Practical Experiments in AI Search Visibility
John Greer I recently read an interesting case study published by OtterlyAI about NOLA Marketing’s work for Single Point of Contact. It caught my attention because several parts of the process closely match conclusions we have reached independently through our own AI visibility testing. The headline results are certainly impressive. OtterlyAI reports that, over a three-month period, … Read more
I have spent a lot of time manually testing how businesses, products and websites appear in AI-generated search results. That has involved repeating the same searches, changing customer requirements, comparing competitors, checking citations and running the same question through different AI platforms. Manual testing is extremely useful because it helps you understand what you are … Read more
A business can update the information on its own website and still have older or conflicting information elsewhere online. Opening hours are a simple example. A restaurant might show one set of hours on its own website, while Google, OpenTable, TripAdvisor or a local directory shows something different. That raises an important AI visibility question: … Read more
A business owner looks at their website with knowledge a customer does not have. They already know whether the restaurant opens on Bank Holidays. They know whether children are welcome. They know whether vegan dishes are available. They know whether the refurbishment mentioned on the website has finished. They know how the booking system works. … Read more
When we started testing AI visibility, the question seemed fairly simple: Does the business appear in the AI-generated answer? Our experiments increasingly suggest that this is only the first layer. A useful assessment also needs to consider which query produced the appearance, how consistently it occurs, whether the business is mentioned or actually recommended, how … Read more
Getting cited by an AI system can feel like a clear visibility win. Your page appeared in the answer. The AI associated your page with the topic. But there is an important complication: A citation shows that the AI system associated your page with the answer. It does not prove that every nearby statement came … Read more
An Interpretation Gap occurs when the relevant facts are available, but the conclusion drawn from them misses an important condition, distinction or exception. Finding one comes down to four questions: That is the practical method. You do not need to hunt for random AI mistakes. Start with an answer that matters to a real customer, … Read more
Sometimes an AI answer is weak because important information is missing. But sometimes the information is already there. The facts exist. The sources exist. The problem is the conclusion drawn from them. We have started thinking of this as an Interpretation Gap. An Interpretation Gap occurs when the relevant facts are available, but the conclusion … Read more
If dozens of credible webpages say roughly the same thing and one page says something different, which information is an AI search engine more likely to use? At first glance, the answer seems obvious. The majority view has weight. There are more sources supporting it, more repetition around it and more evidence that the conclusion … Read more
A webpage can be: and still never be selected as a source in an AI-generated answer. We saw this clearly in a recent Google AI Mode experiment. We created a resource specifically addressing a question we had already tested, confirmed that Google had indexed it, and then repeated the original query ten times. The new … Read more