Category: Marketing Data Science

  • How to Get Better AI Results: The Secret Behind Precise, Step-by-Step Prompts

    Generative AI needs to talk. This is generally accepted advice – that to get the best results out of large language models like the ones that power ChatGPT, they need to talk things out. Of the dozens of prompt engineering techniques that exist, moer than half fall into the category of chain of thought, which…

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  • **”Generative AI vs. Classical AI: Why Using the Wrong Type Can Lead to Disaster”**

    Katie shared this chart from McKinsey this morning, which is… inaccurate. Here’s why. There are three major forms of AI – regression, classification, and generative. We’ve had the first two for decades. You’ve experienced classification AI since the late 1990s when intelligent spam filters first appears to classify email as spam or not. You’ve experienced…

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  • Unlock AI’s Potential: 5 Things You Couldn’t Do Before (That Your Competitors Aren’t Doing)

    What couldn’t you do before that AI enables now? As we close out 2024 and start looking at the road ahead, I have a thought exercise for you, one I’m doing myself. What couldn’t you do before that AI enables you to do now? What was beyond your reach, because of resources or skill? Everyone…

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  • Unlock the Power of MCP: How to Build and Monetize Custom AI Tools for ChatGPT, Claude & More

    MCP is a GPT you control. A lot of people have had a lot to say about Model Context Protocol, or MCP. It’s one of the hot topics in generative AI right now, but it’s also absurdly opaque to a lot of folks. Here’s what it is and how it works. Functionally, MCP is a…

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  • Mind Readings: Treat Reasoning AI Models Like New Managers

    Summary In today's episode, I explain why reasoning models like OpenAI's o1, o3, DeepSeek R1, and Gemini 2 Flash Thinking behave like junior managers rather than forgetful interns, and how to delegate to them effectively using the Trust Insights Prism framework. Here's what this means for you. You will get dramatically better results by treating…

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  • Mind Readings: How to Do a Content Audit With Generative AI, Part 2 of 4

    Summary In today's episode, I walk through using generative AI to build a repeatable Python analysis that scores newsletter issues by their correlation with conversions. Here's what this means for you. You get a concrete method for turning messy, multi-source engagement data into a single weighted score that ranks your top and bottom performing content.…

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  • You Ask, I Answer: Why is Marketing Data Rich but Insight Poor?

    In today’s episode, you’ll explore the intriguing paradox of why marketers, despite having access to vast amounts of data, often struggle to extract meaningful insights. You’ll discover the crucial role that well-defined questions play in guiding data analysis and learn why simply having data isn’t enough. I’ll share a practical framework that helps you transform…

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  • You Ask, I Answer: Why is Marketing Data Rich but Insight Poor?

    Summary In today's episode, I explore why marketers sit on piles of data yet rarely surface meaningful insights. Here's what this means for you. You'll discover that defining clear questions before touching your data is the missing link between raw numbers and real answers. You'll also learn these concepts: how a kitchen analogy maps data…

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  • Mind Readings: The Gold Standard of Marketing Attribution

    In today’s episode, you’ll discover the gold standard of attribution for marketers in an age of increasing privacy concerns. You’ll learn why traditional tracking methods are becoming less reliable and explore a powerful, yet often overlooked, alternative: simply asking your audience how they found you. I’ll explain how this straightforward approach, combined with the capabilities…

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  • Uplift Modeling: Unearthing the ROI Gold in Your Offline Marketing

    Disclosure: This post was written by generative AI using Google Gemini 1.5 Pro, as demonstrated in this issue of my newsletter. Uplift Modeling: Unearthing the ROI Gold in Your Offline Marketing You love data. I love data. We all love data! Numbers tell a story, but sometimes those stories get lost in the noise –…

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