Original research · 2026-07 edition

AI SEO Statistics: Therapist (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 therapist.

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

How do I know if I actually need a therapist or if I'm just going through a temporary rough patch?
Is it better to see a psychologist or a licensed clinical social worker for long-term depression?
What are the red flags I should look for during a first consultation with a new therapist?
I have a high-deductible insurance plan; is it cheaper to pay a self-pay cash rate or use my benefits?
Can a therapist help me with career burnout, or should I be looking for a life coach instead?
What is the average hourly rate for a private practice therapist in a major city right now?
I need someone who specializes in postpartum anxiety; what specific credentials should I be checking for?
How can I tell if a therapist's eclectic approach is actually effective for treating PTSD?
Show all 15 questions
What are the pros and cons of doing virtual therapy versus going into a physical office for sessions?
I am looking for a therapist who shares my cultural background; what is the best way to filter for that specifically?
If I do not feel a connection with my therapist after three sessions, is it time to move on or should I keep trying?
Does sliding scale pricing mean I will be seen by a trainee or student instead of a licensed professional?
My partner and I are fighting constantly; should we start with couples counseling or do individual therapy first?
How long does it typically take to see actual progress when treating generalized anxiety disorder?
Are there specific questions I should ask to ensure a therapist is truly LGBTQ+ affirming and not just friendly?

Model by model

19-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 therapist buyers.

Behavior rates across 15 therapist buyer questions, 2026-07 edition. Last column: average across models.
ChatGPTClaudeGeminiConsensus
Recommends hiring a professional80%60%47%67%
Suggests DIY first13%0%0%87%
Names specific providers7%13%7%87%
Gives price or cost info0%13%20%73%
Tells to check reviews0%0%0%100%
Tells to verify credentials60%20%20%53%
Mentions case studies / portfolio0%0%0%100%
Mentions local proximity33%20%20%60%
Gives selection criteria67%60%60%53%
Warns about red flags33%27%13%73%
Asks a clarifying question60%60%0%27%
Recommends multiple quotes13%7%0%80%

By model

How each assistant handled Therapist questions.

Reading the 45 answers model by model shows how differently the three assistants treat the same therapist questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 80% (ChatGPT) down to 46.7% (Gemini), a 33-point gap on an identical question set.

Across the 15 therapist answers it produced, ChatGPT recommended hiring a professional in 80% of them and suggested a DIY approach first 13.3% of the time. It named a specific provider in 6.7% of answers (about 0.1 distinct providers per answer) and included price or cost information 0% of the time. ChatGPT asked a clarifying question before answering in 60% of cases, warned about red flags or scams in 33.3%, and told the buyer to verify credentials in 60%, averaging 522 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 33.3%; a selection-criteria checklist appeared in 66.7% of its answers and a recommendation to gather multiple quotes in 13.3%.

Across the 15 therapist answers it produced, Claude recommended hiring a professional in 60% of them and suggested a DIY approach first 0% of the time. It named a specific provider in 13.3% of answers (about 1 distinct providers per answer) and included price or cost information 13.3% of the time. Claude asked a clarifying question before answering in 60% of cases, warned about red flags or scams in 26.7%, and told the buyer to verify credentials in 20%, averaging 293 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 20%; a selection-criteria checklist appeared in 60% of its answers and a recommendation to gather multiple quotes in 6.7%.

Across the 15 therapist answers it produced, Gemini recommended hiring a professional in 46.7% of them and suggested a DIY approach first 0% of the time. It named a specific provider in 6.7% of answers (about 0.8 distinct providers per answer) and included price or cost information 20% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 13.3%, and told the buyer to verify credentials in 20%, averaging 275 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 20%; a selection-criteria checklist appeared in 60% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, ChatGPT is the assistant most likely to route a therapist buyer to a professional (80%) and Gemini the least (46.7%). ChatGPT produced the longest answers, at 522 words on average. Specific providers were named most often by Claude (13.3%) — even there, roughly one answer in 8 carried a name.

Where they disagree

The behaviors where the choice of model changes the answer.

The divergence index for this study is 18.9 points — the average distance between the most and least likely model across the coded behaviors. The gaps below are where which assistant a therapist buyer happens to ask matters most:

  • Asks a clarifying question: from 0% (Gemini) to 60% (ChatGPT) — a 60-point spread.
  • Tells the buyer to verify credentials: from 20% (Claude) to 60% (ChatGPT) — a 40-point spread.
  • Recommends hiring a professional: from 46.7% (Gemini) to 80% (ChatGPT) — a 33-point spread.
  • Gives price or cost information: from 0% (ChatGPT) to 20% (Gemini) — a 20-point spread.
  • Warns about red flags or scams: from 13.3% (Gemini) to 33.3% (ChatGPT) — a 20-point spread.

The widest single gap — asks a clarifying question, 60 points — means a therapist 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 therapist market.

Where they agree

The points of near-consensus in Therapist.

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

  • Tells the buyer to check reviews: 0% across all three models.
  • Mentions case studies or portfolio: 0% across all three models.
  • Names a specific provider: 6.7%–13.3% across all three (a 7-point spread).
  • Gives selection criteria: 60%–66.7% 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 check reviews" (identical coding in 100% of questions) and least consistently on "asks a clarifying question" (26.7%).

Every behavior, measured

All twelve coded behaviors for Therapist, averaged across the three models.

The behaviors AI models reproduce most often for therapist are recommends hiring a professional (62.2% on average), gives selection criteria (62.2%) and asks a clarifying question (40%); the rarest are mentions case studies or portfolio (0%), tells the buyer to check reviews (0%) and suggests a DIY approach first (4.4%). 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: 62.2% on average (ChatGPT 80%, Claude 60%, Gemini 46.7%) — a 33-point spread.
  • Gives selection criteria: 62.2% on average (ChatGPT 66.7%, Claude 60%, Gemini 60%) — a 7-point spread.
  • Asks a clarifying question: 40% on average (ChatGPT 60%, Claude 60%, Gemini 0%) — a 60-point spread.
  • Tells the buyer to verify credentials: 33.3% on average (ChatGPT 60%, Claude 20%, Gemini 20%) — a 40-point spread.
  • Mentions local proximity: 24.4% on average (ChatGPT 33.3%, Claude 20%, Gemini 20%) — a 13-point spread.
  • Warns about red flags or scams: 24.4% on average (ChatGPT 33.3%, Claude 26.7%, Gemini 13.3%) — a 20-point spread.
  • Gives price or cost information: 11.1% on average (ChatGPT 0%, Claude 13.3%, Gemini 20%) — a 20-point spread.
  • Names a specific provider: 8.9% on average (ChatGPT 6.7%, Claude 13.3%, Gemini 6.7%) — a 7-point spread.
  • Recommends multiple quotes: 6.7% on average (ChatGPT 13.3%, Claude 6.7%, Gemini 0%) — a 13-point spread.
  • Suggests a DIY approach first: 4.4% on average (ChatGPT 13.3%, Claude 0%, Gemini 0%) — a 13-point spread.
  • Tells the buyer to check reviews: 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 therapist buyer.

Beyond whether to hire, the rubric codes how carefully each assistant protects the therapist buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 0% of answers on average. Verifying credentials or certifications appeared in 33.3%. Warning about red flags or scams appeared in 24.4%.

On structuring the decision, a selection-criteria checklist showed up in 62.2% of answers on average and a recommendation to gather multiple quotes in 6.7%. The single least-reproduced protective signal for therapist is "tells the buyer to check reviews" 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 Therapist providers?

For service providers the decisive question is whether these systems name anyone at all. Across 45 therapist answers, a specific provider was named in 8.9% of responses on average — roughly 0.6 distinct providers per answer. In practice the assistants behave far more as an explanatory layer than as a referral engine for therapist: visibility comes from being the reasoning a model reproduces, not from being the named recommendation.

The question set

What these 15 Therapist questions cover.

The 15 questions behind every percentage on this page were drawn from real therapist (healthcare 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 therapist 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 therapist 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 →