Original research · 2026-07 edition

AI SEO Statistics: Recreation Entertainment (2026-07 edition)

40 questions · 120 AI responses · 3 models · measured 2026-07-06

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The question bank

The questions we tested — sampled from real buyer journeys in recreation entertainment.

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

What's the best type of entertainment for a 40th birthday party with about 50 guests?
Is it cheaper to rent a karaoke machine or hire a professional karaoke host?
How much does it usually cost to hire a professional face painter for a three-hour community event?
What are some unique entertainment ideas for a corporate team-building day that isn't just another escape room?
What should I look for in a contract when hiring a professional magician for a kids' party?
How do I know if a mobile petting zoo company follows proper animal welfare standards?
Is a $1,500 budget enough to get a decent live band for a small outdoor wedding?
What are the red flags to watch out for when booking a freelance DJ online?
Show all 40 questions
Can a professional caricature artist work from photos if I don't want them doing live sketches at the event?
How much space does a professional mobile axe-throwing setup actually require?
Should I hire a professional mixologist or just a regular bartender for a high-end cocktail party?
What's the difference in value between a budget photo booth and one of those 360-degree video booths?
Do professional event entertainers usually require a deposit before the date is confirmed?
I need to hire a Santa Claus for a mall event; what certifications or background checks should I ask for?
How far in advance do I need to book a popular local cover band for a Saturday night in June?
What kind of insurance should a professional inflatable rental company carry?
Is it better to hire a solo acoustic musician or a full jazz trio for a corporate dinner?
What questions should I ask a professional fire performer regarding safety and venue permits?
How do I find a reputable murder mystery troupe that can customize the script for my company?
What's the average hourly rate for a professional balloon twister in a major city?
Can I hire a professional trivia host who provides all the sound equipment and buzzers?
What are some indoor entertainment options for a winter carnival if my original outdoor plan gets snowed out?
Are there any hidden fees I should expect when hiring a mobile gaming truck?
How do I vet a professional psychic or tarot reader for a themed Halloween party?
Should I provide a meal for the entertainers I hire for my wedding reception?
What's the typical cancellation policy for professional party entertainers if the event is rained out?
How can I verify the quality of a professional stilt walker before I book them?
Is it worth hiring a professional choreographer for a one-time flash mob at a proposal?
What equipment do I need to provide if I hire a professional comedian for a private house party?
How do I compare quotes from three different professional event planning services?
Are there specific noise ordinances I should worry about when hiring a live band for my backyard?
What's the best way to find a local professional who does giant bubble shows for kids?
Can a professional circus act perform in a room with standard 8-foot ceilings?
I'm looking for a clean comedian for a church fundraiser; how do I ensure their material is appropriate?
What is a reasonable travel fee for an entertainer coming from two hours away?
Should I hire a professional MC or let my most outgoing employee handle the stage at our awards night?
How do I find a professional who offers luxury picnic setups including catering and decor?
What are the pros and cons of hiring a professional hypnotist for a high school post-prom party?
Do I need to pay for a professional DJ's setup and teardown time or is that usually included in the booking fee?
What are the typical power requirements for a professional live band at an outdoor venue?

Model by model

23-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 recreation entertainment buyers.

Behavior rates across 40 recreation entertainment buyer questions, 2026-07 edition. Last column: average across models.
ChatGPTClaudeGeminiConsensus
Recommends hiring a professional60%48%48%53%
Suggests DIY first3%3%3%95%
Names specific providers8%10%15%88%
Gives price or cost info30%25%25%73%
Tells to check reviews23%15%13%65%
Tells to verify credentials25%15%18%63%
Mentions case studies / portfolio20%18%15%65%
Mentions local proximity33%25%20%58%
Gives selection criteria45%50%48%45%
Warns about red flags18%13%18%73%
Asks a clarifying question63%63%0%20%
Recommends multiple quotes8%8%0%88%

By model

How each assistant handled Recreation Entertainment questions.

Reading the 120 answers model by model shows how differently the three assistants treat the same recreation entertainment questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 60% (ChatGPT) down to 47.5% (Claude), a 13-point gap on an identical question set.

Across the 40 recreation entertainment answers it produced, ChatGPT recommended hiring a professional in 60% of them and suggested a DIY approach first 2.5% of the time. It named a specific provider in 7.5% of answers (about 0.2 distinct providers per answer) and included price or cost information 30% of the time. ChatGPT 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 25%, averaging 559 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 20%, and framed the choice around local proximity in 32.5%; a selection-criteria checklist appeared in 45% of its answers and a recommendation to gather multiple quotes in 7.5%.

Across the 40 recreation entertainment answers it produced, Claude recommended hiring a professional in 47.5% of them and suggested a DIY approach first 2.5% of the time. It named a specific provider in 10% of answers (about 0.4 distinct providers per answer) and included price or cost information 25% of the time. Claude asked a clarifying question before answering in 62.5% of cases, warned about red flags or scams in 12.5%, and told the buyer to verify credentials in 15%, averaging 274 words per answer. On the remaining cues it told the buyer to check reviews in 15%, pointed to case studies or a portfolio in 17.5%, and framed the choice around local proximity in 25%; a selection-criteria checklist appeared in 50% of its answers and a recommendation to gather multiple quotes in 7.5%.

Across the 40 recreation entertainment answers it produced, Gemini recommended hiring a professional in 47.5% of them and suggested a DIY approach first 2.5% of the time. It named a specific provider in 15% of answers (about 0.6 distinct providers per answer) and included price or cost information 25% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 17.5%, and told the buyer to verify credentials in 17.5%, averaging 280 words per answer. On the remaining cues it told the buyer to check reviews in 12.5%, pointed to case studies or a portfolio in 15%, and framed the choice around local proximity in 20%; 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 a recreation entertainment buyer to a professional (60%) and Claude the least (47.5%). ChatGPT produced the longest answers, at 559 words on average. Specific providers were named most often by Gemini (15%) — even there, roughly one answer in 7 carried a name.

Where they disagree

The behaviors where the choice of model changes the answer.

The divergence index for this study is 23.2 points — the average distance between the most and least likely model across the coded behaviors. The gaps below are where which assistant a recreation entertainment buyer happens to ask matters most:

  • Asks a clarifying question: from 0% (Gemini) to 62.5% (ChatGPT) — a 63-point spread.
  • Recommends hiring a professional: from 47.5% (Claude) to 60% (ChatGPT) — a 13-point spread.
  • Mentions local proximity: from 20% (Gemini) to 32.5% (ChatGPT) — a 13-point spread.
  • Tells the buyer to check reviews: from 12.5% (Gemini) to 22.5% (ChatGPT) — a 10-point spread.
  • Tells the buyer to verify credentials: from 15% (Claude) to 25% (ChatGPT) — a 10-point spread.

The widest single gap — asks a clarifying question, 63 points — means a recreation entertainment 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 recreation entertainment market.

Where they agree

The points of near-consensus in Recreation Entertainment.

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

  • Suggests a DIY approach first: 2.5% across all three models.
  • Gives price or cost information: 25%–30% across all three (a 5-point spread).
  • Mentions case studies or portfolio: 15%–20% across all three (a 5-point spread).
  • Gives selection criteria: 45%–50% across all three (a 5-point spread).

Measured question by question, the three assistants coded a response the same way most consistently on "suggests a DIY approach first" (identical coding in 95% of questions) and least consistently on "asks a clarifying question" (20%).

Every behavior, measured

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

The behaviors AI models reproduce most often for recreation entertainment are recommends hiring a professional (51.7% on average), gives selection criteria (47.5%) and asks a clarifying question (41.7%); the rarest are suggests a DIY approach first (2.5%), recommends multiple quotes (5%) and names a specific provider (10.8%). Each figure below is the share of a model's 40 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: 51.7% on average (ChatGPT 60%, Claude 47.5%, Gemini 47.5%) — a 13-point spread.
  • Gives selection criteria: 47.5% on average (ChatGPT 45%, Claude 50%, Gemini 47.5%) — a 5-point spread.
  • Asks a clarifying question: 41.7% on average (ChatGPT 62.5%, Claude 62.5%, Gemini 0%) — a 63-point spread.
  • Gives price or cost information: 26.7% on average (ChatGPT 30%, Claude 25%, Gemini 25%) — a 5-point spread.
  • Mentions local proximity: 25.8% on average (ChatGPT 32.5%, Claude 25%, Gemini 20%) — a 13-point spread.
  • Tells the buyer to verify credentials: 19.2% on average (ChatGPT 25%, Claude 15%, Gemini 17.5%) — a 10-point spread.
  • Mentions case studies or portfolio: 17.5% on average (ChatGPT 20%, Claude 17.5%, Gemini 15%) — a 5-point spread.
  • Tells the buyer to check reviews: 16.7% on average (ChatGPT 22.5%, Claude 15%, Gemini 12.5%) — a 10-point spread.
  • Warns about red flags or scams: 15.8% on average (ChatGPT 17.5%, Claude 12.5%, Gemini 17.5%) — a 5-point spread.
  • Names a specific provider: 10.8% on average (ChatGPT 7.5%, Claude 10%, Gemini 15%) — a 8-point spread.
  • Recommends multiple quotes: 5% on average (ChatGPT 7.5%, Claude 7.5%, Gemini 0%) — a 8-point spread.
  • Suggests a DIY approach first: 2.5% on average (ChatGPT 2.5%, Claude 2.5%, Gemini 2.5%).

Trust signals

How well the models protect the recreation entertainment buyer.

Beyond whether to hire, the rubric codes how carefully each assistant protects the recreation entertainment 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 19.2%. Warning about red flags or scams appeared in 15.8%.

On structuring the decision, a selection-criteria checklist showed up in 47.5% of answers on average and a recommendation to gather multiple quotes in 5%. The single least-reproduced protective signal for recreation entertainment is "recommends multiple quotes" at 5% 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 Recreation Entertainment providers?

For service providers the decisive question is whether these systems name anyone at all. Across 120 recreation entertainment answers, a specific provider was named in 10.8% of responses on average — roughly 0.4 distinct providers per answer. In practice the assistants behave far more as an explanatory layer than as a referral engine for recreation entertainment: visibility comes from being the reasoning a model reproduces, not from being the named recommendation.

The question set

What these 40 Recreation Entertainment questions cover.

The 40 questions behind every percentage on this page were drawn from real recreation entertainment (professional 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 recreation entertainment 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 40 answers in which the behavior appeared at least once — not a confidence score. Because each model answered every question exactly once on 2026-07-06, the figures describe this specific recreation entertainment 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.

40 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 2026-07-06, 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 →