How ColdChain runs AEO.

We run a fixed prompt set against your brand across four AI engines: ChatGPT, Perplexity, Google AI Overviews, and Gemini. The set mixes buyer-intent prompts ("best stablecoin for a DAO treasury"), comparison prompts ("USDC vs. USDT vs. PYUSD"), and category prompts ("what is proof of reserves"). We record the full text of each answer, the cited sources, and whether your brand is mentioned.

In parallel, we run a classical technical SEO audit: crawlability, indexability, Core Web Vitals, internal-link graph, canonical hygiene. And a schema audit: which pages have it, which schemas are wrong, which are missing.

Output: a prompt-level scoreboard, a technical-gap list, and a top-five prioritized recommendation set.

Before any content ships, we define the canonical entity graph for the brand: core entities (organization, products, people), related entities (peers, partners, regulators, standards, supported chains or tokens), and category entities (the broader categories the brand belongs to).

Every entity gets a canonical name, a canonical URL on the site, and a set of sameAs targets on authoritative third-party sources. This graph becomes the spine for all content and schema that follows. Skip this step and every downstream decision is guesswork.

We ship pages mapped to the entity graph. Each page has a job - a target query, a target entity, a role in the internal-link structure. The page template is consistent: a 50-to-70-word lead that answers the query directly, a structured body that matches the schema, explicit comparison tables where relevant, named-author byline, visible publication and update dates, primary-source citations.

Schema mirrors the visible content exactly. FAQPage markup is only used where the visible Q&A matches the markup verbatim. Article schema always includes author, datePublished, and dateModified. Breadcrumbs on every page.

We re-run the Phase 1 prompt set every month. We track citation share per prompt, brand-mention share, and exact quoted-text changes. Alongside, classical metrics: GSC queries and clicks, referring domains, rankings on tracked keywords. Everything lands in a monthly report with the next iteration's content backlog.