Three complaints about a slow response deserve attention. Whether they establish a worsening trend depends on the period, the total feedback received, and what happened before.
AI can help sort comments. It should not turn a memorable cluster into a conclusion the data cannot support.
Start with a bounded batch: a stated date range, a known number of comments, and a clear source. Remove private details before using an approved tool.
Ask for themes with comment IDs so you can audit the grouping:
Group these de-identified comments into themes. Report the number of comments mentioning each theme and the total comments reviewed. A comment may have multiple themes; say so and do not make the counts sum to 100% unless the categories are exclusive. Show supporting IDs, mixed feedback, and comments that contradict the apparent pattern. Do not infer cause or trend from this batch alone.
For a fictional batch of 20 comments, four may mention speed and three clarity, with one comment in both groups. Reporting seven dissatisfied customers would double-count that overlap.
Read the source comments behind the leading theme. “Slow to respond” and “slow to resolve” may describe different processes and need different action.
Finish with one question you can investigate: where in the process does the delay occur? Assigning blame is not a substitute for identifying the step.
The useful result is a traceable summary and a better next question. Save the period and method so next month’s comparison means something.
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—Future Proof