AI SEO Statistics: Grocery Delivery Service (2026-07 edition)
15 questions · 45 AI responses · 3 models · measured 2026-07-05
The question bank
The questions we tested — sampled from real buyer journeys in grocery delivery service.
Each model answered every question once, same wording, same day. These are the prompts behind every percentage on this page.
Show all 15 questions
Model by model
17-point average divergence: which AI you ask changes the answer.
The divergence index is the average gap between the most and least likely model per behavior. Higher = the models disagree more about grocery delivery service buyers.
| ChatGPT | Claude | Gemini | Consensus | |
|---|---|---|---|---|
| Recommends hiring a professional | 47% | 53% | 53% | 93% |
| Suggests DIY first | 13% | 13% | 7% | 93% |
| Names specific providers | 53% | 67% | 80% | 73% |
| Gives price or cost info | 20% | 27% | 60% | 60% |
| Tells to check reviews | 13% | 20% | 0% | 73% |
| Tells to verify credentials | 0% | 0% | 0% | 100% |
| Mentions case studies / portfolio | 0% | 0% | 0% | 100% |
| Mentions local proximity | 33% | 40% | 40% | 53% |
| Gives selection criteria | 33% | 60% | 47% | 40% |
| Warns about red flags | 0% | 7% | 7% | 93% |
| Asks a clarifying question | 40% | 67% | 0% | 27% |
| Recommends multiple quotes | 7% | 7% | 7% | 80% |
By model
How each assistant handled Grocery Delivery Service questions.
Reading the 45 answers model by model shows how differently the three assistants treat the same grocery delivery service questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 53.3% (Claude) down to 46.7% (ChatGPT), a 7-point gap on an identical question set.
Across the 15 grocery delivery service answers it produced, ChatGPT recommended hiring a professional in 46.7% of them and suggested a DIY approach first 13.3% of the time. It named a specific provider in 53.3% of answers (about 3 distinct providers per answer) and included price or cost information 20% of the time. ChatGPT asked a clarifying question before answering in 40% of cases, warned about red flags or scams in 0%, and told the buyer to verify credentials in 0%, averaging 410 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 33.3%; a selection-criteria checklist appeared in 33.3% of its answers and a recommendation to gather multiple quotes in 6.7%.
Across the 15 grocery delivery service answers it produced, Claude recommended hiring a professional in 53.3% of them and suggested a DIY approach first 13.3% of the time. It named a specific provider in 66.7% of answers (about 3.5 distinct providers per answer) and included price or cost information 26.7% of the time. Claude asked a clarifying question before answering in 66.7% of cases, warned about red flags or scams in 6.7%, and told the buyer to verify credentials in 0%, averaging 255 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 40%; a selection-criteria checklist appeared in 60% of its answers and a recommendation to gather multiple quotes in 6.7%.
Across the 15 grocery delivery service answers it produced, Gemini recommended hiring a professional in 53.3% of them and suggested a DIY approach first 6.7% of the time. It named a specific provider in 80% of answers (about 4.5 distinct providers per answer) and included price or cost information 60% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 6.7%, and told the buyer to verify credentials in 0%, averaging 228 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 40%; a selection-criteria checklist appeared in 46.7% of its answers and a recommendation to gather multiple quotes in 6.7%.
Taken together, Claude is the assistant most likely to route a grocery delivery service buyer to a professional (53.3%) and ChatGPT the least (46.7%). ChatGPT produced the longest answers, at 410 words on average. Specific providers were named most often by Gemini (80%) — even there, roughly one answer in 1 carried a name.
Where they disagree
The behaviors where the choice of model changes the answer.
The divergence index for this study is 17.4 points — the average distance between the most and least likely model across the coded behaviors. The gaps below are where which assistant a grocery delivery service buyer happens to ask matters most:
- Asks a clarifying question: from 0% (Gemini) to 66.7% (Claude) — a 67-point spread.
- Gives price or cost information: from 20% (ChatGPT) to 60% (Gemini) — a 40-point spread.
- Names a specific provider: from 53.3% (ChatGPT) to 80% (Gemini) — a 27-point spread.
- Gives selection criteria: from 33.3% (ChatGPT) to 60% (Claude) — a 27-point spread.
- Tells the buyer to check reviews: from 0% (Gemini) to 20% (Claude) — a 20-point spread.
The widest single gap — asks a clarifying question, 67 points — means a grocery delivery service buyer can receive materially different guidance on the same question depending only on which assistant they happen to open, so any visibility strategy built on a single model's behavior describes only part of the grocery delivery service market.
Where they agree
The points of near-consensus in Grocery Delivery Service.
On other behaviors the three models move almost in lockstep — the points of near-consensus for grocery delivery service, where all three landed within a few points of each other:
- Tells the buyer to verify credentials: 0% across all three models.
- Mentions case studies or portfolio: 0% across all three models.
- Recommends multiple quotes: 6.7% across all three models.
- Recommends hiring a professional: 46.7%–53.3% across all three (a 7-point spread).
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" (26.7%).
Every behavior, measured
All twelve coded behaviors for Grocery Delivery Service, averaged across the three models.
The behaviors AI models reproduce most often for grocery delivery service are names a specific provider (66.7% on average), recommends hiring a professional (51.1%) and gives selection criteria (46.7%); the rarest are mentions case studies or portfolio (0%), tells the buyer to verify credentials (0%) and warns about red flags or scams (4.5%). Each figure below is the share of a model's 15 answers in which the behavior appeared at least once, averaged across the 3 models with the full per-model range in parentheses:
- Names a specific provider: 66.7% on average (ChatGPT 53.3%, Claude 66.7%, Gemini 80%) — a 27-point spread.
- Recommends hiring a professional: 51.1% on average (ChatGPT 46.7%, Claude 53.3%, Gemini 53.3%) — a 7-point spread.
- Gives selection criteria: 46.7% on average (ChatGPT 33.3%, Claude 60%, Gemini 46.7%) — a 27-point spread.
- Mentions local proximity: 37.8% on average (ChatGPT 33.3%, Claude 40%, Gemini 40%) — a 7-point spread.
- Gives price or cost information: 35.6% on average (ChatGPT 20%, Claude 26.7%, Gemini 60%) — a 40-point spread.
- Asks a clarifying question: 35.6% on average (ChatGPT 40%, Claude 66.7%, Gemini 0%) — a 67-point spread.
- Suggests a DIY approach first: 11.1% on average (ChatGPT 13.3%, Claude 13.3%, Gemini 6.7%) — a 7-point spread.
- Tells the buyer to check reviews: 11.1% on average (ChatGPT 13.3%, Claude 20%, Gemini 0%) — a 20-point spread.
- Recommends multiple quotes: 6.7% on average (ChatGPT 6.7%, Claude 6.7%, Gemini 6.7%).
- Warns about red flags or scams: 4.5% on average (ChatGPT 0%, Claude 6.7%, Gemini 6.7%) — a 7-point spread.
- Tells the buyer to verify credentials: 0% on average (ChatGPT 0%, Claude 0%, Gemini 0%).
- Mentions case studies or portfolio: 0% on average (ChatGPT 0%, Claude 0%, Gemini 0%).
Trust signals
How well the models protect the grocery delivery service buyer.
Beyond whether to hire, the rubric codes how carefully each assistant protects the grocery delivery service buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 11.1% of answers on average. Verifying credentials or certifications appeared in 0%. Warning about red flags or scams appeared in 4.5%.
On structuring the decision, a selection-criteria checklist showed up in 46.7% of answers on average and a recommendation to gather multiple quotes in 6.7%. The single least-reproduced protective signal for grocery delivery service 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.
Referral behavior
Do AI models name Grocery Delivery Service providers?
For service providers the decisive question is whether these systems name anyone at all. Across 45 grocery delivery service answers, a specific provider was named in 66.7% of responses on average — roughly 3.7 distinct providers per answer. In practice the assistants behave far more as an explanatory layer than as a referral engine for grocery delivery service: visibility comes from being the reasoning a model reproduces, not from being the named recommendation.
The question set
What these 15 Grocery Delivery Service questions cover.
The 15 questions behind every percentage on this page were drawn from real grocery delivery service (ecommerce / online retail; 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 grocery delivery service 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.
How to read this
A note on the numbers.
A percentage here is the share of a model's 15 answers in which the behavior appeared at least once — not a confidence score. Because each model answered every question exactly once on 2026-07-05, the figures describe this specific grocery delivery service question set and snapshot rather than a general prior. The full protocol and coding rubric are documented in the study methodology.
Methodology
A controlled snapshot, documented end to end.
15 standardized buyer questions per industry, one response per model per question (ChatGPT (gpt-5-mini), Claude (claude-sonnet-5), Gemini (gemini-3-flash-preview)), collected 2026-07-05, coded against a fixed 12-behavior rubric with human QA. AI outputs vary with model version, location and time — figures describe this sample and window, and are refreshed each edition. Read the full methodology →