AI SEO Statistics: Insurance Agency (2026-07 edition)

Reading the 45 answers model by model shows how differently the three assistants treat the same insurance agency questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 80% (ChatGPT) down to 46.7% (Gemini), a 33-point gap on an identical question set.

Across the 15 insurance agency answers it produced, ChatGPT recommended hiring a professional in 80% of them and suggested a DIY approach first 13.3% of the time. It named a specific provider in 6.7% of answers (about 0.1 distinct providers per answer) and included price or cost information 0% of the time. ChatGPT asked a clarifying question before answering in 60% of cases, warned about red flags or scams in 13.3%, and told the buyer to verify credentials in 20%, averaging 558 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 20%; a selection-criteria checklist appeared in 66.7% of its answers and a recommendation to gather multiple quotes in 66.7%.

Across the 15 insurance agency answers it produced, Claude recommended hiring a professional in 66.7% of them and suggested a DIY approach first 13.3% of the time. It named a specific provider in 33.3% of answers (about 0.9 distinct providers per answer) and included price or cost information 13.3% of the time. Claude asked a clarifying question before answering in 46.7% of cases, warned about red flags or scams in 20%, and told the buyer to verify credentials in 13.3%, averaging 305 words per answer. On the remaining cues it told the buyer to check reviews in 13.3%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 20%; a selection-criteria checklist appeared in 53.3% of its answers and a recommendation to gather multiple quotes in 53.3%.

Across the 15 insurance agency answers it produced, Gemini recommended hiring a professional in 46.7% of them and suggested a DIY approach first 0% of the time. It named a specific provider in 66.7% of answers (about 2 distinct providers per answer) and included price or cost information 20% 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 6.7%, averaging 307 words per answer. On the remaining cues it told the buyer to check reviews in 0%, 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 40% of its answers and a recommendation to gather multiple quotes in 26.7%.

Taken together, ChatGPT is the assistant most likely to route an insurance agency buyer to a professional (80%) and Gemini the least (46.7%). ChatGPT produced the longest answers, at 558 words on average. Specific providers were named most often by Gemini (66.7%) — even there, roughly one answer in 1 carried a name.

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

• Mentions case studies or portfolio: 0% across all three models.
• Mentions local proximity: 13.3%–20% across all three (a 7-point spread).
• Warns about red flags or scams: 13.3%–20% across all three (a 7-point spread).
• Suggests a DIY approach first: 0%–13.3% across all three (a 13-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 100% of questions) and least consistently on "recommends multiple quotes" (20%).

Beyond whether to hire, the rubric codes how carefully each assistant protects the insurance agency buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 15.5% of answers on average. Verifying credentials or certifications appeared in 13.3%. Warning about red flags or scams appeared in 15.5%.

On structuring the decision, a selection-criteria checklist showed up in 53.3% of answers on average and a recommendation to gather multiple quotes in 48.9%. The single least-reproduced protective signal for insurance agency is "tells the buyer to verify credentials" at 13.3% 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 insurance agency (financial 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 insurance agency 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.