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ChatGPT, Perplexity, Gemini and Claude do not expose one universal ranking checklist. Build the durable signals they can use: consistent entities, helpful pages, primary sources, current information and strong technical SEO.

Services · 8 min read · Updated 2026-06-06

Optimise the information layer

Use a consistent organisation name, product description, URL and author identity. Explain what the company does, for whom and in which situations. Link related entities so an answer engine can resolve the context.

Platform-aware priorities

The list below breaks this down into the parts that matter most. Read through each one and note anything that applies to your own setup.

  • ChatGPT: clear brand and product information that remains useful when pages are browsed.
  • Perplexity: current claims, direct answers and a healthy set of credible sources.
  • Gemini and Google AI Overviews: strong classic search foundations, entity clarity and structured content.
  • Claude: well-organised, well-sourced pages with careful definitions and useful detail.
  1. Create or improve the relevant service or use-case page.
  2. Add a concise answer and supporting evidence.
  3. Use appropriate schema and an internal link to the next page.
  4. Refresh facts and dates when the underlying product changes.
  5. Track observed mentions directionally rather than treating them as guaranteed rankings.
Do not create separate near-identical pages for each AI engine. One strong answer can serve multiple discovery surfaces.

What influences citations

Before making changes, work through the points below. Each one covers a different part of the picture, so treat them as a set rather than picking favourites.

  • A crawlable page that states the answer plainly, without scripts hiding the content.
  • Consistent facts: the same product name, pricing and claims everywhere they appear.
  • Third-party corroboration: reviews, documentation, directories and community discussion.
  • Freshness signals: visible dates and content that is updated when facts change.
  • Specificity: numbers, steps and named entities beat generic positioning language.

A realistic testing routine

Here is the process broken into clear steps. Take them one at a time and check each off before continuing.

  1. Pick ten questions your buyers actually ask these systems.
  2. Ask each platform monthly from a clean session and record the answers.
  3. Note which sources are cited when you are not mentioned.
  4. Improve the page or source that should have been cited.
  5. Re-test after changes have had time to be recrawled.
Do not create separate near-identical pages for each AI engine. One strong answer can serve multiple discovery surfaces.

Questions

Mostly no. All of them reward the same fundamentals: crawlable pages, clear answers, consistent entities and credible sources. Platform-specific tweaks are marginal compared with getting the information layer right.

Usually because the clearest available source about you is outdated or written by someone else. Publish accurate, specific pages about your own product and correct the third-party sources you control.

Blocking training crawlers in robots.txt removes your content from systems that respect it, which reduces the chance of being cited. Only block if you have a deliberate reason to stay out of AI answers.

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