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Main takeaways: Cornell research shows a one-point increase in Global Review Index score correlates with +0.89% ADR, +0.54% occupancy, and +1.42% RevPAR, worth roughly $71,000 in near-pure profit for a $5M/year hotel Expedia data shows a one-point review score increase drives a 9% ADR increase, and properties scoring 4.0-5.0 generate more than double the conversion

Main takeaways: Gene McCubbin's research shows that a Google rating below 4.0 stars effectively removes a business from AI recommendation results for general queries, regardless of review volume. AI search engines do not downrank low-rated businesses. They exclude them from the discovery set entirely. A 3.8-star property with 400 reviews loses to a 4.1-star competitor

Main takeaways: Most business owners have never searched their own name the way a stranger would, and what they find would surprise them. NAP inconsistencies across directories signal an unmanaged presence to both Google and prospective customers. Dozens of directories auto-create listings for your business without your knowledge, and unclaimed listings cannot be managed or

Main takeaways: Google indexes every word of your review responses, making each reply a permanent part of your searchable footprint. Including your business name in a negative review response pairs your brand with complaint language in Google's index, and that association compounds over time. Repeating the problem keyword in your reply (as in "our hotel

Main takeaways: ChatGPT, Google AI Overviews, and Perplexity now recommend local businesses directly, and the signals they use to evaluate trust go far deeper than star ratings. AI recommendation engines do not browse endlessly; they shortlist. A business that does not make the shortlist of three or four results is not ranked lower, it is