are weighted by frequency and the value of the customers behind them, so a signal from two key accounts is not lost in the noise.

Verifiable, not a black box

Every theme links to the underlying quotes, so you can check the machine's work before acting.

How it works

From a backlog of feedback to a ranked plan.

  1. 01
    Connect your channels

    Bring in support, sales, survey and review feedback from every tool.

  2. 02
    Corha codes and clusters

    Every item is tagged and grouped into themes, with the source quotes attached.

  3. 03
    Rank by impact

    Sort themes by how often they appear and the value of the customers affected.

  4. 04
    Act on the top themes

    Send the highest-impact themes straight into tracked work.

Frequently asked

Questions about feedback analysis

How do you analyse customer feedback at scale?
Centralise every channel, cluster items into themes automatically, keep each theme traceable to its source, then rank by frequency and customer value.
Can we trust automated tagging?
Yes, when it is verifiable. Corha links every theme to the exact quotes behind it, so a human can confirm the grouping in one click.

See it with your own data.

Connect your first source and Corha will draft your starter personas in under five minutes.

Browse use cases