Roughly 80% of AI visibility work is shared across every platform — crawler access, entity clarity, extractable structure, corroboration. These pages cover the 20% that genuinely differs.
Platform coverage is agreed for each engagement. The dedicated pages and sections below explain what to check and how to interpret the results.
A lot of AI SEO marketing implies each platform needs a completely separate strategy, usually because separate strategies are easier to sell as separate line items. That isn't what we find in practice.
The things that matter most — whether crawlers can read your site, whether models can resolve your brand, whether your content contains extractable answers, whether independent sources corroborate your claims — help everywhere simultaneously. A brand that fixes those improves across all six platforms at once.
What genuinely differs is worth knowing: Perplexity searches on nearly every query and moves fastest, Copilot depends entirely on Bing's index, Gemini leans on Google's knowledge graph, and Claude hedges when corroboration is thin. Those differences shape sequencing and emphasis, not separate programmes.
The Claude work belongs to the shared AI SEO programme. Review access using Anthropic’s current crawler and user-fetch documentation, then test the buyer questions that matter to your company.
Gemini and Google Search’s AI features are different surfaces. Record the product, question, locale and search setting in each test instead of assuming that one result represents both.
Treat Google’s AI search features as part of a sound Search programme: useful content, accessible pages, clear internal links and accurate information. There is no special schema or AI text file required to appear.
Review Search Console performance alongside specific, dated observations of the relevant search feature. Do not label all organic sessions as AI traffic or assume a fall in clicks has one cause.
Google documents the applicable controls and recommendations in its AI search guidance.
DeepSeek is not a separate service package. Where it is relevant to your buyers, include it in the agreed prompt benchmark and review documentation, capability claims and public company information as part of the existing programme.
Distinguish the hosted product from other deployments of an open-weight model. A test of one deployment cannot establish what every application using that model says. Report only the surfaces and questions actually observed.
Developer-focused and international businesses can assess whether these tests add useful information. We do not recommend a separate content programme solely to cover another model.
No. Around 80% of the work — crawler access, rendering, entity clarity, extractable structure, corroboration — improves visibility on every platform simultaneously.
Platform differences affect sequencing and emphasis rather than requiring separate programmes. We'd be sceptical of anyone selling six separate retainers.
It depends on your buyers. ChatGPT has the largest reach; Perplexity skews professional and moves fastest; Copilot has enterprise distribution; Claude concentrates technical and professional users; Gemini and AI Overviews carry Google's scale.
For diagnostic purposes we often start with Perplexity, because it retrieves live and shows its sources, making it the clearest early signal that the underlying work is functioning.
It happens, and it's why we monitor monthly rather than delivering one-time projects. Model updates reshuffle source selection, sometimes substantially.
Durable assets — entity clarity, schema accuracy, genuine corroboration — survive updates better than tactical wins, which is where we weight the work.
We can add others where there's a genuine reason — regional assistants or emerging platforms relevant to your market. The six listed cover the overwhelming majority of commercial AI search in the US.
We'd rather cover six properly than fifteen superficially.
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