The Three-Engine Model™ · Signostic

The buyer asks three engines. You answer one.

Search ranks. Answer engines cite. Maps place. The signals overlap; the weights don't. Most operators are optimized for the engine that's losing share of the question.

Run a Three-Engine audit
Search Engine ranks
Answer Engine cites
Place Engine locates

The Three-Engine Model

Three engines now decide whether a buyer sees you. They read the same signals. They weight them differently. The model is the spine of every audit Signostic ships.

Search Engine

The slow lane

Ten blue links. Still the largest single channel. Still the most predictable.

Weights Backlinks · page depth · intent match · click history. Failure mode Ranking #1 on a query nobody clicks.
Answer Engine

The citation lane

ChatGPT, Perplexity, Claude, Google AI Overviews, Gemini.

Weights Entity clarity · extractability · source authority · schema depth. Failure mode Cited by no one because the page reads like a brochure.
Place Engine

The proximity lane

Maps, Local Pack, “near me”, AI-grounded local recommendations.

Weights NAP consistency · review velocity · GBP completeness · geo content. Failure mode Hidden two scrolls below the fold of a map query.

The shared signal base

In order of leverage:

  • Entity definitionWho and what you are, unambiguously, at machine-read depth.
  • Structured dataSchema as the spine — read by all three engines.
  • Authority graphWho cites you, who you cite, the company you keep.
  • Content depthOne paragraph isn't an answer. Answer engines know.
  • Local consistencyNAP, GBP, citation parity, review pattern.

The asymmetry worth knowing: optimizing the Search Engine alone does roughly 60% of the work for the other two. The remaining 40% is where most sites lose the answer lane — and where the audit looks first.

How Signostic measures it

The audit ships with three sub-scores, one per engine.

01 Sub-score

Citation Presence

Appearances across the four major answer engines, with the prompt set that matched — and the prompt set that didn't.

Answer Engine read

02 Sub-score

Schema · Entity Health

Markup depth, entity disambiguation, knowledge-graph reach, extractable answer blocks.

Machine-read surface

03 Sub-score

Place Signal

GBP, NAP, review pattern, geo-content density, Local Pack eligibility.

Place Engine read

Pulled, pinpointed, proven. The same diagnostic shape; one more index.

What changes — and what doesn't

The audit

Ships with a Three-Engine score, not a search score.

The strategy

Maps remediation by engine, by weight, by month.

The proof loop

Tracks citation deltas alongside rank deltas.

Nothing about the shape of the work changes. The aperture widens.

FAQ

  • Will answer engines replace search?

    No. They're a layer above it. Stack accordingly.

  • What's the fastest move?

    Schema depth and entity disambiguation. Read by all three engines, costs hours not months, almost always under-built.

  • How do I know if my pages are being cited?

    You don't, without measurement. Citation discovery runs on a fixed prompt set per vertical. It's part of the audit.

  • Is this a new service?

    No. Same diagnostic shape. One more engine in the model.

  • Why call it the Answer Engine, not AEO?

    AEO names the optimization. Answer Engine names the thing being optimized for. The second one survives the next renaming cycle.

See the model applied to your domain

Run a Three-Engine audit

Same diagnostic shape. One more engine in the model. Citation Presence, Schema/Entity Health, Place Signal — with a remediation map weighted to where ground is being lost fastest.

Get a diagnosis