AEO — answer engine optimization.
Getting your business named when a customer asks an AI assistant instead of typing into a search box.
The free audit on this site is the front end of this work: it runs the same rules, returns the same two scores, and hands you the same finding list we would work from. Start there, then read what the retainer actually buys.
Traditional SEO is about ranking on a page of ten blue links. Answer engine optimization is about being one of the three companies an assistant actually names — in ChatGPT, Perplexity, Gemini, and Google's AI Overviews. Some of the industry calls the same work GEO, generative engine optimization. Same discipline, two names; we use AEO.
It does not replace SEO — a site that crawlers cannot read is invisible to both. That is why we score the two separately and never average them.
Two scores, never blended.
SEO Health and AI Readiness, each 0–100, each computed from deterministic rules.
Every deducted point traces to a finding row with a URL and a rule ID. There is no composite vanity score to hide behind — two numbers, and the exact reasons behind each one.
The competitor table.
Around 25 fixed prompts per business, run against ChatGPT, Perplexity, Gemini, and Google AI Overviews. For each prompt we record whether you were mentioned, whether you were cited, your position, and — the part that sells itself — which domains got recommended instead of you.
| Prompt | Engine | Mentioned | Cited | Cited instead |
|---|---|---|---|---|
| best plumber in Yuma | ChatGPT | no | no | competitor-a.com, competitor-b.com |
| emergency drain cleaning near me | Perplexity | yes | no | competitor-c.com |
Example — your table is generated from your live results.
How the audit runs.
Collect — render the page the way a browser does, and capture both the raw and rendered HTML. Pull robots.txt, the sitemap, llms.txt, headers, and Lighthouse. If any step fails, the crawl fails — no partial-crawl salvage.
Extract — normalize every page to rows: title, meta, heading tree, canonical, the JSON-LD graph, links, word count, alt text, Core Web Vitals, and the raw-vs-rendered text delta.
Evaluate — deterministic rules, one per file, each returning findings. Every deducted point carries a rule ID and a URL.
Remediate — rank fixes by impact and confidence over effort. The model emits the artifact — rewritten meta, a JSON-LD block, an FAQ section, llms.txt, internal links — as a diff, not advice.
Apply — approved diffs are written through the site adapter, behind an approval gate. Nothing ships without a human yes.
The whole pipeline runs on the same agent stack CoreShift builds and sells as automation work — which is how one operator delivers it, and why the audit is something we can hand you before you pay anything. Browse the bot catalog
What we check on the AI side.
Raw-vs-rendered delta — if your content only exists after hydration, most crawlers never see it. This is the highest-signal check we run, and almost nobody runs it.
Bot policy — explicit robots handling for GPTBot, ClaudeBot, PerplexityBot, Google-Extended, and CCBot. We flag accidental blocks and missing policy.
Entity graph — Organization, LocalBusiness, Service, and FAQ nodes with sameAs and @id cross-references — scored as a graph, not as isolated snippets.
Chunkability — heading hierarchy, answer-first paragraphs, definitional sentences, tables, and stats: what survives retrieval and gets cited.
Attribution — a named author, real credentials, and an accurate dateModified.
llms.txt — present, and correct.
Start here: Benchmark — $497.
Not a tier. The audit. Both scores, every finding traced to a URL and a rule ID, the competitor table, and the remediation list. Credited in full toward onboarding if you continue. If it isn't worth doing, we'll say so and you keep the report.
Then: the AEO retainer.
Every tier is metered on work we perform — pages we maintain, prompts we track, reports we produce. Nothing here is billed on how much work you happen to book.
| Watch | Section | Township | Range | |
|---|---|---|---|---|
| Know where you stand before you commit to fixing it. | One location, one service area. | One location, wide service mix — or a regional operator. | Multi-location. | |
| Pages | Up to 25 tracked | Up to 25 audited and maintained | Up to 100 audited and maintained | 100+ audited and maintained |
| Prompts | 25 | 25 | 100 | Per-location sets |
| Engines | ChatGPT, Perplexity, Gemini, AI Overviews | same | same | same |
| Changes shipped | — | every month | every month | every month, per location |
| Onboarding | none | $1,500 | $2,500 | $5,000 |
| Monthly | $299/mo | $1,250/mo | $2,500/mo | from $4,500/mo |
Ninety-day minimum, then month to month — not a twelve-month term. Onboarding covers the rebuild, the migration, and the foundation sprint: render fixes, entity graph, schema, llms.txt, content restructure. If CoreShift built your site, onboarding is waived — that work is already done and you should not pay for it twice. The $497 Benchmark is credited in full against onboarding if you continue. Watch has no onboarding and no minimum.
The Public Land Survey System — a literal ladder, not a set of invented adjectives. Benchmark, a surveyor's reference marker · Section, one square mile · Township, thirty-six sections · Range, a column of townships.