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Search is splitting into two paths: the ten blue links, and the single direct answer a machine reads out loud. AEO engineers your content, entities and evidence so that answer names you — across Google AI Overviews, ChatGPT, Perplexity and Copilot.
"best {category} for {use-case}"
Named as the direct answer across all four engines — this is the answer share AEO builds and protects.
What is answer engine optimization?
Answer engine optimization is the practice of structuring a brand's content, entities and evidence so that when an AI answer engine gives one direct answer, that answer names — and links — you.
It is scoped more tightly than generative engine optimization: GEO is about being visible and citable across generative search generally, AEO is about winning the single featured answer inside it. Digital Otters runs both as one programme, because the technical foundation is shared and only the content shape differs. Start with the AI Visibility Audit if you need a baseline, or read the Generative Engine Optimization and AI Search Visibility pages for the wider programme.
How an answer engine picks its one source
Four stages, each with its own failure point. The audit tells you which stage is costing you the citation.
- 01Retrieve
The engine pulls a shortlist of candidate pages from its index or a live search call.
Risk: not indexed or crawlable - 02Parse & verify
It checks entity consistency, structured data and whether the facts match across the web.
Risk: inconsistent facts - 03Rank sources
Candidates are scored on authority, freshness and how directly they answer the question.
Risk: buried, indirect answer - 04Cite one
Usually a single source gets named or linked in the direct answer — everyone else gets nothing.
Risk: competitor wins the slot
AEO and SEO want different things
| Factor | Traditional SEO | Answer engine optimization |
|---|---|---|
| Goal | Rank in the top 10 results | Be the single cited answer |
| Unit of success | Position, clicks, sessions | Mention rate, citation rate, share of voice |
| Content shape | Long-form, keyword-structured pages | Extractable, quotable, fact-dense passages |
| Technical layer | Crawlability, speed, backlinks | Schema, entity graphs, crawler access for AI bots |
| Feedback loop | Rank tracking, weekly/monthly | Prompt panel testing, per assistant, per release |
Six workstreams, run monthly
What each answer engine actually weighs
Pick a platform to see what it prioritises when it chooses the source it names.
Pulls almost entirely from pages already ranking organically, then summarises the top few. Winning here starts with the same technical SEO and content depth that wins classic search — AEO adds the answer-shaped summary an LLM can lift cleanly.
Blends its training knowledge with live browsing for recency-sensitive queries. Brand mentions baked into widely-syndicated, fact-consistent content carry weight even without a live citation.
Always cites — it's a research engine by design. Ranking here is closest to classic SEO: authority, freshness and directly-quotable passages that survive being lifted verbatim.
Leans on Bing's index and Microsoft's own entity graph. Structured data and consistent NAP and entity facts matter more here than raw content volume.
What each answer engine actually weighs
Pick a platform to see what it prioritises when it chooses the source it names.
Pulls almost entirely from pages already ranking organically, then summarises the top few. Winning here starts with the same technical SEO and content depth that wins classic search — AEO adds the answer-shaped summary an LLM can lift cleanly.
Blends its training knowledge with live browsing for recency-sensitive queries. Brand mentions baked into widely-syndicated, fact-consistent content carry weight even without a live citation.
Always cites — it's a research engine by design. Ranking here is closest to classic SEO: authority, freshness and directly-quotable passages that survive being lifted verbatim.
Leans on Bing's index and Microsoft's own entity graph. Structured data and consistent NAP and entity facts matter more here than raw content volume.
Four numbers, per engine, every month
Share of the buying-question panel where you're the named direct answer.
How often your actual page is linked, not just your name surfaced.
Where you land among the sources each engine chooses when it does cite.
Your answer share versus the competitors named most often, tracked over time.
Three phases, then it repeats
The first three phases build the foundation; after that the panel re-runs every month and the work follows what moved.
- Phase 1Baseline & scope
Prompt panel built, run across all four engines, gaps ranked by effort and impact.
- Phase 2Technical foundation
Entity, schema and crawler access fixed so engines can retrieve and trust your pages.
- Phase 3Answer-shaped content
Priority pages rewritten to be directly extractable, with evidence added.
- MonthlyRe-test & expand
Panel re-run monthly; new prompts and markets added as answer share grows.
Three ways in
Start with the diagnostic if you need a baseline, or scope straight into the retained programme. Multi-market work is quoted against the markets and languages it covers.
Know your baseline before you spend on fixing it.
- Prompt panel across 4 engines
- Entity & crawler review
- Prioritised roadmap
Actively building answer share across every major engine.
- Everything in the audit
- Entity & schema implementation
- Answer-shaped content programme
- Citation & evidence building
- Monthly re-testing & reporting
Multi-market brands defending answer share in every language.
- Everything in the core programme
- Multi-market, multi-language panels
- Competitive answer-share benchmarking
- Dedicated strategist
Fees exclude media spend and third-party tooling. No agency can guarantee an engine's output — what is guaranteed is the baseline, the technical work and the monthly re-test that shows whether answer share moved.
Three ways in
Start with the diagnostic if you need a baseline, or scope straight into the retained programme. Multi-market work is quoted against the markets and languages it covers.
Know your baseline before you spend on fixing it.
- Prompt panel across 4 engines
- Entity & crawler review
- Prioritised roadmap
Actively building answer share across every major engine.
- Everything in the audit
- Entity & schema implementation
- Answer-shaped content programme
- Citation & evidence building
- Monthly re-testing & reporting
Multi-market brands defending answer share in every language.
- Everything in the core programme
- Multi-market, multi-language panels
- Competitive answer-share benchmarking
- Dedicated strategist
Fees exclude media spend and third-party tooling. No agency can guarantee an engine's output — what is guaranteed is the baseline, the technical work and the monthly re-test that shows whether answer share moved.
Where AEO sits in the programme
The one-off baseline this programme is usually built on.
Explore Sibling disciplineGenerative Engine OptimizationThe broader technical and content foundation AEO draws on.
Explore Parent programmeAI Search VisibilityThe full cross-platform strategy AEO sits inside.
Explore Sibling serviceChatGPT VisibilityDeep-dive on the most-used assistant and its ranking mechanics.
Explore Sibling serviceGemini & Perplexity VisibilityGoogle's assistant and the always-cited research engine.
Explore FoundationSEO ServicesIndexed authority still feeds most engines' retrieval step.
ExploreWhat engineers and heads of growth ask us
Send the URL, the platform and what changed. You get a written technical read from the person who would run the audit.
Ask a questionWhat is the difference between an audit and ongoing technical SEO?
An audit is a point-in-time diagnosis with a prioritised backlog. Ongoing work supports implementation, reviews new templates before release, QAs staging, monitors regressions and keeps the backlog current as the site changes. Most teams need the audit once and the ongoing support during a period of heavy development.
Can you work with Next.js, Nuxt, Remix or a custom SPA?
Yes. We review source HTML, rendered output, routing, metadata timing, canonical behaviour, streaming, caching and deployment patterns. Recommendations differ depending on whether rendering is static, server-side, streamed or client-side — we scope after seeing how your app actually renders, not from the framework name.
Do you fix the issues or only report them?
Either. For client-controlled codebases we write implementation tickets with acceptance criteria and work alongside your developers, including PR review. Where the CMS and scope allow, we implement directly and validate the release ourselves.
How long does a technical SEO audit take?
A small marketing site is one to two weeks. Large ecommerce, marketplace or international sites take three to six, because findings have to be segmented by template, market and business impact — and because log-file analysis needs a full 30-day window to be meaningful.
Can technical SEO recover traffic lost after a migration?
It can resolve migration-caused problems: missing or chained redirects, changed canonicals, blocked resources, altered architecture, indexation errors. Recovery also depends on how long the problems persisted and whether content, links or demand changed at the same time. We tell you which of those we can see in the data before quoting.
Is Core Web Vitals a ranking factor?
Page experience is one input among many, and a weak one relative to relevance. We improve field vitals because speed and stability affect conversion and crawl efficiency as well as search — not because one score is a strategy. Anyone selling a 100 Lighthouse score as an SEO plan is selling the wrong thing.
How much does a technical SEO audit cost?
It moves with URL count, template variety, JavaScript complexity, international or ecommerce features, whether log-file analysis is in scope, and how much implementation support you need. Starting points are on this page; we review the site before proposing a scope.
Does technical SEO affect ChatGPT, Copilot and AI search?
At the eligibility level, yes. Search-connected AI systems depend on crawlable, indexable, well-structured content. Robots rules, CDN and WAF access, canonicalisation, internal links and clear textual HTML all affect whether your content can be retrieved at all. No agency can guarantee citation — but being unfetchable guarantees the opposite.
