How answer engine optimization works, AnswerWins

The 5 signals AI engines use to choose a source

When a buyer asks an AI to recommend a tool or vendor, the model doesn't guess, it weighs a handful of signals to decide which 3-5 sources to cite. Optimizing those signals is the entire job.

01 · the biggest lever

Third-party authority

Around 91% of AI citations come from third-party sources, buyer guides, roundups, review platforms, Reddit, not the brand's own website. Getting named in the places the model trusts beats any on-site change.

Reviews & ratings

Models weight review volume and average rating heavily. A product with reviews in its data beats an identical one without, regardless of how good the page is.

Extractable, structured content

Schema.org markup and clear, self-contained answers let the model parse and quote you. If it can't instantly read your price, features, and proof, it skips you and cites a competitor.

Pricing & availability accuracy

Inconsistent or stale facts read as a data conflict and drop you from consideration. Clean, current, consistent data keeps you eligible.

Freshness & consistency

Recent, dated, corroborated information across multiple sources is trusted more than a single stale page. We keep the signals aligned everywhere the model looks.

the result

You become the answer

When these signals line up, the model names you instead of a rival, for the exact questions your buyers ask. And we prove the movement with a monthly measurement.

Our process

Week 1 · Measure

AI Visibility Sprint

We map the 30-50 questions your buyers ask AI, score where you stand vs competitors on each, and hand you a ranked 90-day plan.

Months 1-3 · Execute

Done-for-you

We run the levers: third-party authority, reviews, structured content. You approve, we do the work.

Monthly · Prove

Re-measurement report

The same audit, re-run every month: cited X → Y, question by question. You only continue if the number moves.

Always · Transparent

See it yourself

We do this on our own properties in public and publish the numbers. See our proof →

Common questions

Is this just SEO with a new name?

No. SEO competes to rank in a list of links the user clicks. AEO competes to be cited inside the AI's answer, often with no click at all. The fundamentals overlap, but the winning levers (third-party authority, structured data the model can parse, review signals) are weighted very differently by language models than by Google's ranking.

Which AI engines do you optimize for?

The ones your buyers actually use: ChatGPT (and ChatGPT Search), Claude, Perplexity, and Google's AI Overviews. They retrieve and cite sources in similar ways, so the work compounds across all of them.

How long until it moves?

Authority signals take weeks to land and be re-crawled, so we work in 90-day cycles and re-measure monthly. You see the trend in the first report and the movement by month 2-3. We don't promise overnight results, we promise a measured number that goes up.

How AI decides who to recommend, and how we get you in.