AI SEO Statistics: Ecommerce (2026-07 edition)

Reading the 120 answers model by model shows how differently the three assistants treat the same ecommerce questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 25% (ChatGPT) down to 5% (Gemini), a 20-point gap on an identical question set.

Across the 40 ecommerce answers it produced, ChatGPT recommended hiring a professional in 25% of them and suggested a DIY approach first 22.5% of the time. It named a specific provider in 32.5% of answers (about 2 distinct providers per answer) and included price or cost information 25% of the time. ChatGPT asked a clarifying question before answering in 55% of cases, warned about red flags or scams in 7.5%, and told the buyer to verify credentials in 12.5%, averaging 482 words per answer. On the remaining cues it told the buyer to check reviews in 22.5%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 15%; a selection-criteria checklist appeared in 57.5% of its answers and a recommendation to gather multiple quotes in 0%.

Across the 40 ecommerce answers it produced, Claude recommended hiring a professional in 12.5% of them and suggested a DIY approach first 12.5% of the time. It named a specific provider in 50% of answers (about 2.7 distinct providers per answer) and included price or cost information 27.5% of the time. Claude asked a clarifying question before answering in 62.5% of cases, warned about red flags or scams in 17.5%, and told the buyer to verify credentials in 12.5%, averaging 264 words per answer. On the remaining cues it told the buyer to check reviews in 27.5%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 10%; a selection-criteria checklist appeared in 70% of its answers and a recommendation to gather multiple quotes in 0%.

Across the 40 ecommerce answers it produced, Gemini recommended hiring a professional in 5% of them and suggested a DIY approach first 12.5% of the time. It named a specific provider in 65% of answers (about 2.8 distinct providers per answer) and included price or cost information 32.5% of the time. Gemini asked a clarifying question before answering in 10% of cases, warned about red flags or scams in 12.5%, and told the buyer to verify credentials in 5%, averaging 222 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 2.5%; a selection-criteria checklist appeared in 47.5% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, ChatGPT is the assistant most likely to route an ecommerce buyer to a professional (25%) and Gemini the least (5%). ChatGPT produced the longest answers, at 482 words on average. Specific providers were named most often by Gemini (65%) — 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 ecommerce, where all three landed within a few points of each other:

• Mentions case studies or portfolio: 0% across all three models.
• Recommends multiple quotes: 0% across all three models.
• Gives price or cost information: 25%–32.5% across all three (a 8-point spread).
• Tells the buyer to verify credentials: 5%–12.5% across all three (a 8-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 "asks a clarifying question" (30%).

Beyond whether to hire, the rubric codes how carefully each assistant protects the ecommerce buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 16.7% of answers on average. Verifying credentials or certifications appeared in 10%. Warning about red flags or scams appeared in 12.5%.

On structuring the decision, a selection-criteria checklist showed up in 58.3% of answers on average and a recommendation to gather multiple quotes in 0%. The single least-reproduced protective signal for ecommerce is "recommends multiple quotes" 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 40 questions behind every percentage on this page were drawn from real ecommerce / online retail (DTC brands, online stores) buyer journeys, expanded from 4 seed prompts. Each was put to all 3 models once, with identical wording, so the rates above describe how the assistants handled this exact ecommerce 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.