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Depth 02.2 · Search and AI visibility · Level 3

Answer engine optimisation

Answer engine optimisation is the practice of making a company's facts easy for AI assistants and AI search features to find, trust and quote correctly. Tools such as ChatGPT, Perplexity and Google's AI Overviews build their answers from web sources. This work makes sure the sources they draw on describe you accurately, in a structure a machine can read without guessing.

Specification

Input
The facts you want stated correctly about the company and its services, and the pages and public profiles that currently carry them.
Method
We list the entities that matter to you, such as the company, each service and each product. Then we check how each one is described on your site and in public sources, align the descriptions, and mark them up with schema.org structured data.
Deliverable
Entity and schema map: every entity, its canonical description, the page that owns it and the structured data that marks it up.
Measured by
Whether a fixed set of prompts in the main AI assistants names your company and describes it correctly, checked on a schedule and recorded with dates. Markup is validated with Google's Rich Results Test and the Schema.org validator.

Most often bought inB2B software, Professional services

The artefact, before and after

Entity and schema map: every entity, its canonical description, the page that owns it and the structured data that marks it up.

Before: a blank answer engine optimisation record with a row for each of entity inventory, schema.org markup in json-ld, definitional page openings that can be quoted, ai crawler access and llms.txt, consistent descriptions across public profiles, and no entries. After: every row carries a finding and a checked status, which is the state the work hands over.

Inside it

  • 01Entity inventory
  • 02schema.org markup in JSON-LD
  • 03Definitional page openings that can be quoted
  • 04AI crawler access and llms.txt
  • 05Consistent descriptions across public profiles
Deliverable · Level 4→ Entity and schema mapAn entity and schema map is a record of the things your company wants search engines and AI assistants to recognise, such as the organisation, its services and the terms it defines, with the one page that defines each and the structured data that page carries.

Typical first engagement

The usual order of a first piece of work. Timing and price are set at scoping, once we have seen the stack.

  1. 01Question setYou get: The questions buyers ask, agreed with you, tested against current assistant answers.
  2. 02Entity mapYou get: Your company, services and terms as entities, with the pages that define them.
  3. 03Markup and copyYou get: Structured data and definitional paragraphs added to the pages that need them.
  4. 04RecheckYou get: The same question set run again, with answers and citations recorded side by side.

Search and AI visibility

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