ChatGPT, Claude and Gemini describe you differently — here's why

Why the answers diverge

Training data differs in both cut-off date and source mix. Retrieval differs too: some engines search live for almost every commercial question, others answer from memory unless pushed. And each has its own guardrails about recommending named companies, which is why one will list five vendors and another will describe categories instead.

What a 'no recall' result really tells you

If an engine doesn't know you, the most likely explanation is that you are young, small, or thinly covered by third parties — not that your site is broken. Recall tracks external footprint far more than on-page work. The fastest movers are usually independent coverage, directory listings, comparison pages and community mentions.

What to do with each outcome

Match the fix to the failure mode.

• Not recognised at all: build third-party footprint — reviews, directories, partner pages, podcasts.
• Recognised but described wrongly: publish an unambiguous about page and Organization schema, and correct the stale sources it names.
• Recognised but not recommended: publish comparison and alternatives content with real pricing.
• Recommended by one engine only: look at what that engine cites, then get equivalent coverage in the sources the others prefer.

Read it as a sample, not a scoreboard

Any engine test is a handful of prompts at one moment in time, and answers vary between runs. Track direction across weeks rather than reacting to a single result. Beacon labels every model judgement as an estimate and shows how many engines agreed, precisely so you can tell a trend from noise.

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