Answer engine optimisation
Be the answer when buyers ask AI who to trust.
Help AI assistants such as ChatGPT, Gemini, Perplexity, Claude and Copilot understand, describe and appropriately recommend the brand for high-intent questions.
Why it matters
What AEO is for.
Buyers increasingly ask AI assistants for recommendations rather than scanning a page of links. Instead of ten results, they receive one synthesised answer that names a few brands, explains why and cites a handful of sources. Being absent from that answer - or described inaccurately - can remove a brand from consideration before a website is ever visited.
Answer engine optimisation is the discipline of improving how those systems understand and represent a brand. We map the questions that reveal genuine buying intent, document how selected assistants currently answer them, trace the sources behind those answers and close the gaps in clarity, evidence and authority that limit the brand’s presence and fit.
AEO builds on strong SEO foundations and depends on credible independent sources, which is why it is closely connected to strategic PR placement. Our methodology explains how we measure change without claiming control over independent models.
Common challenges
- The brand is absent from AI answers to the questions closest to a buying decision.
- Assistants describe the brand inaccurately, vaguely or for the wrong audience.
- Competitors are cited from sources where the brand has no presence.
- There is no baseline for how AI currently presents the brand.
What we deliver
- High-intent prompt universe
- Model-response baseline across selected assistants
- Citation and source-pattern analysis
- Entity and content gap roadmap
- Ongoing AI visibility reporting
How we work
A clear path from diagnosis to results.
- 01
Map high-intent prompts
Build a prompt universe from buyer roles, decision stages and comparison criteria, focused on questions closest to commercial consideration.
- 02
Baseline the answers
Document how selected assistants respond: whether the brand appears, how it is described, who it is compared with and which sources are cited.
- 03
Close the evidence gaps
Strengthen owned content, entity information and independent sources so assistants have clearer, more credible evidence to work from.
- 04
Re-test and adapt
Repeat the agreed prompt set on a set cadence, interpret movement as directional evidence and adjust priorities as models and markets evolve.
How progress is measured
- Presence in answers to agreed prompts
- Fit of recommendations to the right buyer and need
- Accuracy of brand descriptions
- Quality of sources cited alongside the brand
Delivered through
Built on our core infrastructure.
Every service draws on the same connected infrastructure, so research, evidence and measurement compound across the programme rather than living in separate silos.
Measurement is directional evidence, not a guarantee of ranking, recommendation or commercial outcome.A good fit when
- Buyers in your category increasingly ask AI assistants for recommendations.
- Competitors appear in AI answers to questions where you have stronger credentials.
- Assistants describe the brand vaguely, inaccurately or for the wrong audience.
- You want a measured, evidence-led view of AI visibility rather than anecdotes.
Where this matters most
Industries we apply this to.
The approach adapts to the language, intermediaries and evidence of each market. These are the sectors where AEO most often shapes consideration.
Frequently asked
AEO questions
What is answer engine optimisation?
Answer engine optimisation (AEO) is the practice of improving how AI assistants and AI search features understand, describe and recommend a brand. It focuses on clear answers to real buyer questions, accurate entity information and credible supporting sources rather than keyword rankings alone.
How is AEO different from SEO?
SEO focuses on ranking pages in search results. AEO focuses on whether a brand appears, and how it is described, inside a synthesised AI answer. The two share foundations, but AEO places more weight on direct answers, entity clarity and the independent sources assistants cite.
Which AI assistants do you cover?
Programmes typically include ChatGPT, Gemini, Perplexity, Claude and Copilot, selected according to where your audience researches. Coverage is agreed at the start of each engagement.
Can you guarantee that AI will recommend us?
No. Independent models decide their own outputs, and those outputs vary between runs and versions. We improve the clarity, evidence and authority that recommendations may depend on, and we measure directional change against a documented baseline.
Do we need special markup or an llms.txt file?
No special markup is required. Google states that its AI features rely on standard search foundations, and llms.txt remains an informal proposal. What matters most is visible, accurate content that answers real buyer questions, supported by credible independent sources. Structured data can still help clarify facts, but it is not a shortcut.
Private AI visibility assessment
Start with a clear view of where to act.
Establish how assistants interpret your brand today, which questions matter, and where infrastructure can improve speed, learning and compounding results.
Request a private assessment