Original research · 2026-07 edition

AI SEO Statistics: Liposuction (2026-07 edition)

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

See how AI talks about YOUR businessFull data table

The question bank

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

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

I've been hitting the gym for two years but can't lose the lower belly pooch, is lipo my only option?
What is the difference between VASER liposuction and traditional lipo in terms of recovery time?
How much does stomach liposuction typically cost in a major US city?
Can I get liposuction if my BMI is over 30 or do I need to lose weight first?
What are the red flags I should look for when visiting a plastic surgery clinic for a consultation?
Is it better to do fat freezing or just go straight to surgical liposuction for inner thighs?
How long do I actually have to take off work after a full 360 lipo procedure?
Does insurance ever cover liposuction if it's for lipedema or is it always out of pocket?
Show all 40 questions
I'm seeing prices for lipo abroad that are half the cost of the US, is it safe to travel for this?
What questions should I ask a surgeon to make sure they are actually experienced in body contouring?
Will my skin sag after getting liposuction on my arms or does it tighten back up?
How do I know if a surgeon is board-certified in plastic surgery specifically?
What happens if I gain weight again after getting liposuction?
Is it normal for a clinic to charge a consultation fee that doesn't go toward the surgery?
Are there non-surgical alternatives for double chin fat that actually work as well as lipo?
Can I get liposuction and a fat transfer to my hips at the same time?
How many liters of fat can safely be removed in one single session?
What is the average cost of chin liposuction including anesthesia and facility fees?
I have a wedding in three months, is that enough time to fully heal from lipo?
Do I need to have a driver take me home after the procedure or can I call an Uber?
What kind of compression garments are best for post-op swelling and how long do I wear them?
Is it better to get lipo before or after having children if I'm planning a family soon?
What are the most common complications people experience with wake-up lipo versus general anesthesia?
How do I find a surgeon who specializes in high-definition lipo for abdominal etching?
Can liposuction get rid of cellulite or does it make it look worse?
What should I expect during the first 48 hours of recovery from abdominal liposuction?
Is there a way to get a price estimate without going in for a physical exam?
Why do some surgeons use drains after lipo and others don't?
What are the risks of getting liposuction at a medspa instead of a surgical center?
Does the fat come back in other areas of the body after it's sucked out of the stomach?
How much does it cost to fix a lumpy liposuction result from a previous doctor?
Can I get liposuction on my ankles and calves or is that too risky?
What is the difference between a plastic surgeon and a cosmetic surgeon when booking lipo?
Are there financing options like monthly payment plans for body contouring surgeries?
Is it possible to do liposuction under local anesthesia while I'm still awake?
How do I check if a surgery center has had any safety violations or lawsuits?
Will I have visible scars from the cannula insertion points?
I'm 55, am I too old for liposuction or is skin elasticity the bigger issue?
What is the total all-in price I should expect for flank and back lipo?
How many follow-up appointments are usually required after the initial surgery?

Model by model

22-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 liposuction buyers.

Behavior rates across 40 liposuction buyer questions, 2026-07 edition. Last column: average across models.
ChatGPTClaudeGeminiConsensus
Recommends hiring a professional63%78%23%35%
Suggests DIY first8%5%8%95%
Names specific providers3%8%10%93%
Gives price or cost info10%10%13%90%
Tells to check reviews15%10%3%85%
Tells to verify credentials53%55%18%45%
Mentions case studies / portfolio28%13%3%75%
Mentions local proximity20%10%8%75%
Gives selection criteria48%40%13%45%
Warns about red flags15%23%10%75%
Asks a clarifying question65%70%0%13%
Recommends multiple quotes18%18%0%75%

By model

How each assistant handled Liposuction questions.

Reading the 120 answers model by model shows how differently the three assistants treat the same liposuction questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 77.5% (Claude) down to 22.5% (Gemini), a 55-point gap on an identical question set.

Across the 40 liposuction answers it produced, ChatGPT recommended hiring a professional in 62.5% of them and suggested a DIY approach first 7.5% of the time. It named a specific provider in 2.5% of answers (about 0.1 distinct providers per answer) and included price or cost information 10% of the time. ChatGPT asked a clarifying question before answering in 65% of cases, warned about red flags or scams in 15%, and told the buyer to verify credentials in 52.5%, averaging 451 words per answer. On the remaining cues it told the buyer to check reviews in 15%, pointed to case studies or a portfolio in 27.5%, 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 17.5%.

Across the 40 liposuction answers it produced, Claude recommended hiring a professional in 77.5% of them and suggested a DIY approach first 5% of the time. It named a specific provider in 7.5% of answers (about 0.3 distinct providers per answer) and included price or cost information 10% of the time. Claude asked a clarifying question before answering in 70% of cases, warned about red flags or scams in 22.5%, and told the buyer to verify credentials in 55%, averaging 272 words per answer. On the remaining cues it told the buyer to check reviews in 10%, pointed to case studies or a portfolio in 12.5%, and framed the choice around local proximity in 10%; a selection-criteria checklist appeared in 40% of its answers and a recommendation to gather multiple quotes in 17.5%.

Across the 40 liposuction answers it produced, Gemini recommended hiring a professional in 22.5% of them and suggested a DIY approach first 7.5% of the time. It named a specific provider in 10% of answers (about 0.3 distinct providers per answer) and included price or cost information 12.5% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 10%, and told the buyer to verify credentials in 17.5%, averaging 270 words per answer. On the remaining cues it told the buyer to check reviews in 2.5%, pointed to case studies or a portfolio in 2.5%, and framed the choice around local proximity in 7.5%; a selection-criteria checklist appeared in 12.5% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, Claude is the assistant most likely to route a liposuction buyer to a professional (77.5%) and Gemini the least (22.5%). ChatGPT produced the longest answers, at 451 words on average. Specific providers were named most often by Gemini (10%) — even there, roughly one answer in 10 carried a name.

Where they disagree

The behaviors where the choice of model changes the answer.

The divergence index for this study is 22.2 points — the average distance between the most and least likely model across the coded behaviors. The gaps below are where which assistant a liposuction buyer happens to ask matters most:

  • Asks a clarifying question: from 0% (Gemini) to 70% (Claude) — a 70-point spread.
  • Recommends hiring a professional: from 22.5% (Gemini) to 77.5% (Claude) — a 55-point spread.
  • Tells the buyer to verify credentials: from 17.5% (Gemini) to 55% (Claude) — a 38-point spread.
  • Gives selection criteria: from 12.5% (Gemini) to 47.5% (ChatGPT) — a 35-point spread.
  • Mentions case studies or portfolio: from 2.5% (Gemini) to 27.5% (ChatGPT) — a 25-point spread.

The widest single gap — asks a clarifying question, 70 points — means a liposuction 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 liposuction market.

Where they agree

The points of near-consensus in Liposuction.

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

  • Suggests a DIY approach first: 5%–7.5% across all three (a 3-point spread).
  • Gives price or cost information: 10%–12.5% across all three (a 3-point spread).
  • Names a specific provider: 2.5%–10% across all three (a 8-point spread).
  • Tells the buyer to check reviews: 2.5%–15% across all three (a 13-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" (12.5%).

Every behavior, measured

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

The behaviors AI models reproduce most often for liposuction are recommends hiring a professional (54.2% on average), asks a clarifying question (45%) and tells the buyer to verify credentials (41.7%); the rarest are names a specific provider (6.7%), suggests a DIY approach first (6.7%) and tells the buyer to check reviews (9.2%). 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: 54.2% on average (ChatGPT 62.5%, Claude 77.5%, Gemini 22.5%) — a 55-point spread.
  • Asks a clarifying question: 45% on average (ChatGPT 65%, Claude 70%, Gemini 0%) — a 70-point spread.
  • Tells the buyer to verify credentials: 41.7% on average (ChatGPT 52.5%, Claude 55%, Gemini 17.5%) — a 38-point spread.
  • Gives selection criteria: 33.3% on average (ChatGPT 47.5%, Claude 40%, Gemini 12.5%) — a 35-point spread.
  • Warns about red flags or scams: 15.8% on average (ChatGPT 15%, Claude 22.5%, Gemini 10%) — a 13-point spread.
  • Mentions case studies or portfolio: 14.2% on average (ChatGPT 27.5%, Claude 12.5%, Gemini 2.5%) — a 25-point spread.
  • Mentions local proximity: 12.5% on average (ChatGPT 20%, Claude 10%, Gemini 7.5%) — a 13-point spread.
  • Recommends multiple quotes: 11.7% on average (ChatGPT 17.5%, Claude 17.5%, Gemini 0%) — a 18-point spread.
  • Gives price or cost information: 10.8% on average (ChatGPT 10%, Claude 10%, Gemini 12.5%) — a 3-point spread.
  • Tells the buyer to check reviews: 9.2% on average (ChatGPT 15%, Claude 10%, Gemini 2.5%) — a 13-point spread.
  • Suggests a DIY approach first: 6.7% on average (ChatGPT 7.5%, Claude 5%, Gemini 7.5%) — a 3-point spread.
  • Names a specific provider: 6.7% on average (ChatGPT 2.5%, Claude 7.5%, Gemini 10%) — a 8-point spread.

Trust signals

How well the models protect the liposuction buyer.

Beyond whether to hire, the rubric codes how carefully each assistant protects the liposuction buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 9.2% of answers on average. Verifying credentials or certifications appeared in 41.7%. Warning about red flags or scams appeared in 15.8%.

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 11.7%. The single least-reproduced protective signal for liposuction is "tells the buyer to check reviews" at 9.2% 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 Liposuction providers?

For service providers the decisive question is whether these systems name anyone at all. Across 120 liposuction answers, a specific provider was named in 6.7% of responses on average — roughly 0.2 distinct providers per answer. In practice the assistants behave far more as an explanatory layer than as a referral engine for liposuction: visibility comes from being the reasoning a model reproduces, not from being the named recommendation.

The question set

What these 40 Liposuction questions cover.

The 40 questions behind every percentage on this page were drawn from real liposuction (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 liposuction 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 liposuction 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 →