Comparing AI Visibility Providers: A Practical Framework

Three AI visibility proposals often read remarkably alike - the same buzzwords, the same promises, similar prices. The difference doesn't show up on the page, it shows up in the conversation afterwards, when concrete questions demand concrete answers.

Three provider types shaping the market today

The market for AI visibility roughly splits into three groups, and that split isn't a judgement on any individual company - it describes patterns that show up repeatedly in conversations. The first group is SEO agencies that added the word GEO or AEO to an existing package while largely staying the same underneath. The second is technically fluent specialists who understand the mechanics precisely but sometimes work without much regard for industry or company size. The third combines both: technical understanding with an offer sized to fit an SME's budget and scale.

That split is no reason to write off the first group - solid SEO work remains the prerequisite for any AI visibility, and some of these agencies are actively building GEO knowledge right now. What matters is that you, as the buyer, know which group a specific proposal actually belongs to, rather than trusting its own description of itself.

The scorecard: questions every provider has to answer

• Show me a real AI answer where an existing client is named
• Which schema.org types do you specifically use for businesses like mine, and why those
• What does your monitoring look like - which questions, which systems, which cadence
• What exactly changes when an AI model updates, and how do you respond to that
• Which part of your service do you actually control, and which part don't you

The last question is the most important one in the whole conversation. A serious provider states the limit of its own control unprompted, without you having to ask. A provider who doesn't know that limit, or hides it, has either not understood the mechanics behind AI visibility or is knowingly selling more than it can deliver.

Laying proposals side by side

This scorecard doesn't replace an actual conversation, but it gives you a structure to actually lay several proposals side by side instead of comparing them on gut feeling alone.

What a realistic price comparison means

Judging a proposal on price alone rarely leads to a good decision, because the range between serious providers is wide and depends on scope, industry and how deep the observation goes. We break down realistic market ranges for one-off setup and ongoing support, with concrete figures, in our article on AI visibility cost. As a rule of thumb, though: a proposal noticeably below those ranges for ongoing support rarely replaces real editorial work, because preparing facts, building structures and watching results cannot be automated like a software subscription.

Concrete steps for the next 90 days

• Days 1-30: request three proposals, use the scorecard in this article as your interview guide, and document the answers
• Days 31-60: verify references concretely, sign a contract with clearly named deliverables and monitoring as a fixed component
• Days 61-90: discuss the first documented samples with your chosen provider and check the agreed cadence

Conclusion

A good comparison between AI visibility providers doesn't come from gathering more proposals, it comes from asking the same hard questions of every one of them - and from ruling out any provider who guarantees results on a model it does not control. What answer engine optimisation actually covers as its own discipline is in our article AEO Agencies in Germany; how a ChatGPT-specific strategy differs from other systems is in ChatGPT Optimisation Services. How to measure your own AI visibility independently of any provider is in Measuring AI Visibility. For an informal second opinion on a proposal you've received, feel free to get in touch.