Original research · 2026-07 edition

AI SEO Statistics: Personal Injury Law Firm (2026-07 edition)

15 questions · 45 AI responses · 3 models · measured 2026-07-04

The question bank

The questions we tested — sampled from real buyer journeys in personal injury law firm.

Each model answered every question once, same wording, same day. These are the prompts behind every percentage on this page.

I got rear-ended and my neck hurts but the car damage is minor, is it even worth calling a lawyer or should I just go through insurance?
Can I handle a slip and fall claim myself if the store already offered me a small settlement for my medical bills?
What specific things should I look for in a lawyer's track record if I have a complex medical malpractice claim?
How does the contingency fee structure work and will I be responsible for filing fees if we don't win the case?
Is it better to hire a huge law firm with lots of commercials or a small local attorney who might give me more personal attention?
I need a personal injury lawyer near me who has experience specifically with commercial trucking accidents and federal safety regulations.
What are the red flags I should watch out for during a free consultation with a personal injury attorney?
The insurance adjuster is pressuring me to sign a release just three days after my accident, should I hire a lawyer before I sign anything?
Show all 15 questions
I was hit by a car while walking and the driver didn't have insurance, what are my legal options for getting my hospital bills paid?
How long does the average personal injury case take to settle if we have to go to discovery and depositions?
What documents and evidence should I start collecting right now to make sure my lawyer has everything they need for a strong case?
How do attorneys actually calculate the dollar amount for pain and suffering versus just adding up my medical receipts?
If I'm not happy with how slowly my current lawyer is moving, can I fire them and hire a new firm without paying double the fees?
Do I need a workers comp specialist or a personal injury lawyer if I was injured on a job site by a subcontractor?
What happens if I was partially at fault for the accident, can I still hire a lawyer to recover some of my damages?

Model by model

21-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 personal injury law firm buyers.

Behavior rates across 15 personal injury law firm buyer questions, 2026-07 edition. Last column: average across models.
ChatGPTClaudeGeminiConsensus
Recommends hiring a professional87%93%60%67%
Suggests DIY first20%13%0%80%
Names specific providers0%0%0%100%
Gives price or cost info33%40%47%53%
Tells to check reviews20%20%0%73%
Tells to verify credentials20%20%7%87%
Mentions case studies / portfolio20%7%7%73%
Mentions local proximity33%20%13%60%
Gives selection criteria33%40%27%73%
Warns about red flags27%40%20%67%
Asks a clarifying question80%67%7%13%
Recommends multiple quotes20%13%0%80%

By model

How each assistant handled Personal Injury Law Firm questions.

Reading the 45 answers model by model shows how differently the three assistants treat the same personal injury law firm questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 93.3% (Claude) down to 60% (Gemini), a 33-point gap on an identical question set.

Across the 15 personal injury law firm answers it produced, ChatGPT recommended hiring a professional in 86.7% of them and suggested a DIY approach first 20% 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. ChatGPT asked a clarifying question before answering in 80% of cases, warned about red flags or scams in 26.7%, and told the buyer to verify credentials in 20%, averaging 537 words per answer. On the remaining cues it told the buyer to check reviews in 20%, pointed to case studies or a portfolio in 20%, 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 20%.

Across the 15 personal injury law firm answers it produced, Claude recommended hiring a professional in 93.3% of them and suggested a DIY approach first 13.3% of the time. It named a specific provider in 0% of answers (about 0 distinct providers per answer) and included price or cost information 40% of the time. Claude asked a clarifying question before answering in 66.7% of cases, warned about red flags or scams in 40%, and told the buyer to verify credentials in 20%, averaging 312 words per answer. On the remaining cues it told the buyer to check reviews in 20%, pointed to case studies or a portfolio in 6.7%, and framed the choice around local proximity in 20%; a selection-criteria checklist appeared in 40% of its answers and a recommendation to gather multiple quotes in 13.3%.

Across the 15 personal injury law firm answers it produced, Gemini recommended hiring a professional in 60% 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 46.7% of the time. Gemini asked a clarifying question before answering in 6.7% of cases, warned about red flags or scams in 20%, and told the buyer to verify credentials in 6.7%, averaging 294 words per answer. On the remaining cues it told the buyer to check reviews in 0%, pointed to case studies or a portfolio in 6.7%, and framed the choice around local proximity in 13.3%; a selection-criteria checklist appeared in 26.7% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, Claude is the assistant most likely to route a personal injury law firm buyer to a professional (93.3%) and Gemini the least (60%). ChatGPT produced the longest answers, at 537 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.

The divergence index for this study is 20.7 points — the average distance between the most and least likely model across the coded behaviors. The gaps below are where which assistant a personal injury law firm buyer happens to ask matters most:

  • Asks a clarifying question: from 6.7% (Gemini) to 80% (ChatGPT) — a 73-point spread.
  • Recommends hiring a professional: from 60% (Gemini) to 93.3% (Claude) — a 33-point spread.
  • Suggests a DIY approach first: from 0% (Gemini) to 20% (ChatGPT) — a 20-point spread.
  • Tells the buyer to check reviews: from 0% (Gemini) to 20% (ChatGPT) — a 20-point spread.
  • Mentions local proximity: from 13.3% (Gemini) to 33.3% (ChatGPT) — a 20-point spread.

The widest single gap — asks a clarifying question, 73 points — means a personal injury law firm 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 personal injury law firm market.

Where they agree

The points of near-consensus in Personal Injury Law Firm.

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

  • Names a specific provider: 0% across all three models.
  • Tells the buyer to verify credentials: 6.7%–20% across all three (a 13-point spread).
  • Mentions case studies or portfolio: 6.7%–20% across all three (a 13-point spread).
  • Gives selection criteria: 26.7%–40% across all three (a 13-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" (13.3%).

Every behavior, measured

All twelve coded behaviors for Personal Injury Law Firm, averaged across the three models.

The behaviors AI models reproduce most often for personal injury law firm are recommends hiring a professional (80% on average), asks a clarifying question (51.1%) and gives price or cost information (40%); the rarest are names a specific provider (0%), recommends multiple quotes (11.1%) and mentions case studies or portfolio (11.1%). 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: 80% on average (ChatGPT 86.7%, Claude 93.3%, Gemini 60%) — a 33-point spread.
  • Asks a clarifying question: 51.1% on average (ChatGPT 80%, Claude 66.7%, Gemini 6.7%) — a 73-point spread.
  • Gives price or cost information: 40% on average (ChatGPT 33.3%, Claude 40%, Gemini 46.7%) — a 13-point spread.
  • Gives selection criteria: 33.3% on average (ChatGPT 33.3%, Claude 40%, Gemini 26.7%) — a 13-point spread.
  • Warns about red flags or scams: 28.9% on average (ChatGPT 26.7%, Claude 40%, Gemini 20%) — a 20-point spread.
  • Mentions local proximity: 22.2% on average (ChatGPT 33.3%, Claude 20%, Gemini 13.3%) — a 20-point spread.
  • Tells the buyer to verify credentials: 15.6% on average (ChatGPT 20%, Claude 20%, Gemini 6.7%) — a 13-point spread.
  • Tells the buyer to check reviews: 13.3% on average (ChatGPT 20%, Claude 20%, Gemini 0%) — a 20-point spread.
  • Suggests a DIY approach first: 11.1% on average (ChatGPT 20%, Claude 13.3%, Gemini 0%) — a 20-point spread.
  • Mentions case studies or portfolio: 11.1% on average (ChatGPT 20%, Claude 6.7%, Gemini 6.7%) — a 13-point spread.
  • Recommends multiple quotes: 11.1% on average (ChatGPT 20%, Claude 13.3%, Gemini 0%) — a 20-point spread.
  • Names a specific provider: 0% on average (ChatGPT 0%, Claude 0%, Gemini 0%).

Trust signals

How well the models protect the personal injury law firm buyer.

Beyond whether to hire, the rubric codes how carefully each assistant protects the personal injury law firm buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 13.3% of answers on average. Verifying credentials or certifications appeared in 15.6%. Warning about red flags or scams appeared in 28.9%.

On structuring the decision, a selection-criteria checklist showed up in 33.3% of answers on average and a recommendation to gather multiple quotes in 11.1%. The single least-reproduced protective signal for personal injury law firm is "recommends multiple quotes" at 11.1% 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 Personal Injury Law Firm providers?

For service providers the decisive question is whether these systems name anyone at all. Across 45 personal injury law firm answers, a specific provider was named in 0% of responses on average — roughly 0 distinct providers per answer. In practice the assistants behave far more as an explanatory layer than as a referral engine for personal injury law firm: visibility comes from being the reasoning a model reproduces, not from being the named recommendation.

The question set

What these 15 Personal Injury Law Firm questions cover.

The 15 questions behind every percentage on this page were drawn from real personal injury law firm (legal 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 personal injury law firm 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 2026-07-04, the figures describe this specific personal injury law firm 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 2026-07-04, 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 →