Advocacy & Sentiment Operations

Public ratings and written feedback were treated as reputation management rather than as an operational input. This work existed to route what customers said into the teams who could actually change it.

Reviews were read individually and forgotten collectively. A rating drop generated concern but no diagnosis, because nobody had a consistent way to categorize what people were unhappy about. The same complaints recurred for months without ever being counted.

• Code the reason, not the score. A star rating tells you temperature. The reason tells you what to fix.
• Keep the category list short enough to apply consistently. A taxonomy nobody can remember produces inconsistent data.
• Distinguish product complaints from service complaints from expectation gaps. They go to three different owners.
• Track distribution over time, not just averages. The average moves slowly while the shape of the distribution moves early.
• Respond publicly where a response is warranted, and treat the response as part of the operation rather than as marketing.
• Close the loop. If a fix shipped, the same reason category should shrink. If it does not, the diagnosis was wrong.

1. 01

   A feedback reason taxonomy

   A small, stable set of categories covering the recurring drivers, applied the same way each period so themes could be counted.

2. 02

   A distribution read

   Ratings tracked by distribution and trend rather than by average alone, which surfaced problems earlier.

3. 03

   An ownership routing map

   Each reason category assigned to the team that could act on it, so feedback ended somewhere specific.

4. 04

   A public response practice

   Monitoring and responding to incoming reviews during release windows and known issues, with a defined tone and escalation path.

• Turned public feedback into a recurring input for product and operations rather than a reputational chore.
• Gave release windows an early warning signal that moved faster than support volume.
• Fed the reason taxonomy thinking that later shaped cancellation and return categorization in customer operations.

The hardest part was not the analysis. It was getting agreement on the category names, because each team wanted the labels that made their area look smaller. Once the taxonomy was fixed and boring, it started producing useful counts within a month.

• Customer Operations
  Customer Health Framework →

  A framework for reading customer signals, separating recoverable customers from finalized losses, and matching an intervention to the reason rather than the symptom.

• Enterprise Customer Success
  Incident Communication Strategy →

  A repeatable way to explain a live product problem to enterprise customers: what is broken, what is being fixed now, what is being fixed properly, and who tells whom.