Managing Reviews

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

• How do reviews feed into AI-generated responses about your business?

  AI engines ingest review platforms as authoritative third-party evidence and paraphrase the recurring themes across them as 'customers say.' That makes review content directly material to what the engines tell people about your business.

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• A competitor is posting fake reviews and news. Can ORM address competitor sabotage?

  Yes. Competitor sabotage is addressed by running several tracks in parallel: platform reporting to remove the fake reviews, legal escalation where the activity is demonstrably defamatory and attributable, continuous monitoring of the affected channels because sabotage is a campaign rather than a single act, and authoritative content that displaces the planted material - all of it aimed at protecting the synthesized answer buyers actually read.

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• What is the difference between review management and reputation management?

  Review management is the subset that works the review platforms specifically - Google, Glassdoor, Trustpilot, G2. Reputation management is the whole field: organic search, the AI engines, Wikipedia and the Knowledge Panel, and the entity signals across every channel that shapes how an organization is perceived. Reviews are one input into that larger picture.

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• How do you handle fake or malicious reviews?

  Handle fake or malicious reviews on three parallel tracks: report them through the platform's policy-violation process, escalate legally where the review is a false assertion of fact (not opinion) and the harm and attribution justify it, and post a measured public response that gives future readers context. Because many fake reviews are never removed, the realistic goal is to neutralize their effect, not erase them.

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• Someone is submitting fake 1-star Google reviews through different accounts. What recourse do I have?

  Run three tracks at once: flag each review through Google's process citing the specific policy it breaks, pursue the source legally where the accounts can be attributed and the conduct is defamatory, and accelerate authentic recent reviews to dilute the attack's weight. Coordinated fake-review attacks are containable, but removal is slow and inconsistent, so the realistic goal is containment and dilution while the removal process grinds.

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