ChatGPT · LLM monitoring
Hundreds of millions ask AI weekly—if you’re invisible in ChatGPT, you’re invisible
Buyers already ask a chatbot for the “best vendor” instead of typing a classic query. ChatGPT is the largest public entry point; answers usually don’t show explicit footnotes, so your brand is either named or absent. A ChatGPT slice sets the baseline before you compare other models.
What a finished report looks like
The demo excerpt below highlights the ChatGPT row: share of prompts where the model mentioned the brand, plus quotes from its answers. Your report uses the same layout for your brand and niche.
Carapelli
Mentions by model (demo run)
Highlight: ChatGPT — the focus of this landing page. Numbers are illustrative.
Competitors in this slice
Your real report uses the same layout: scores, per-model breakdown, quotes, competitors, and citations — with your brand and the models you select.
Benchmarking
Timestamped snapshot
Completion time is stored with every run—clean before/after comparisons when you change positioning or content.
Method
Organic-style prompts
Your brand name is not pasted into the question text; we score whether models still mention you in realistic category queries.
Context
Around ChatGPT
Add sibling models in the same check to see if the pattern is specific to ChatGPT or repeats across the stack.
About this model
Industry reporting often cites 400M+ weekly ChatGPT users—larger than any other consumer chat assistant in our monitoring set.
ChatGPT rarely surfaces a transparent source list in casual answers: visibility is binary—you’re mentioned in the narrative or not. Shopping-oriented flows inside ChatGPT are a separate e-commerce surface worth tracking.
How we measure visibility
Getllmspy uses fixed scenario packs by niche and check type. The brand name is not inserted into prompt text; site/category context is used to score answers.
- Compare ChatGPT with Claude, Gemini, Perplexity, YandexGPT, and more in one run
- Mentions, list placement, sentiment, competitors, and answer excerpts
- Timestamped reports for marketing and SEO reporting loops
Inside the report
Snapshot header
Completion time and which models ran—your anchor for before/after benchmarking.
LLM-Score & share of voice
Aggregated 0–100 signal plus the share of models that mentioned your brand at least once.
Competitors & roundups
Who appears next to you in ChatGPT answers: names, frequency, comparison or recommendation context.
Quotes & wording
Answer excerpts for manual review—how the model talks about the category and your brand.
Same prompts on other models
Parallel runs (Claude, Gemini, Perplexity, …) to see if the pattern is ChatGPT-specific.
From check to PDF-ready snapshot
Brand & niche
You set brand context, site, category, language, and check type—this selects the prompt pack.
Model mix
Pick the LLM families to include; the same scenarios run in parallel across all of them.
Server run
The job executes on our side; you can close the tab and open the report from History when ready.
Report
LLM-Score, share of voice, competitors, quotes, citations—exportable and rerunnable on demand.
If ChatGPT omits your brand on organic prompts, strengthen on-site facts, reviews, and third-party coverage the models can cite.