You already know SEO. This is what changes when the goal is being cited inside an answer instead of ranked in a list — on a catalog with a hundred thousand SKUs, not a blog. No tool does this for you yet. It is hand work.
What GEO actually is (and isn’t)
GEO is getting AI engines to retrieve, summarize, and cite you. It is not getting a blue link to rank. The plumbing overlaps with SEO — Google itself shrugs and calls GEO/AEO “still SEO” — but the target is a citation and you measure it differently. It sits on top of solid SEO. It does not replace it.
Make the catalog extractable
Engines cite what they can read. The industrial failure mode is specs trapped in PDFs or a JavaScript catalog the crawler never renders. Get specs into HTML tables. Put Product schema with MPN and GTIN on the template, not the SKU. Publish cross-reference data as flat tables. You fix it once at the template and it lands across every SKU.
Build the entity graph
An engine decides who you are from your pages plus the sources it already trusts. Say the same thing everywhere — what you sell, which brands, where — across your site, the manufacturer’s pages, the directories, Wikidata. Thin or contradictory signals are why a real distributor loses the answer to a marketplace.
Open the doors to AI crawlers
Two kinds of bot: training (GPTBot, ClaudeBot) and retrieval (OAI-SearchBot, PerplexityBot). Block the retrieval bots — usually by accident, in your WAF — and you are not in the answer, full stop, however good the page is. Run the crawler-access audit first, not last.
Measure what you can’t rank for
Rankings don’t help you here — only about 12% of AI-cited URLs sit in Google’s top 10 for the same prompt. So fix a set of real buyer prompts, run them on a schedule, and count mention rate, citation share, and share of voice against named competitors. Brand Radar, Profound, and Otterly do the sampling.