See what answer systems say about your brand
- Test relevant questions
- Trace the sources
- Track change over time
We test relevant questions in ChatGPT, Perplexity, Gemini, and AI search, analyse the sources, and set up the next content and technical experiments.
“For this question, the answer system mentions your brand and cites the following sources.”
- 1your-brand.com
- 2industry-portal.com
- 3trade-press.com
Research no longer ends at a list of links
Many search and research journeys now include a written answer. That makes it important to understand whether your brand is described accurately and supported by traceable sources.
A comparison of the leading providers — services, reviews and ratings at a glance.
“For this question, the answer system mentions your brand and cites the following sources.”
- 1your-brand.com
- 2industry-portal.com
- 3trade-press.com
Three things need separate measurement
Which brands and claims appear for your relevant questions?
Which owned and third-party pages support those claims?
What shifts after a technical or editorial intervention?
Without a baseline, AEO remains a claim
Answers vary by question, model, mode, and date. We therefore start with a repeatable question set and documented results.
“For this question, the answer system mentions your brand and cites the following sources.”
- 1your-brand.com
- 2industry-portal.com
- 3trade-press.com
Four factors influence your visibility
They help explain why content may be found, understood, cited, or ignored.
Retrieval
The model pulls live content from the web and its index. Findable = retrievable.
Trust
Authority, consistency and third-party citations make you a reliable source.
Extractable
Clearly structured, unambiguous content can be cited cleanly in answers.
Freshness
Fresh, complete information is preferred — outdated content loses.
From SEO to GEO — the rules of the game are changing.
Being found
- Goal
- Ranking in the list
- Unit
- Keyword
- Success
- Clicks & traffic
- Audience
- Human searches
Appearing in answers
- Goal
- Cited in the answer
- Unit
- Entity & prompt
- Success
- Mentions & sources
- Audience
- AI mediates
SEO remains the foundation. AEO and GEO add questions, sources, mentions, and the quality of generated answers.
What do answer systems say about your brand today?
An AEO baseline creates a documented starting point for the next tests.
What we work on
From brand authority to monitoring — every lever pays into one of the four factors.
Brand & entity authority
Consistent brand data and relevant entity sources can help systems distinguish your organisation.
Structured data
Schema.org markup so machines read offers, FAQs and facts unambiguously.
Answer-oriented content
Clear definitions, questions & answers and summaries — directly citable.
Crawlability & llms.txt
Clean technology, fast rendering, and a deliberate decision about which crawlers may retrieve your content.
Citability & signals
PR, reviews and third-party sources the AI trusts — external validation of your brand.
Monitoring & steering
Repeat a fixed question set, log answers and observe how results change over time.
Start with a baseline, then run a learning loop
We separate measurement, hypothesis, and implementation so observed change does not turn into false certainty.
AEO baseline
We test an agreed question set, document answers and sources, and form the first testable hypotheses.
- Question set by audience and offer
- Answer and source log
- Technical, entity, and content analysis
- Prioritised experiments with a measurement plan
AEO Operations
We implement prioritised measures, repeat the tests, and document what changed.
- Content, entity, and technical experiments
- Repeatable tests over the fixed question set
- Change log instead of a vanity dashboard
- Regular decisions on the next hypotheses
Scope and cadence depend on the question set, markets, languages, and implementation needs.
Technology, content, and measurement in one working loop
Tech & content in one hand
We can test technical, structural, and editorial hypotheses together.
A repeatable starting point
Questions, answers, sources, and changes are recorded so a later comparison is possible.
Honest uncertainty
We separate observed change from causality and do not promise a recommendation by someone else's model.
Teams we have built products and systems with
Start with a defensible AEO baseline
We will identify the questions, systems, and markets that belong in your first measurement cycle.