How do you compare AI systems fairly?
Use comparable buyer questions and retain the actual product surface, observed model, search configuration, market, language and time. Then read mentions, citations and recommendations separately. Ready Scan keeps answer evidence by question and system; crawler traffic, search results and failed requests do not substitute for a completed answer.
Engine profile notes
The six reference guides explain different answer and retrieval surfaces. They do not imply that every scan runs all six systems. The current free-scan handoff names ChatGPT, Claude, Gemini and Perplexity; the actual scan plan determines which systems and checks run.
ChatGPT-facing
Keep the observed ChatGPT or API surface explicit. Search crawling, possible training collection and user-requested page visits are separate activities; none is a substitute for reading the answer.
Claude-facing
Record whether web search was enabled or actually used. Claude's training crawler, search-indexing agent and user-requested retrieval have different roles.
Google/Gemini-facing
Separate Gemini Apps answers, API answers grounded with Google Search and Google Search AI features. Their source links and performance reports do not measure the same event.
Perplexity-facing
Distinguish an answer with citations from a ranked Search API result. Keep the consumer interface and API configuration visible when comparing observations.
Grok-facing
Distinguish web-page evidence from public X evidence. A URL encountered during search is not automatically an inline citation in the final answer.
DeepSeek-facing
Name the consumer, API or search integration used. A client-operated tool can supply retrieval data; that controlled path does not establish what another surface would select.
Compare an answer surface, not a logo
An AI-system name alone is not a reproducible measurement. The same family can expose a consumer chat product, a developer API and several retrieval configurations. A change between those surfaces can change the evidence even when the brand logo stays the same.
Ready Scan retains the observation context with the answer. Read the actual model, provider/surface and search state available in that record. Do not relabel a controlled API result as a browser test of a consumer product.
Context that makes two observations comparable
Scroll to read all columns.
| Keep visible | Why it matters |
|---|---|
| Exact question and buying conditions | Changing the need can change which products fit. |
| Product surface, observed model and retrieval configuration | A browser product, API and search-enabled integration can behave differently. |
| Market and language | Results may address different customer contexts. |
| Observation date and completed/scored coverage | A later or incomplete sample is not automatically comparable to the earlier one. |
Read disagreement before averaging it
Illustrative example: two systems answer the same buying question. One says a product is an option if the buyer needs a named integration; the other links its documentation while explaining the category, without recommending it. Both may cite the product, but only the first contains that conditional recommendation.
The difference is useful information. Check the condition and the cited passage before treating the two answers as equivalent successes. Do not erase disagreement by looking only at one overall score; the system-by-question evidence shows where the result differs.
A failed cell is not a negative opinion
A request that failed, never returned an answer or produced an inconclusive assessment does not show that the AI rejected the brand. Search-result-only material also does not become a scored narrative recommendation.
Normal final report assembly requires the selected answer acquisition and assessments to complete. Where an incomplete attempt or retained coverage is shown, read its actual state. Do not manufacture a zero or silently substitute another system to make the coverage look complete.
Use the system-specific guide for the next question
If the issue is crawler access, use the matching provider guide to identify the documented agent and its purpose. If the issue is an answer, inspect the question, recommendation wording and sources. If the issue is measurement, use the methodology for the scoring rules.
These are different investigations. Good crawler delivery cannot prove a recommendation, and an unfavourable answer does not prove that the page was inaccessible. Start with the evidence that addresses the actual question.
Check the AI systems your buyers use.
Free scans include ChatGPT, Claude, Gemini and Perplexity, with each answer retained separately.