AI SEO Statistics: Dating (2026-07 edition)

Reading the 120 answers model by model shows how differently the three assistants treat the same dating questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 72.5% (ChatGPT) down to 55% (Gemini), a 18-point gap on an identical question set.

Across the 40 dating answers it produced, ChatGPT recommended hiring a professional in 72.5% of them and suggested a DIY approach first 10% of the time. It named a specific provider in 10% of answers (about 0.4 distinct providers per answer) and included price or cost information 20% of the time. ChatGPT asked a clarifying question before answering in 45% of cases, warned about red flags or scams in 20%, and told the buyer to verify credentials in 22.5%, averaging 494 words per answer. On the remaining cues it told the buyer to check reviews in 40%, pointed to case studies or a portfolio in 35%, and framed the choice around local proximity in 30%; a selection-criteria checklist appeared in 45% of its answers and a recommendation to gather multiple quotes in 12.5%.

Across the 40 dating answers it produced, Claude recommended hiring a professional in 57.5% of them and suggested a DIY approach first 17.5% of the time. It named a specific provider in 12.5% of answers (about 0.4 distinct providers per answer) and included price or cost information 30% of the time. Claude asked a clarifying question before answering in 65% of cases, warned about red flags or scams in 32.5%, and told the buyer to verify credentials in 12.5%, averaging 274 words per answer. On the remaining cues it told the buyer to check reviews in 32.5%, pointed to case studies or a portfolio in 17.5%, and framed the choice around local proximity in 20%; a selection-criteria checklist appeared in 42.5% of its answers and a recommendation to gather multiple quotes in 2.5%.

Across the 40 dating answers it produced, Gemini recommended hiring a professional in 55% of them and suggested a DIY approach first 0% of the time. It named a specific provider in 45% of answers (about 1.5 distinct providers per answer) and included price or cost information 25% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 12.5%, and told the buyer to verify credentials in 0%, averaging 287 words per answer. On the remaining cues it told the buyer to check reviews in 0%, 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 25% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, ChatGPT is the assistant most likely to route a dating buyer to a professional (72.5%) and Gemini the least (55%). ChatGPT produced the longest answers, at 494 words on average. Specific providers were named most often by Gemini (45%) — even there, roughly one answer in 2 carried a name.

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

• Gives price or cost information: 20%–30% across all three (a 10-point spread).
• Mentions local proximity: 20%–30% across all three (a 10-point spread).
• Recommends multiple quotes: 0%–12.5% across all three (a 13-point spread).
• Recommends hiring a professional: 55%–72.5% across all three (a 18-point spread).

Measured question by question, the three assistants coded a response the same way most consistently on "recommends multiple quotes" (identical coding in 87.5% of questions) and least consistently on "asks a clarifying question" (22.5%).

Beyond whether to hire, the rubric codes how carefully each assistant protects the dating buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 24.2% of answers on average. Verifying credentials or certifications appeared in 11.7%. Warning about red flags or scams appeared in 21.7%.

On structuring the decision, a selection-criteria checklist showed up in 37.5% of answers on average and a recommendation to gather multiple quotes in 5%. The single least-reproduced protective signal for dating is "recommends multiple quotes" at 5% 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 dating (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 dating 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.