Summary In today's episode, I walk through a practical framework for measuring AI visibility across your marketing analytics stack, including what you cannot measure and what you can. Here's what this means for you. You gain a tiered approach to tracking how AI tools interact with your brand, so you can stop chasing unreliable promises…
Summary In today's episode, I tackle Cecil's question about the best strategies for managing LLM context window decay and token limits during long-running analytical sessions. Here's what this means for you. You'll discover that offloading work to deterministic tools and persistent notes lets you squeeze dramatically more value out of any LLM you use. You'll…
Summary In today's episode, I walk through what LLMs.txt is, why Google now considers it part of site health, and how to build one using real analytics data. Here's what this means for you. You learn that LLMs.txt does not boost AI visibility but serves as a curated briefing document that helps AI agents navigate…
Summary In today's episode, I walk through how to analyze whether your brand has a GEO problem by examining search data and content performance. Here's what this means for you. You gain a practical framework for measuring whether your content efforts actually translate into AI search visibility using tools you likely already have. You'll also…
Summary In today's episode, I explain the most reliable method for tracking AI tool traffic attribution. Here's what this means for you. You can identify exactly which AI models drive your business growth by using simple, direct human feedback. You'll also learn these concepts: why open-ended questions outperform unreliable analytics tools, how to leverage generative…
Summary In today's episode, I walk through how to analyze freeform survey data with generative AI using both low-tech spreadsheet solutions and high-tech coding tools. Here's what this means for you. You'll see how unstructured responses can become a content calendar, a strategic plan, and even a sales pipeline without forcing respondents into outdated drop-down…
Summary In today's episode, I walk through eight real-world data horror stories from marketers and map each one to the Six C's Data Quality Framework (clean, complete, comprehensive, calculable, chosen, and credible). Here's what this means for you. You walk away with a horror-story-tested approach to spotting data quality failures plus a workflow that audits…
Summary In today's episode, I walk through the AI-ready data quality audit, covering the three levels of data quality assessment, the 6C Data Quality Audit Framework, and why AI systems fail without high-quality data. Here's what this means for you. You'll gain a practical diagnostic approach to catch small data issues before they compound into…
Almost Timely News: 🗞️ Using AI for Analytics (2025-09-21) :: View in Browser The Big Plug 🇬🇧 There are only 4 seats left for my full day workshop in London, England, on 31 October! 👁️ Register for our new online course, the AI-Ready Strategist, now available! Content Authenticity Statement 100% of this week’s newsletter was…
Summary In today's episode, I explain how to integrate generative AI with various analytics tools beyond Google Analytics. Here's what this means for you. You can harness the power of any data source with an API to automate your insights and decision-making. You'll also learn these concepts: why generative AI struggles with direct math, how…
