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You know where you stand
It starts with a measurement, not a proposal. You see in black and white which AI answers name your company and which do not, with a date and a question set.
AEO works on individual questions. Who asks them, what the best answer is in four sentences, and whether yours is written so a system can lift it. Narrower than GEO, and quicker to take effect.
Definition
Share of owned answer passages
Across the questions in your set: how often the quoted paragraph clearly comes from you rather than a comparison portal or a competitor.
Answer engine optimisation works on the smallest unit: a single question and the passage that answers it. The target formats are answer boxes in search, the short reply from an assistant, and the quoted paragraphs inside a chatbot.
The work has three parts. First, finding out which questions your audience actually asks, in their words rather than yours. Second, writing the answer so it holds up without context, because it will be lifted out. Third, marking it up as what it is.
A good answer passage stands on its own. It names the subject rather than saying “we”, it carries the point in the first sentence, and it keeps figures, limits and dates where they belong.
How it runs
From search data, your sales team, your support desk and the follow-ups chatbots ask on their own. The customer's phrasing counts, not the internal one.
Point in the first sentence, reasoning after it, limits at the end. Fully understandable without the page around it.
FAQPage or HowTo as JSON-LD, generated from the same source as the visible text. Two copies drift apart.
Is the passage being used, and if not, whose text stands there instead. That sets up the next round.
Boundaries
AEO operates at the level of single questions. If your brand does not appear at all because nobody outside your website mentions you, the best-written passage will not help. What is missing then is trust in the source, not phrasing.
In that case GEO as a full programme is the right frame, or LLMO when it is specifically about sources and mentions. Which of the three applies shows up in the first measurement.
Common questions
Difference
Not a judgement on individual agencies, but a description of two approaches. The right column is checkable, because this website itself is built that way.
| Difference | Usual agency approach | agenticsearch.at |
|---|---|---|
| Starting point | A proposal after a first call | A measurement with a date, before anything gets recommended |
| Basis | Keywords from classic search | A question set of real prompts, clustered and prioritised |
| Proof of success | Rankings and a visibility index | Mentions per question and system, with the raw data |
| Reporting | A monthly dashboard with curves | The same measurement repeated, change called only after three runs |
| When unsure | Try it and see what happens | We say what is not evidenced, and write it on the page |
| Tooling | Agency licences, access ends with the contract | The question set and the data are yours, afterwards too |
| Scope | As many channels as possible from one supplier | A capped number of concurrent projects, otherwise we turn it down |
Your guides
You know your business, your customers and your offer better than any agency does. What is usually missing is solid numbers on how AI systems talk about it, and an order in which to tackle that.
The number of concurrent projects is capped. When a piece of work needs more capacity than exists, we turn it down rather than take it on.
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It starts with a measurement, not a proposal. You see in black and white which AI answers name your company and which do not, with a date and a question set.
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Instead of a list of everything, you get an order. Every step has a result you can verify yourself, including without us.
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Your offer and your positioning stay yours. We tell you what stands in the way of visibility and take on the technical part of it.
Next step
One conversation, 30 minutes, no sales pressure. You leave with an honest read on whether this is worth the effort for you.