AEO Is the New ASO
Ten years ago, app store optimization rewarded the people who got in early. Answer-engine optimization is at the same moment now — and the lessons from ASO transfer almost directly.
What is AEO?
Answer-engine optimization is the practice of making your product, company or expertise the source an AI system cites or recommends when someone asks a question. It is to ChatGPT, Claude, Gemini, Perplexity and Google’s AI Overviews what SEO was to search results — and what ASO was to app stores.
Why is AEO like early ASO?
Ten years ago, app store optimization was a window. Most teams treated store listings as an afterthought; the few who understood how discovery worked — what people searched, how the store ranked and converted — compounded quietly. Then the window closed: keyword fields filled up, paid search took the top slots, and the early advantage became table stakes.
AI discovery is at that same moment. Discovery is migrating from ten blue links and store charts to a single synthesised answer. Most brands have not noticed. The ones that become the cited source now will compound the way early-ASO winners did.
What is structurally different about AI discovery?
Models answer from what they learned during training plus what they retrieve at answer time. The training part lags reality: a model can keep recommending yesterday’s winner after the market has moved — the “stale restaurant” problem. That gap cuts both ways. It punishes brands that are invisible in the sources models learn from, and it rewards those that are consistently present, specific and easy to quote before the next training cycle.
Which ASO lessons transfer to AEO?
- Start from the query, not the keyword. In ASO you learned what players were actually trying to do. In AEO, write down the real questions your customers ask — “how do I calculate marginal ROAS?”, “who can audit my mediation setup?” — and answer them directly.
- Make the promise explicit. Your first three screenshots had to explain the game in four seconds. Your pages need a direct, quotable answer in the first lines of each section.
- Be consistent everywhere. Store, ads and first session had to tell one story. Your site, LinkedIn, directories and bios need the same facts, stated the same way.
- Earn the proof. Ratings and reviews shaped store conversion; citations, original data and named expertise shape AI answers.
- Measure choice, not vanity. CVR mattered more than impressions. Track whether you are cited for the questions that lead to business, not how often your name appears.
What does that look like in practice?
Pages that answer one question each, with definitions, formulas and worked examples; structured data that matches the content; an llms.txt file that tells AI crawlers what the site covers; tools and glossaries other people link to; and a regular check of how AI assistants answer your ten most important questions. This site is built that way — the glossary, the free tools and the article summaries are the AEO layer.
If you ran ASO in 2015, you already know how this movie ends. What are you doing about AEO today?
Related: ASO Is an Organic Growth System · Your Store Listing Is a Conversion Surface · Glossary: ASO