Competitive Analysis
Competitive analysis is the systematic examination of your competitors in order to assess their strengths, weaknesses, and visibility. In the context of AI visibility, you check which providers are named and recommended by AI assistants like ChatGPT or Perplexity, how often, and in what context. This lets you see where you stand in AI answers and where the gaps are.
Why competitive analysis matters for AI visibility
AI assistants usually deliver their users only a handful of recommendations instead of ten blue links like a classic search engine. Whoever is not named practically does not exist for the person asking. That is exactly why it is not enough to measure your own visibility. You have to know who gets recommended instead and why. Competitive analysis shows you which providers the AI treats as a reference, which content these providers offer, and which sources the AI cites. From this you can deduce whether you are behind in content, in technology, or in perception. Without this comparison, you optimize blindly and never know whether your gap is large or just a matter of a few details.
How a competitive analysis works
First, you define which questions you want to be visible for, for example "Which tax advisor for freelancers in Cologne?". Then you pose these questions to several AI assistants and note which names come up, in what order, and with what wording. Next, you identify the recurring competitors. For these, you look at which websites, reviews, and specialist articles the AI uses as a source. You compare the structure, currency, and clarity of their content with your own. In the end you have a sober list: where are they named and you are not, which topics do they cover, and which verifiable facts make them easy to cite for the AI.
Common mistakes in competitive analysis
A widespread mistake is looking only at the obvious market leaders. In AI answers, smaller providers that deliver well-structured content often appear, while big brands are missing. Second, many rely on a single query. AI answers fluctuate, so you need several runs and several assistants for a robust picture. Third, people often count only who is named, but not in what tone. A mention as a cautionary example is something different from a recommendation. Fourth, some confuse a snapshot with a trend. Without repeated measurement over weeks, you can't tell whether your gap is widening or narrowing. Treat the analysis as an ongoing process, not a one-time project.
Relevance to AI recommendations and GEO
Competitive analysis is the foundation for Generative Engine Optimization, that is, the targeted optimization of your content for AI answers. Only once you know why the AI prefers your competitors can you counteract it. Often it comes down to clear, fact-rich pages, consistent details across many sources, or good accessibility for AI crawlers. The analysis connects directly with your visibility score and your share of voice, that is, your share of all mentions. It provides the comparison values that make these metrics meaningful in the first place. In short: competitive analysis turns a vague feeling of being behind into a concrete to-do list.
Example
A small online driving school wonders why hardly any sign-ups come through AI recommendations. It asks ChatGPT, Gemini, and Perplexity five times each about the best online driving schools in Germany. Three competitors appear almost every time, its own brand never. On examination it turns out: the named providers have structured FAQ pages with prices, process, and pass rates, while its own page contains only advertising copy. The driving school adds clear facts and, after a few weeks, is included in AI answers for the first time.
Common questions
How often should I run a competitive analysis for AI visibility?
At least monthly, better ongoing. AI answers change with new model versions and new content from your competitors. A one-time analysis quickly becomes outdated; repeated measurements show you real trends instead of random moments.
How does AI competitive analysis differ from classic SEO competitor analysis?
In SEO you compare rankings, keywords, and backlinks in search results. In AI analysis, what counts is who the assistant names and recommends in its answer. It is less about placements than about mentions, tone, and cited sources.