Gumshoe Blog

Insights on AI visibility, GEO, and the future of brand discovery.

How Much Data Do You Need to Measure AI Visibility with Confidence?

Recent research from SparkToro and Gumshoe examined how consistent AI tools are when recommending brands and products. We found that individual AI responses are highly variable (you’ll rarely see the same answers twice), but the frequency with which a brand appears across many queries converges to a stable signal. Visibility, measured as the proportion of responses in which a brand appears, behaves like a well-defined probability that can be estimated with standard statistical tools.

Gumshoe AI Manual: Mastering Visibility & Growth in the AI Search Era

In the age of AI-driven search, marketers face a new kind of visibility challenge. Large language models (LLMs) like ChatGPT, Google’s Gemini, and Perplexity are answering your customers’ questions directly – often citing sources and making brand recommendations. Agency owners, marketing leaders, and SEO leads are quickly discovering that traditional SEO strategies aren’t enough. You might be ranking on Google, but what happens when a prospect asks an AI assistant about the “best solution” in your domain?

When Content Is Goliath and Algorithm Is David: What This New Research Reveals About Generative Search Optimization

A new research paper from the University of Washington has uncovered something counterintuitive about how generative search engines select content for citations. The findings challenge what many marketers assume about AI search optimization and reveal a surprising opportunity for brands willing to adapt their content strategy.

How APIs Unlock Better Insights Into AI Search Visibility

A recent study from SurferSEO compared API responses to scraped web interface results across 1,000 ChatGPT prompts. They found the overlap between brands mentioned using the two methods was 24%. Their conclusion: “Monitoring responses from API as a proxy for your AI visibility is totally wrong.”

At Gumshoe, we read that study with interest. The data is real, but the conclusion misses the point.