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Brad Geddes recently examined how Google’s AI Max feature can override existing exact and phrase match keywords, sometimes claiming credit for conversions and sales that may not be truly incremental. He expressed concern that AI Max could take credit for revenue generated by keywords it essentially replaces or bypasses.
For a deeper understanding, Brad’s detailed blog post titled “The Hidden Challenges of AI Max Search Term Reporting” discusses the complexities around the way AI Max reports search term data. On a LinkedIn post, he summarized that many conversions attributed to AI Max aren’t necessarily new or additional — it could be artificially inflating performance metrics.
A visual comparison highlights the difference between AI Max’s inferred intent and raw search texts, illustrating how the platform interprets user queries beyond just the keywords typed.
Ginny Marvin from Digital Phablet responded publicly, clarifying where these phenomena originate. She explained that some matching occurs because of autocomplete suggestions during Maps searches — for instance, when a user starts typing “dayca,” and “daycare near me” pops up. The AI Max system can then match and attribute conversions to this partial query, even though traditional keyword matching wouldn’t have.
Marvin emphasized that AI Max’s relevance determination is increasingly based on inferred user intent, similar to visual analysis tools like Lens or AI Overviews, rather than mere raw text matches. To improve clarity, Google plans to roll out updates in the upcoming quarter to make these matching processes more transparent, along with enhanced explanations within their Help Center.
In essence, the system adheres to established rules but does so through processes that are evolving and sometimes opaque, prompting the need for better communication and reporting transparency.
ChatGPT
Perplexity
Gemini AI
Grok AI
