Your Reputation Agency · United States

Using AI to analyze review themes

Use AI to sort review themes while checking the sample, language, evidence and decisions behind the resulting report.

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AI can help organize a collection of reviews, but a topic label is an interpretation rather than proof. Keep the original review available, define what each category means and have a person check uncertain classifications.

01

Start with a question your team can act on

Decide whether you are investigating delivery delays, confusing prices, staff conduct or another operational issue. Mixing all complaints into one negative category makes it harder to identify a responsible team. Include positive and mixed experiences so the analysis does not become a search for complaints only.

Record the platform, location and time period. A week with three reviews should not be compared directly with a month containing hundreds without showing the difference in sample size.

02

Check a small labeled sample first

For example, 'The food was great, but we waited an hour' contains both a positive product judgment and a service concern. Forcing it into a single positive label would hide the wait-time issue.

  • Define each theme with an example and an exclusion.
  • Review comments containing more than one topic.
  • Keep sentiment separate from whether a factual claim is verified.
  • Check English and Mexican Spanish independently.
  • Leave ambiguous comments unclassified until someone reviews them.

03

Use findings to investigate, not accuse

Connect repeated themes with operating records before changing policy or blaming an employee. A model may confuse sarcasm, a quoted complaint or a regional expression. It cannot determine from wording alone whether a reviewer is a real customer.

Your report should show the number of reviewed items, representative excerpts with unnecessary identifiers removed, uncertain cases and proposed follow-up. Save the category definitions so the next period can be compared on the same basis.

Frequently asked questions

Can AI determine which reviews are fake?

It can flag patterns for review, but a linguistic pattern does not establish authenticity or intent. Assess the available evidence and platform rules separately.

Should every review receive one theme?

Not necessarily. Several themes or an uncertain label can be more accurate than forcing a complex experience into one category.

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Educational information, not legal advice. Outcomes depend on the facts and decisions made by third parties.