Original research · 2026-07 edition

AI SEO Statistics: Locksmith (2026-07 edition)

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

See how AI talks about YOUR businessFull data table

The question bank

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

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

I just moved into a pre-owned home and I'm worried about who has the old keys, should I replace all the hardware or just get them rekeyed?
My front door deadbolt is getting really hard to turn and I'm afraid it's going to snap, what's the average cost for a professional to come fix it?
I'm locked out of my apartment at 2 AM on a Tuesday, how do I find a legitimate locksmith that won't overcharge me for an emergency call?
Can a locksmith help me install a smart lock I bought online, or do they only install the brands they sell?
What are the warning signs of a locksmith scam, especially when they give a super low quote over the phone?
My key snapped off inside the lock cylinder and there's nothing sticking out to grab, is this something I can DIY or do I need a pro?
How much more does it cost to have a locksmith come out on a holiday versus a regular weekday?
Is it cheaper to bring my locks into a shop to be rekeyed or have a mobile locksmith come to my house?
Show all 15 questions
I lost my only set of house keys and I don't have a spare, will a locksmith have to break my door or can they pick it without damage?
What's the difference between a high-security lock and a standard one from a big box store, and is the extra $200 worth it?
Do locksmiths usually offer any kind of warranty or guarantee on the parts they install and their labor?
My sliding glass door lock is jammed and won't budge, can a regular residential locksmith fix those or is that a different specialist?
I'm looking for a locksmith who is licensed and bonded, what specific documents should I ask to see when they arrive at my house?
Can a locksmith make a master key system for my house so one key opens everything but the guest suite has its own?
Why is there such a huge price range for a simple lockout service, I'm seeing quotes from $50 to $250?

Model by model

26-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 locksmith buyers.

Behavior rates across 15 locksmith buyer questions, 2026-07 edition. Last column: average across models.
ChatGPTClaudeGeminiConsensus
Recommends hiring a professional100%80%67%60%
Suggests DIY first20%33%27%87%
Names specific providers13%0%13%87%
Gives price or cost info53%53%47%67%
Tells to check reviews20%20%0%73%
Tells to verify credentials40%33%7%53%
Mentions case studies / portfolio0%0%0%100%
Mentions local proximity60%53%27%40%
Gives selection criteria67%60%40%40%
Warns about red flags27%33%13%67%
Asks a clarifying question80%40%0%13%
Recommends multiple quotes27%27%0%53%

By model

How each assistant handled Locksmith questions.

Reading the 45 answers model by model shows how differently the three assistants treat the same locksmith questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 100% (ChatGPT) down to 66.7% (Gemini), a 33-point gap on an identical question set.

Across the 15 locksmith answers it produced, ChatGPT recommended hiring a professional in 100% of them and suggested a DIY approach first 20% of the time. It named a specific provider in 13.3% of answers (about 0.3 distinct providers per answer) and included price or cost information 53.3% 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 40%, averaging 447 words per answer. On the remaining cues it told the buyer to check reviews in 20%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 60%; a selection-criteria checklist appeared in 66.7% of its answers and a recommendation to gather multiple quotes in 26.7%.

Across the 15 locksmith answers it produced, Claude recommended hiring a professional in 80% of them and suggested a DIY approach first 33.3% of the time. It named a specific provider in 0% of answers (about 0 distinct providers per answer) and included price or cost information 53.3% of the time. Claude asked a clarifying question before answering in 40% of cases, warned about red flags or scams in 33.3%, and told the buyer to verify credentials in 33.3%, averaging 288 words per answer. On the remaining cues it told the buyer to check reviews in 20%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 53.3%; a selection-criteria checklist appeared in 60% of its answers and a recommendation to gather multiple quotes in 26.7%.

Across the 15 locksmith answers it produced, Gemini recommended hiring a professional in 66.7% of them and suggested a DIY approach first 26.7% of the time. It named a specific provider in 13.3% of answers (about 0.5 distinct providers per answer) and included price or cost information 46.7% 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 6.7%, averaging 283 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 26.7%; 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 locksmith buyer to a professional (100%) and Gemini the least (66.7%). ChatGPT produced the longest answers, at 447 words on average. Specific providers were named most often by ChatGPT (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 25.6 points — the average distance between the most and least likely model across the coded behaviors. The gaps below are where which assistant a locksmith buyer happens to ask matters most:

  • Asks a clarifying question: from 0% (Gemini) to 80% (ChatGPT) — a 80-point spread.
  • Recommends hiring a professional: from 66.7% (Gemini) to 100% (ChatGPT) — a 33-point spread.
  • Tells the buyer to verify credentials: from 6.7% (Gemini) to 40% (ChatGPT) — a 33-point spread.
  • Mentions local proximity: from 26.7% (Gemini) to 60% (ChatGPT) — a 33-point spread.
  • Gives selection criteria: from 40% (Gemini) to 66.7% (ChatGPT) — a 27-point spread.

The widest single gap — asks a clarifying question, 80 points — means a locksmith 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 locksmith market.

Where they agree

The points of near-consensus in Locksmith.

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

  • Mentions case studies or portfolio: 0% across all three models.
  • Gives price or cost information: 46.7%–53.3% across all three (a 7-point spread).
  • Suggests a DIY approach first: 20%–33.3% across all three (a 13-point spread).
  • Names a specific provider: 0%–13.3% across all three (a 13-point spread).

Measured question by question, the three assistants coded a response the same way most consistently on "mentions case studies or portfolio" (identical coding in 100% of questions) and least consistently on "asks a clarifying question" (13.3%).

Every behavior, measured

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

The behaviors AI models reproduce most often for locksmith are recommends hiring a professional (82.2% on average), gives selection criteria (55.6%) and gives price or cost information (51.1%); the rarest are mentions case studies or portfolio (0%), names a specific provider (8.9%) and tells the buyer to check reviews (13.3%). 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: 82.2% on average (ChatGPT 100%, Claude 80%, Gemini 66.7%) — a 33-point spread.
  • Gives selection criteria: 55.6% on average (ChatGPT 66.7%, Claude 60%, Gemini 40%) — a 27-point spread.
  • Gives price or cost information: 51.1% on average (ChatGPT 53.3%, Claude 53.3%, Gemini 46.7%) — a 7-point spread.
  • Mentions local proximity: 46.7% on average (ChatGPT 60%, Claude 53.3%, Gemini 26.7%) — a 33-point spread.
  • Asks a clarifying question: 40% on average (ChatGPT 80%, Claude 40%, Gemini 0%) — a 80-point spread.
  • Suggests a DIY approach first: 26.7% on average (ChatGPT 20%, Claude 33.3%, Gemini 26.7%) — a 13-point spread.
  • Tells the buyer to verify credentials: 26.7% on average (ChatGPT 40%, Claude 33.3%, Gemini 6.7%) — a 33-point spread.
  • Warns about red flags or scams: 24.4% on average (ChatGPT 26.7%, Claude 33.3%, Gemini 13.3%) — a 20-point spread.
  • Recommends multiple quotes: 17.8% on average (ChatGPT 26.7%, Claude 26.7%, Gemini 0%) — a 27-point spread.
  • Tells the buyer to check reviews: 13.3% on average (ChatGPT 20%, Claude 20%, Gemini 0%) — a 20-point spread.
  • Names a specific provider: 8.9% on average (ChatGPT 13.3%, Claude 0%, Gemini 13.3%) — a 13-point spread.
  • Mentions case studies or portfolio: 0% on average (ChatGPT 0%, Claude 0%, Gemini 0%).

Trust signals

How well the models protect the locksmith buyer.

Beyond whether to hire, the rubric codes how carefully each assistant protects the locksmith 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 26.7%. Warning about red flags or scams appeared in 24.4%.

On structuring the decision, a selection-criteria checklist showed up in 55.6% of answers on average and a recommendation to gather multiple quotes in 17.8%. The single least-reproduced protective signal for locksmith is "tells the buyer to check reviews" at 13.3% 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 Locksmith providers?

For service providers the decisive question is whether these systems name anyone at all. Across 45 locksmith answers, a specific provider was named in 8.9% of responses on average — roughly 0.3 distinct providers per answer. In practice the assistants behave far more as an explanatory layer than as a referral engine for locksmith: visibility comes from being the reasoning a model reproduces, not from being the named recommendation.

The question set

What these 15 Locksmith questions cover.

The 15 questions behind every percentage on this page were drawn from real locksmith (home 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 locksmith 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 locksmith 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 →