AI SEO Statistics: Criminal Defense Lawyer (2026-07 edition)
15 questions · 45/45 expected AI responses · 3 models · measured 2026-07-04
Apply these findings to your criminal defense lawyer SEO strategy.
This benchmark explains how AI assistants advise buyers. The related service page turns those findings into the technical, content, authority, and conversion priorities for this market.
The question bank
The questions we tested: a frozen buyer-intent benchmark for criminal defense lawyer.
The question set was curated from a predefined buyer-intent taxonomy and held constant for this edition. Each model received the same wording. These are the prompts behind every percentage on this page.
Show all 15 questions
Model by model
26.3% question-level model disagreement.
This rate is the average pairwise disagreement between binary behavior codes across questions and behaviors. It is not the gap between the highest and lowest aggregated model percentages.
Behavior prevalence across 15 criminal defense lawyer benchmark questions, 2026-07 edition. Last column: equal-model mean.
| Behavior | ChatGPT | Claude | Gemini | Equal-model mean |
|---|---|---|---|---|
| Recommends hiring a professional | 86.7% | 86.7% | 60% | 77.8% |
| Suggests DIY first | 0% | 6.7% | 6.7% | 4.5% |
| Names specific providers | 0% | 0% | 0% | 0% |
| Gives price or cost info | 26.7% | 26.7% | 33.3% | 28.9% |
| Tells to check reviews | 33.3% | 6.7% | 6.7% | 15.6% |
| Tells to verify credentials | 33.3% | 20% | 13.3% | 22.2% |
| Mentions case studies / portfolio | 26.7% | 26.7% | 6.7% | 20% |
| Mentions local proximity | 80% | 80% | 33.3% | 64.4% |
| Gives selection criteria | 73.3% | 80% | 40% | 64.4% |
| Warns about red flags | 33.3% | 33.3% | 6.7% | 24.4% |
| Asks a clarifying question | 86.7% | 80% | 0% | 55.6% |
| Recommends multiple quotes | 46.7% | 40% | 0% | 28.9% |
Question-level agreement
How often all measured models received the same binary code.
Agreement is calculated question by question for each behavior. A high value can coexist with a low behavior prevalence; it means the models usually agreed on whether the behavior appeared.
All-model binary agreement by behavior across 15 benchmark questions.
| Behavior | All-model agreement |
|---|---|
| Recommends hiring a professional | 60% |
| Suggests DIY first | 86.7% |
| Names specific providers | 100% |
| Gives price or cost info | 93.3% |
| Tells to check reviews | 60% |
| Tells to verify credentials | 60% |
| Mentions case studies / portfolio | 73.3% |
| Mentions local proximity | 33.3% |
| Gives selection criteria | 46.7% |
| Warns about red flags | 66.7% |
| Asks a clarifying question | 6.7% |
| Recommends multiple quotes | 40% |
By model
How each assistant handled Criminal Defense Lawyer questions.
Reading the 45 answers model by model shows how differently the three assistants treat the same criminal defense lawyer questions. On the most consequential behavior, whether to send the buyer to a professional at all, the rate ranged from 86.7% (ChatGPT) down to 60% (Gemini), a 27-point gap on an identical question set.
Across the 15 criminal defense lawyer answers it produced, ChatGPT recommended hiring a professional in 86.7% of them and suggested a DIY approach first 0% of the time. It named a specific provider in 0% of answers (about 0 distinct providers per answer) and included price or cost information 26.7% of the time. ChatGPT asked a clarifying question before answering in 86.7% of cases, warned about red flags or scams in 33.3%, and told the buyer to verify credentials in 33.3%, averaging 551 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 26.7%, and framed the choice around local proximity in 80%; a selection-criteria checklist appeared in 73.3% of its answers and a recommendation to gather multiple quotes in 46.7%.
Across the 15 criminal defense lawyer answers it produced, Claude recommended hiring a professional in 86.7% of them and suggested a DIY approach first 6.7% of the time. It named a specific provider in 0% of answers (about 0 distinct providers per answer) and included price or cost information 26.7% of the time. Claude asked a clarifying question before answering in 80% of cases, warned about red flags or scams in 33.3%, and told the buyer to verify credentials in 20%, averaging 325 words per answer. On the remaining cues it told the buyer to check reviews in 6.7%, pointed to case studies or a portfolio in 26.7%, and framed the choice around local proximity in 80%; a selection-criteria checklist appeared in 80% of its answers and a recommendation to gather multiple quotes in 40%.
Across the 15 criminal defense lawyer answers it produced, Gemini recommended hiring a professional in 60% of them and suggested a DIY approach first 6.7% of the time. It named a specific provider in 0% of answers (about 0 distinct providers per answer) and included price or cost information 33.3% 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 13.3%, averaging 253 words per answer. On the remaining cues it told the buyer to check reviews in 6.7%, pointed to case studies or a portfolio in 6.7%, and framed the choice around local proximity in 33.3%; a selection-criteria checklist appeared in 40% of its answers and a recommendation to gather multiple quotes in 0%.
Taken together, ChatGPT is the assistant most likely to route a buyer researching criminal defense lawyer toward professional help (86.7%) and Gemini the least (60%). ChatGPT produced the longest answers, at 551 words on average. No model named a specific provider in more than 0% of answers.
Where they disagree
The behaviors where the choice of model changes the answer.
Question-level model disagreement is 26.3%. This is the average pairwise rate at which models received different binary codes across questions and behaviors. The observed rate spreads below are a separate measure showing where the choice of assistant matters most for a buyer researching criminal defense lawyer:
- Asks a clarifying question: from 0% (Gemini) to 86.7% (ChatGPT). The spread is 87 points.
- Mentions local proximity: from 33.3% (Gemini) to 80% (ChatGPT). The spread is 47 points.
- Recommends multiple quotes: from 0% (Gemini) to 46.7% (ChatGPT). The spread is 47 points.
- Gives selection criteria: from 40% (Gemini) to 80% (Claude). The spread is 40 points.
- Recommends hiring a professional: from 60% (Gemini) to 86.7% (ChatGPT). The spread is 27 points.
The widest single gap concerns asks a clarifying question at 87 points. This means a buyer researching criminal defense lawyer 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 criminal defense lawyer market.
Where they agree
The points of near-consensus in Criminal Defense Lawyer.
On other behaviors the three models move almost in lockstep. The points of near-consensus for criminal defense lawyer, where all three landed within a few points of each other:
- Names a specific provider: 0% across all three models.
- Gives price or cost information: 26.7%–33.3% across all three (a 7-point spread).
- Suggests a DIY approach first: 0%–6.7% across all three (a 7-point spread).
- Tells the buyer to verify credentials: 13.3%–33.3% across all three (a 20-point spread).
Measured question by question, the three assistants coded a response the same way most consistently on "names a specific provider" (identical coding in 100% of questions) and least consistently on "asks a clarifying question" (6.7%).
Every behavior, measured
All twelve coded behaviors for Criminal Defense Lawyer, averaged across the three models.
The behaviors AI models reproduce most often for criminal defense lawyer are recommends hiring a professional (77.8% on average), mentions local proximity (64.4%) and gives selection criteria (64.4%); the rarest are names a specific provider (0%), suggests a DIY approach first (4.5%) and tells the buyer to check reviews (15.6%). 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:
- Recommends hiring a professional: 77.8% on average (ChatGPT 86.7%, Claude 86.7%, Gemini 60%). The spread is 27 points.
- Mentions local proximity: 64.4% on average (ChatGPT 80%, Claude 80%, Gemini 33.3%). The spread is 47 points.
- Gives selection criteria: 64.4% on average (ChatGPT 73.3%, Claude 80%, Gemini 40%). The spread is 40 points.
- Asks a clarifying question: 55.6% on average (ChatGPT 86.7%, Claude 80%, Gemini 0%). The spread is 87 points.
- Gives price or cost information: 28.9% on average (ChatGPT 26.7%, Claude 26.7%, Gemini 33.3%). The spread is 7 points.
- Recommends multiple quotes: 28.9% on average (ChatGPT 46.7%, Claude 40%, Gemini 0%). The spread is 47 points.
- Warns about red flags or scams: 24.4% on average (ChatGPT 33.3%, Claude 33.3%, Gemini 6.7%). The spread is 27 points.
- Tells the buyer to verify credentials: 22.2% on average (ChatGPT 33.3%, Claude 20%, Gemini 13.3%). The spread is 20 points.
- Mentions case studies or portfolio: 20% on average (ChatGPT 26.7%, Claude 26.7%, Gemini 6.7%). The spread is 20 points.
- Tells the buyer to check reviews: 15.6% on average (ChatGPT 33.3%, Claude 6.7%, Gemini 6.7%). The spread is 27 points.
- Suggests a DIY approach first: 4.5% on average (ChatGPT 0%, Claude 6.7%, Gemini 6.7%). The spread is 7 points.
- Names a specific provider: 0% on average (ChatGPT 0%, Claude 0%, Gemini 0%).
Trust signals
How well the models protect the criminal defense lawyer buyer.
Beyond whether to hire, the rubric codes how carefully each assistant protects the criminal defense lawyer buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 15.6% of answers on average. Verifying credentials or certifications appeared in 22.2%. Warning about red flags or scams appeared in 24.4%.
On structuring the decision, a selection-criteria checklist showed up in 64.4% of answers on average and a recommendation to gather multiple quotes in 28.9%. The single least-reproduced protective signal for criminal defense lawyer is "tells the buyer to check reviews" at 15.6% on average. This is 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 Criminal Defense Lawyer providers?
For service providers the decisive question is whether these systems name anyone at all. Across 45 criminal defense lawyer answers, a specific provider was named in 0% of responses on average, or roughly 0 distinct providers per answer. In practice the assistants behave far more as an explanatory layer than as a referral engine for criminal defense lawyer: visibility comes from being the reasoning a model reproduces, not from being the named recommendation.
The question set
What these 15 Criminal Defense Lawyer questions cover.
The 15 questions behind every percentage on this page form a frozen criminal defense lawyer (legal services; buyer hiring decisions for this specific service) buyer-intent benchmark. Each was put to all 3 models once, with identical wording, so the rates above describe how the assistants handled this exact criminal defense lawyer question set rather than 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. It is not a confidence score. Because each model answered every question exactly once on 2026-07-04, the figures describe this specific criminal defense lawyer 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 frozen benchmark questions, one expected response per model per question (ChatGPT API (gpt-5-mini), Claude API (claude-sonnet-5), Gemini API (gemini-3-flash-preview)), collected 2026-07-04 and coded against a fixed 12-behavior rubric. The pipeline validates the schema, recomputes aggregates and reports consistency issues. AI outputs vary with model version, location and time, so the figures describe this edition's exact sample and measurement window. Read the full methodology →
Citation
Cite this edition.
Authority Specialist. “AI SEO Statistics: Criminal Defense Lawyer (2026-07 edition).” AuthoritySpecialist.com. https://authorityspecialist.com/research/ai-seo-statistics/services/legal/criminal-defense-lawyer