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How Reviews Affect AI Recommendations

AI reads your reviews more carefully than you think

What is it?

Reviews are like word-of-mouth recommendations for AI. Just like you'd ask a friend "What do people say about this place?" AI does the same thing, except it reads hundreds of reviews in seconds and picks up on patterns you might miss.

AI doesn't just count stars. It reads the actual words customers use. "Amazing coffee and the barista remembered my order" tells a completely different story than "Coffee was fine, nothing special." Both might be 4-star reviews, but AI knows which business to recommend.

Why it matters for your business

We've analyzed thousands of AI recommendations, and here's what moves the needle:

  • Review velocity - businesses with steady, recent reviews outperform those with old reviews, even if the old ones have higher ratings
  • Specific praise - reviews that mention specific services or products give AI concrete details to cite
  • Sentiment consistency - AI trusts businesses where reviews consistently mention the same strengths
  • Response rate - businesses that respond to reviews signal they're active and engaged

What AI looks for in reviews:

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Recency: Reviews from the last 3-6 months carry more weight
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Volume: A steady stream of reviews (even 2-3 per month) beats sporadic bursts
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Specificity: Detailed reviews with service/product names are gold
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Themes: Repeated mentions of "fast service" or "friendly staff" create patterns AI recognizes

Think of it this way: AI is reading your reviews like a human would, but at scale. It picks up on enthusiasm, hesitation, and those little details that make your business unique.

The technical details (for the curious)

AI models use natural language processing (NLP) to analyze review text. They look for sentiment (positive/negative), entity extraction (what specific things are mentioned), and temporal patterns (how sentiment changes over time).

Modern language models like ChatGPT are trained on billions of human conversations, so they understand context and nuance. When a review says "It's okay," the model knows that's lukewarm at best. When it says "Absolutely incredible," the model knows that's genuine enthusiasm.

Review signals AI analyzes:

Sentiment scoreOverall positive/negative ratio
Keyword frequencyCommon themes and topics
Review velocityHow often new reviews appear
Response engagementOwner replies and interaction

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