Summary In today's episode, I break down why some companies charge for data you can get free from the government and how to think about paying for convenience. Here's what this means for you. You'll get a clear ROI framework that helps you decide between spending your time processing raw data or spending money to…
Summary In today's episode, I explore what content is missing in the analytics space by walking through the "who, what, where, when, why, and how" framework to identify the biggest gaps. Here's what this means for you. You'll discover that the most overlooked areas are retention analytics and demystifying who should be doing analytics, which…
Summary In today's episode, I break down why most marketing technology problems aren't actually technology problems at all, and I introduce the 5P framework for diagnosing the real issues. Here's what this means for you. You stop blaming tools and start examining the data, people, and processes that truly drive marketing performance. You'll also learn…
Summary In today's episode, I break down the biggest data trends shaping marketing teams over the next two to five years, from privacy laws like California's CPRA to the rise of artificial intelligence in marketing workflows. Here's what this means for you. You'll walk away knowing which data to keep, which to discard, and how…
Summary In today's episode, I break down why bad data is the biggest pain point in data preparation and why no tool can fully fix it. Here's what this means for you. You'll realize that clean data is the foundation for any accurate reporting, forecasting, or machine learning effort. You'll also learn these concepts: how…
Summary In today's episode, I walk through a simple Google Data Studio exercise for diagnosing dirty data in your Google Analytics account. Here's what this means for you. You'll gain a fast, no-code method to surface the attribution-breaking problems hiding in your traffic sources. You'll also learn these concepts: why a source/medium table exposes your…
Ashlee asks, “What are some strategies for increasing first-party data?” Let’s recall that first-party data is data given to us by prospective customers, and comes in two flavors. Passive first-party data is data collected by tools like Google Analytics and our email marketing software – when a user does something, these tools measure the actions…
One of the truths we don’t talk about nearly enough in marketing data science is the need to blend data. There are very few data sources that are a single source of truth by themselves, that need no augmentation or supplementation to provide maximum value. Even our most favorite, most used tools like Google Analytics,…
Kate asks, “Why do you have such a fixation on data?” This is a more interesting, philosophical question than it might first appear. Yes, I emphasize data a great deal in my work; my company, Trust Insights, is rooted in data-driven marketing. But where did this all come from? A significant part comes from my…
A few years ago, there was a big movement called Quantified Self, in which we would apply principles of analytics and data science to our lives with fitness trackers and other apps that would help quantify how we were living. For a variety of reasons – mainly overhead – that movement never really took off.…
