How to analyze stated reasons for customer cancellations
Cancellation reasons can show where expectations, value or product fit need attention. Organizing them is useful when the goal is to learn from what customers explicitly reported.
Start with the right material.
- What you provide
- a visible cancellation-feedback export or table.
- The intended result
- Group explicitly stated cancellation reasons and count the selected sample.
How the workflow works.
Keep each stated reason linked to its source and distinguish multiple reasons within one response. Use a clear category scheme while retaining an option for unclear or unstated explanations.
What to check in the result.
Review the selection and denominator before comparing reason frequencies. Silence is not evidence of a particular cause, and the analysis should not infer private circumstances from a brief cancellation note.
Import the CSV with a consistent delimiter and inspect text identifiers, dates and amounts before using spreadsheet totals. Keep the original file available while checking any automatic type conversion.
Learn from the worked example.
The downloadable CSV example uses these columns: Stated reason, Count, Selected responses. Compare a complete record with the source before sorting, combining or importing your own output.
The supplied example is illustrative. It is not a recorded run on your data.
Download the example ↓Use it with your own material.
- Open the source you want to work with and activate WebAct on that tab.
- Copy the task from the hero, add any required fields or preferences, and review the proposed actions.
- Compare the first result with your source. Ask for a specific correction or refinement where needed.