AI SEO Statistics: Resort (2026-07 edition)

Reading the 45 answers model by model shows how differently the three assistants treat the same resort questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 20% (ChatGPT) down to 0% (Gemini), a 20-point gap on an identical question set.

Across the 15 resort answers it produced, ChatGPT recommended hiring a professional in 20% of them and suggested a DIY approach first 40% of the time. It named a specific provider in 13.3% of answers (about 0.5 distinct providers per answer) and included price or cost information 26.7% of the time. ChatGPT asked a clarifying question before answering in 40% of cases, warned about red flags or scams in 20%, and told the buyer to verify credentials in 0%, averaging 509 words per answer. On the remaining cues it told the buyer to check reviews in 26.7%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 6.7%; a selection-criteria checklist appeared in 53.3% of its answers and a recommendation to gather multiple quotes in 0%.

Across the 15 resort answers it produced, Claude recommended hiring a professional in 13.3% of them and suggested a DIY approach first 26.7% of the time. It named a specific provider in 13.3% of answers (about 0.3 distinct providers per answer) and included price or cost information 26.7% of the time. Claude asked a clarifying question before answering in 40% of cases, warned about red flags or scams in 13.3%, and told the buyer to verify credentials in 0%, averaging 281 words per answer. On the remaining cues it told the buyer to check reviews in 33.3%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 13.3%; a selection-criteria checklist appeared in 53.3% of its answers and a recommendation to gather multiple quotes in 0%.

Across the 15 resort answers it produced, Gemini recommended hiring a professional in 0% of them and suggested a DIY approach first 33.3% of the time. It named a specific provider in 40% of answers (about 1.1 distinct providers per answer) and included price or cost information 26.7% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 13.3%, and told the buyer to verify credentials in 0%, averaging 253 words per answer. On the remaining cues it told the buyer to check reviews in 20%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 0%; a selection-criteria checklist appeared in 40% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, ChatGPT is the assistant most likely to route a resort buyer to a professional (20%) and Gemini the least (0%). ChatGPT produced the longest answers, at 509 words on average. Specific providers were named most often by Gemini (40%) — even there, roughly one answer in 3 carried a name.

On other behaviors the three models move almost in lockstep — the points of near-consensus for resort, where all three landed within a few points of each other:

• Gives price or cost information: 26.7% across all three models.
• Tells the buyer to verify credentials: 0% across all three models.
• Mentions case studies or portfolio: 0% across all three models.
• Recommends multiple quotes: 0% across all three models.

Measured question by question, the three assistants coded a response the same way most consistently on "tells the buyer to verify credentials" (identical coding in 100% of questions) and least consistently on "asks a clarifying question" (40%).

Beyond whether to hire, the rubric codes how carefully each assistant protects the resort buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 26.7% of answers on average. Verifying credentials or certifications appeared in 0%. Warning about red flags or scams appeared in 15.5%.

On structuring the decision, a selection-criteria checklist showed up in 48.9% of answers on average and a recommendation to gather multiple quotes in 0%. The single least-reproduced protective signal for resort is "tells the buyer to verify credentials" at 0% on average — the clearest opening for content that supplies it, since the models are not yet reliably surfacing that guidance on their own.

The 15 questions behind every percentage on this page were drawn from real resort (hospitality; buyer hiring decisions for this specific service) buyer journeys. Each was put to all 3 models once, with identical wording, so the rates above describe how the assistants handled this exact resort question set — not a general prior or a hand-picked subset. The full list is shown earlier on this page; the coded percentages are what those specific questions produced.