A step-by-step plan to improve your answer engine optimization: five moves, in order, that take a business from unmentioned to named across ChatGPT, Gemini, Claude, and Perplexity.
Run your buyers' questions across all four assistants and record who gets named and how you are framed when you appear at all. Improvement starts with knowing which answers you are losing and to whom.
For each lost question, compare your page against the cited winners. Usually the gap is structural: the winner answers in the first screen with concrete claims; your page warms up for four paragraphs. Restructure before you write anything new.
If your page is strong but still unnamed, the model does not trust you enough yet. Get listed and consistently described in the sources it cites for that question. One well-placed mention in a trusted roundup regularly outperforms a month of on-site edits.
Once you hold a head question, claim its variants: by budget, team size, industry, and urgency. Variants have lower competition and higher intent, and holding a cluster stabilizes your presence against model updates.
Answers drift. Re-run the panel monthly, alert on losses, and fix the highest-revenue gap first. That cadence is the entire difference between improving AEO once and owning it. Aethon automates the loop end to end, book a demo.
Audit your current answers, restructure losing pages to answer in the first screen, earn corroboration in cited sources, expand to qualified variants, and re-measure monthly.
Usually one of three gaps: your content is not extractable, your brand facts are inconsistent across sources, or you lack presence in the sources the model cites.
Track mention rate, position, and framing across repeated runs on a fixed prompt panel, per assistant, month over month.