01
Entity identity
Use a stable organisation name, canonical URLs, contact details and clear descriptions so references are less likely to be mistaken for different entities.
AI Search / GEO / AEO / focused landing page
AI Search / GEO / AEO / authority guideAI entity footprint across search and AI answers.
An AI entity footprint is the collection of consistent, corroborated signals that helps search and AI systems understand a brand, its expertise and its relationships.
Build a clearer, more consistent body of evidence about who your organisation is, what it does and why its published expertise is credible.
AISB growth brief
Build a clearer, more consistent body of evidence about who your organisation is, what it does and why its published expertise is credible.
FocusAI Entity Footprint
SystemHuman strategy × AI power
NextDefine the entity
Make the next move useful
An entity footprint is evidence, not a single markup field.
Search and AI systems can draw on many public signals when interpreting an organisation: its own website, structured data, author and organisation details, independent references, consistent naming and the relationships between topics and pages. Inclusion or citation cannot be assured by any single signal. The practical goal is to remove ambiguity and publish useful, supportable information.
Put entity clarity into practice with AI SEO services for entity and search visibility, evidence-led content marketing, website structure and conversion improvements, and an AI search visibility audit.
Keep organisation, service and author details consistent across first-party pages
Use structured data to describe visible content rather than create claims
Support expertise with clear sources, ownership and independent corroboration
The signals to review
Four parts of a credible AI entity footprint.
These areas can improve machine-readable clarity and human trust, but they do not guarantee rankings, citations or inclusion in an AI-generated answer.
02
Structured data
Connect valid Organization, WebSite, WebPage, Article, Service and author markup to content people can see and verify on the page.
03
Topical authority
Publish a connected body of useful material that explains the subject, answers related questions and distinguishes evidence from opinion.
04
External corroboration
Treat relevant third-party mentions, profiles and citations as supporting evidence, without inventing endorsements or relying on volume alone.
A practical review
Assess the footprint before adding more content.
The review defines the business job and evidence required for AI entity footprint. The first phase produces a question set, source-page findings, entity corrections and repeatable visibility checks. External model behaviour, mentions and citations cannot be guaranteed; third-party evidence must be earned legitimately.
Our recommendations are grounded in recognised industry guidance, including Google Search Central SEO guidance.
1
Define the entity
Record the canonical organisation name, services, people, locations and topic relationships that the business can verify.
2
Audit first-party signals
Check canonical pages, about and author information, internal links and structured data for consistency with visible content.
3
Check corroboration
Review relevant independent references and profiles, noting conflicts, unsupported claims and evidence gaps.
4
Monitor representative queries
Track a documented set of search and AI prompts over time, while recognising that outputs are variable and not guaranteed.
Repeatable visibility check
Create a baseline you can compare without overclaiming.
Run the same queries with the same wording and settings. The set should reflect how people identify the brand, find its category and test its claimed expertise; it is a sample for observation, not a complete measure of demand.
Branded
Check whether the organisation is identified consistently.
- What is [organisation name] known for?
- Who are the experts at [organisation name]?
Category
Observe visibility where a buyer is comparing providers or approaches.
- Which companies help with [service] in [market]?
- What should I look for in a [category] partner?
Expertise
Test whether published knowledge appears around supported topics.
- How should a business approach [specialist topic]?
- What are the risks and best practices for [specialist topic]?
Record every observation
Keep one row per query and system run. Preserve the output even when the organisation is absent.
- Exact query and category
- AI or search system, mode and account/location context
- Observation date
- Output or an archived screenshot/transcript
- Whether the organisation or its content was included
- Every cited source URL, including third-party sources
- Relevant entity or source-page changes since the previous run
Comparison cadence
Record a baseline before material entity changes, repeat the full set monthly for three months, then review quarterly. Add a separate run after a major source-page, structured-data or corroboration update; do not replace the scheduled comparison with that run.
Observation is not causation
Report inclusion, wording and cited sources as observations. A change after entity work is correlation, not proof that the work caused the result: model updates, retrieval changes, location, personalisation, competitors and source freshness can also affect an answer. Use repeated patterns to form a hypothesis, then check other evidence before assigning causation. No cadence or signal can ensure future inclusion.
Make the next move count
Need to review the source evidence?
Bring priority questions and the pages or public facts buyers should find.
