Track your brand in ChatGPT
ChatGPT is the most used AI assistant in the world, and for a growing share of buyers it is the first place they ask for a recommendation. If ChatGPT names your competitors and not you, that is revenue quietly walking past you. Diploria polls ChatGPT with the questions your customers actually ask, records the full answer every time, and turns those answers into a visibility score you can track and improve.
How ChatGPT decides who to mention
ChatGPT answers from two distinct places. When it answers from model memory, it draws on what it learned about your brand during training: how often you appeared across the web, what was said about you on review sites, forums, news coverage, and comparison articles, and how consistently your positioning was described. A brand with a thin or contradictory footprint at training time tends to be vague or absent in memory answers.
When ChatGPT searches the web, the picture changes. It retrieves live pages and leans on results and rankings from its search partners. Live answers can include citations when the engine provides them. Here, retrievable, well structured pages and a presence on the sites it likes to cite (publishers, review platforms, community threads) matter far more than what the model memorised.
The two modes can disagree about you. It is common for a brand to be recommended in memory answers but missing when ChatGPT searches, or the reverse. That is exactly why tracking one mode is not enough.
Want the deep dive? How ChatGPT chooses its sources.
What Diploria tracks in ChatGPT
- Whether ChatGPT mentions your brand for each tracked prompt, and in what position
- Memory mode and Live (web search) mode, tracked separately so you can see where the gap is
- The full text of every response, stored so you can read exactly how you were described
- Sentiment: whether ChatGPT frames your brand positively, neutrally, or negatively
- Which competitors are named alongside or instead of you, and your share of voice
- The sources ChatGPT cites in Live mode, including whether your own domain made the list
Memory-mode engines answer from model knowledge without web search. Live-mode engines search the web. Live answers can include citations when the engine provides them. Choose Memory for baseline model knowledge and Live for current, web-grounded results.
Diploria tracks ChatGPT in both Memory mode (what the model says from training) and Live mode (what it says when it searches the web). The gap between the two tells you whether your problem is your long-term footprint or your current, retrievable content.
What makes ChatGPT different
ChatGPT's defining trait is the weight of its trained memory combined with its massive user base. No other assistant answers as many recommendation questions per day, and many of those answers are served from memory with no live retrieval at all. That makes your long-term web footprint (reviews, comparisons, community mentions accumulated over years) a bigger factor here than on retrieval-first engines. When ChatGPT does search, it cites sources, so the publications and platforms it trusts become a second, faster lever. You need to win both games, and they move at different speeds.
How to improve your visibility in ChatGPT
- Build presence on the third-party sources ChatGPT cites in your category: review platforms, comparison articles, and community threads, not just your own site
- Keep your positioning consistent everywhere it appears, so both training data and live retrieval tell the same story about you
- Make your key pages retrievable and well structured so Live mode can find and cite them
- Track branded and non-branded prompts separately; memory gaps show up first on non-branded category questions
- Re-measure after changes: Live mode can shift in weeks, memory moves slower
Diploria's Optimization Hub turns this into a workflow: the AI Readiness Scan grades any page for AI readiness, the AI Readiness Checklist prioritises the fixes, and AI crawler access checks make sure engines can reach your content at all.
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