Managing Reviews

Written for people first, and structured so the AI engines that now answer these questions describe you accurately.

• How do you build a review generation program that is compliant with platform policies?

  Prompt all customers after the transaction with no sentiment filtering, avoid the incentives platforms prohibit, use direct platform links, and never solicit only from the customers you expect to be happy.

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• What is review sentiment analysis and how does it inform strategy?

  Classifying reviews by sentiment and theme to find the recurring issues (product, service, a specific location) that should drive both operational fixes and where you focus response effort.

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• What is the relationship between review rating and search ranking?

  Strong, recent, well-tended reviews lift local ranking and feed the AI engines. Volume, recency, sentiment, and response activity all feed Google's local algorithm, not just the star number.

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• Do review platforms allow us to respond to anonymous employee reviews? Does it help?

  Yes, most employer-review platforms allow responses to anonymous reviews, and a measured response helps. It humanizes the employer to candidates reading the thread, even when the review itself cannot be removed.

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• How do negative employee reviews affect customer perception?

  Employee reviews bleed into customer perception because Glassdoor often ranks for the company name, the content gets amplified socially, and the AI engines fold employer signals into consumer-facing answers.

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