Answer engine optimization for apps, games and ecommerce. Assistants hand buyers a shortlist now, not a page of links. We get you onto it.
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Answer engine optimization is the work of getting a brand named, quoted and linked inside AI answers. Admiral Media runs it for apps, games and ecommerce brands across six workstreams: entity foundation, a machine readable surface, content built to be extracted, citations and mentions, prompt monitoring and monthly reporting. Every engagement runs all six, because they compound.
Models answer with things they can identify. We make your brand an unambiguous entity, described the same way everywhere it appears.
Give the crawlers something written for them, not a brochure they have to reverse engineer.
Assistants lift passages, not pages. We rewrite the ones that matter so a clean, quotable answer is easy to find.
Models trust a claim that appears in several places they already retrieve from. We go and put it there.
We track the questions your buyers actually type, across every major assistant, and watch who gets named.
One monthly view of where you gained a citation, where you lost one, and what we are doing about it next.
A results page gives you ten slots and a scroll. An answer gives you one paragraph and about three names. Every rule below changes when the list becomes a sentence, which is why answer engine optimization is not search engine optimization with a new label.
| Dimension | Classic SEO | |
|---|---|---|
| You win by | Ranking a page in a list | Being named inside the answer |
| The unit | A keyword | A question a real buyer types |
| What gets read | A page, by a crawler | A passage, by a model that has to trust it |
| What you optimise | Titles, links, page speed | Entities, structured data, extractable passages, citations |
| Authority comes from | Backlinks | Consistent mentions across sources models retrieve from |
| How you measure | Position and clicks | Citation share, mention count, assistant referral traffic |
Worth saying plainly You need both. Assistants read the open web, so the pages that rank are usually the pages that get quoted.
Answer engine optimization is not one playbook. What gets a subscription app named is not what gets a game named, because the sources a model reaches for are different in each category. These are the six we run it in.
“Which app actually helps me stick to a habit?”
Assistants lean on app roundups and review corpora here, so the work is getting into the comparison sources they retrieve from, and making trial terms and outcomes machine readable rather than buried in a paywall.
Subscription app marketing Mobile games“What should I play next if I liked this one?”
Game answers are built from community sources and wikis more than from your own site, so entity accuracy across those and a real presence in the places players actually discuss the genre is what moves you.
Game user acquisition Ecommerce“Where should I buy this, and is it any good?”
Product level structured data and review corpora decide whether an assistant can quote a specific item at a specific price, so the entity work runs down to the product, not just the brand.
Ecommerce marketing Fintech and crypto“Is this app safe, and which one should I trust?”
Models hedge hardest in regulated categories. Authority signals, clear regulatory language and corroboration on sources they already trust matter more here than anywhere else.
FinTech app marketing EdTech“What is the best app to teach my child to read?”
Parents ask assistants before they ask the store. Expert citation, credible third party mentions and clearly stated age ranges are what get a product named in that answer.
EdTech app marketing SaaS and AI tools“What is the best tool for this, and what are the alternatives?”
This category is decided by comparison and alternatives pages, most of which you do not own. We make sure the ones that rank describe you correctly, and that your own comparisons are extractable.
SaaS performance marketingBy the end of week two you will know how often an assistant names you today, how often it names the brand you are chasing, and which of the two of you it links. You can judge the rest of the quarter on that, rather than on our enthusiasm.
We measure how often you are named today, across assistants and against your category. Entity gaps, crawler access and content readiness get audited at the same time.
Schema graph, llms.txt, AI information page and crawler policy go live. This is the part most brands have never done, and it moves fastest.
Priority pages get restructured so a model can lift a clean answer, and we publish the questions your category asks that nobody has answered properly.
We earn mentions on the sources assistants actually retrieve from, so the claim about you exists in more than one place.
A citation is not a ranking you hold. Prompts shift, models update, competitors move. We monitor monthly and keep pushing.
Every seat runs on Peec AI, an answer engine analytics platform we do not own. It puts your buyers’ real questions to the assistants on a schedule and records who gets named, in what order, in what tone, and which sources the model leaned on to say it. The recorded answers make visibility easier to inspect. We assess commercial outcomes separately because a mention is not a qualified enquiry.
The share of tracked answers where you get named at all. This is the number that has to move first, because everything after it is a refinement of it.
When you are named, are you first or fourth. Position describes the order of mentions in the tracked answer. Interpret it alongside the answer itself, citation quality and the buyer question.
Whether the model describes you well, neutrally or badly. Being mentioned and being recommended are not the same event, and only one of them sells.
Which pages and domains the answer was assembled from. This is a work list, not trivia: it tells us exactly where to go and earn the next mention.
The same three numbers for the brands you are actually losing deals to, on the same prompts, week over week.
Because a number you cannot audit is a number you should not trust. Peec AI runs the same prompts for the brands you compete with as it runs for you, it exports, and it does not care who is paying. We would rather hand you an instrument you can check than a slide we made.
For a subscription app or DTC brand, a useful proposal connects the questions buyers ask with evidence they can check. It should explain the work, how progress will be measured and what remains outside the agency’s control.
Agree the products, countries, languages and decisions you want to understand. For a subscription app, include questions about use cases, alternatives, trial terms and suitability. For a DTC brand, include product comparisons, delivery, returns and the evidence behind product claims. Keep branded questions separate from category questions, so an easy brand lookup does not obscure weak discovery.
If Germany is a target market, include German-language questions and the sources buyers use there. A US result in English is not a substitute for that evidence. Record the model, date, exact prompt and cited sources with each observation.
A screenshot of a visibility chart is a starting point. Ask to inspect the underlying answer, whether it names the brand correctly and whether its links support the claims. Separate a brand mention from a citation to your website. Check whether a recommendation fits the customer’s needs, rather than counting every favourable adjective as progress.
A case study should state its starting position, the work completed, the measurement period and the limits of the comparison. A newly published page proves that work was delivered. It does not, by itself, prove that the work caused an AI recommendation or a sale.
Technical checks should establish whether important pages can be accessed and understood, whether the facts agree across the site and whether structured data matches the page. Google says there is no special schema required for its AI features. Its guidance for website owners is a useful reference when evaluating claims about mandatory AI markup.
Content work should answer a real buyer question with supported information. External coverage should come from relevant publishers and real customer experience. Ask who controls each source and distinguish an editorial mention, a paid placement and an agency-owned page.
Keep the same prompt cohort when comparing periods, and report changes by country, language, model and topic. Alongside visibility, inspect factual accuracy and the reasons for negative descriptions. A change in the question mix or the model can change the score without a change in your business.
For acquisition, track identifiable referrals and accepted enquiries through qualification and revenue where the data permits it. A mention, citation or visit is not a qualified lead. Some journeys will remain unattributed; report that gap instead of assigning every improvement to AEO.
The proposal should name who approves factual claims, supplies product evidence, edits the website and handles publisher contact. Agree access, reporting, deliverables and commercial terms in writing. No agency can guarantee how an independent model will answer a future question. The useful commitment is a clear scope, documented changes and an honest review of the results.
Discuss your category and current evidence with Admiral Media.
These files document work on our own website. They show the implementation, not a guaranteed ranking, citation or commercial result. Use them to inspect the approach, and ask for separate evidence of changes in visibility and qualified enquiries.
admiral.media/llms.txt
A structured summary of who we are, what we do and which pages matter, in a format assistants can parse without guessing.
Open the fileadmiral.media/ai-information
One page stating the company facts, services, leadership and verified proof points, so an assistant never has to assemble us from scraps.
Open the pageadmiral.media/robots.txt
Explicit rules for GPTBot, ClaudeBot, PerplexityBot, Google-Extended and the rest. Most sites have never made this decision on purpose.
Open the file
“They always know the current best practices and are able to stay ahead of the curve.”
“Since the beginning of our work with Admiral Media, we have seen only one direction: upwards.”
“They were always available, responded quickly to messages, and were receptive to feedback.”
Entity cleanup, passage rewriting and earning real mentions do not scale with a tool. They scale with senior hours, and we only have so many.
This is a young discipline. Three engagements let us go deep, learn fast and keep the method sharp instead of spreading it thin.
One brand per category. If we win a citation for you, we cannot honestly go and win the same citation for your competitor, so we will not take them. This is written into the engagement, not a sales line.
Opens for Q4. Closes when the third is taken.
Tell us your category and where you think you stand. If a brand in your space has already taken a seat we will say so in the first reply, because the category lock cuts both ways.
Book a meetingEnglische Testfragen aus einem anderen Markt beschreiben nicht automatisch die Sichtbarkeit im DACH-Raum. Fragen, Sprache und Quellen sollten zu den Käufern passen, die Sie erreichen möchten. Dokumentieren Sie, wie Zielmarkt und Standort in der Messmethode berücksichtigt werden.
Ein Bericht sollte die getesteten Fragen, das Modell, den Zeitpunkt und die genannten Quellen zeigen. Markenerwähnungen, Links zur Website und tatsächliche Anfragen sind getrennte Ergebnisse. Aus einer einzelnen Antwort lässt sich weder eine stabile Position noch die Ursache einer Veränderung ableiten.
Answer engine optimization is the practice of structuring your brand’s content, entities and public evidence so that AI assistants name, quote and link you when they answer a question in your category. Classic SEO gets a page ranked in a list. Answer engine optimization gets your brand into the answer itself.
In practice they describe the same job. Generative engine optimization is the term used more often for generative assistants, answer engine optimization for cited answers and AI Overviews. We run one programme covering both, because the underlying work is identical: be identifiable, be extractable, be corroborated.
The technical foundation is live inside four weeks and usually moves first, because most brands have never done it. Citations and mentions build over the following months. This is a compounding programme, not a switch, and any agency promising you an assistant citation by a fixed date is guessing.
No, and nobody can. Model providers do not sell placement and their retrieval changes without notice. What we control is everything that makes you the obvious thing to cite: a clean entity, machine readable pages, extractable answers and corroborating mentions. We report the movement honestly, including when it goes the wrong way.
On Peec AI, an answer engine analytics platform we do not own. We build a prompt set for your category, it runs those prompts against ChatGPT, Google AI Overviews, Google AI Mode, Perplexity, Gemini and Microsoft Copilot on a schedule, and it records visibility, which is how often you are named at all, position, which is where you sit when you are, and sentiment, which is how you get described. It also captures the sources each answer was built from, which is what tells us where to earn the next mention. Your competitors run on the same prompts, so the comparison is like for like.
Yes. Assistants retrieve from the open web, so the pages that rank are often the pages that get quoted. Answer engine optimization sits on top of solid search and content work rather than replacing it. If your technical foundation is broken we will say so in week two.
We run it for subscription apps, mobile games, ecommerce, fintech and crypto, EdTech, and SaaS and AI tools. The method is the same in each, but the sources differ: a game answer is assembled from community posts and wikis, an ecommerce answer from product data and reviews, a fintech answer from whatever a cautious model already trusts. We build the source strategy per category rather than running one playbook everywhere.
Apps, games and ecommerce brands with a real category to compete in and something worth being recommended for. It works best when there is already a product people like and a buyer who researches before choosing. If you want to read more first, we publish our thinking on answer engine optimization for apps and AI search optimization.
A strategist reads every message, not an automated sequence. You get a straight answer on whether your category is winnable, and if it is not, we will tell you that too.
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Q4 intake · three seats · one brand per category