AI SEO Statistics: Limo (2026-07 edition)

Reading the 120 answers model by model shows how differently the three assistants treat the same limo questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 45% (Claude) down to 25% (Gemini), a 20-point gap on an identical question set.

Across the 40 limo answers it produced, ChatGPT recommended hiring a professional in 42.5% of them and suggested a DIY approach first 10% of the time. It named a specific provider in 7.5% of answers (about 0.1 distinct providers per answer) and included price or cost information 25% of the time. ChatGPT asked a clarifying question before answering in 60% of cases, warned about red flags or scams in 15%, and told the buyer to verify credentials in 32.5%, averaging 408 words per answer. On the remaining cues it told the buyer to check reviews in 20%, pointed to case studies or a portfolio in 5%, and framed the choice around local proximity in 30%; a selection-criteria checklist appeared in 65% of its answers and a recommendation to gather multiple quotes in 15%.

Across the 40 limo answers it produced, Claude recommended hiring a professional in 45% of them and suggested a DIY approach first 7.5% of the time. It named a specific provider in 7.5% of answers (about 0.1 distinct providers per answer) and included price or cost information 32.5% of the time. Claude asked a clarifying question before answering in 55% of cases, warned about red flags or scams in 17.5%, and told the buyer to verify credentials in 20%, averaging 271 words per answer. On the remaining cues it told the buyer to check reviews in 20%, pointed to case studies or a portfolio in 2.5%, and framed the choice around local proximity in 25%; a selection-criteria checklist appeared in 70% of its answers and a recommendation to gather multiple quotes in 12.5%.

Across the 40 limo answers it produced, Gemini recommended hiring a professional in 25% of them and suggested a DIY approach first 5% of the time. It named a specific provider in 10% of answers (about 0.3 distinct providers per answer) and included price or cost information 45% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 17.5%, and told the buyer to verify credentials in 5%, averaging 275 words per answer. On the remaining cues it told the buyer to check reviews in 2.5%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 15%; a selection-criteria checklist appeared in 45% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, Claude is the assistant most likely to route a limo buyer to a professional (45%) and Gemini the least (25%). ChatGPT produced the longest answers, at 408 words on average. Specific providers were named most often by Gemini (10%) — even there, roughly one answer in 10 carried a name.

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

• Names a specific provider: 7.5%–10% across all three (a 3-point spread).
• Warns about red flags or scams: 15%–17.5% across all three (a 3-point spread).
• Suggests a DIY approach first: 5%–10% across all three (a 5-point spread).
• Mentions case studies or portfolio: 0%–5% across all three (a 5-point spread).

Measured question by question, the three assistants coded a response the same way most consistently on "mentions case studies or portfolio" (identical coding in 92.5% of questions) and least consistently on "asks a clarifying question" (32.5%).

Beyond whether to hire, the rubric codes how carefully each assistant protects the limo buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 14.2% of answers on average. Verifying credentials or certifications appeared in 19.2%. Warning about red flags or scams appeared in 16.7%.

On structuring the decision, a selection-criteria checklist showed up in 60% of answers on average and a recommendation to gather multiple quotes in 9.2%. The single least-reproduced protective signal for limo is "recommends multiple quotes" at 9.2% on average — the clearest opening for content that supplies it, since the models are not yet reliably surfacing that guidance on their own.

The 40 questions behind every percentage on this page were drawn from real limo (professional services; 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 limo 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.