Summary In today's episode, I walk through how to determine whether your A/B test results are truly meaningful or simply random chance. Here's what this means for you. You gain a clear two-step framework for validating any test before making business decisions on it. You'll also learn these concepts: how a proportion test reveals whether…
Summary In today's episode, I walk through exploring a brand-new COVID-19 behavioral dataset from Imperial College London and YouGov covering 29 countries. Here's what this means for you. You gain a repeatable workflow for opening an unfamiliar dataset and pulling out early insights without getting overwhelmed. You'll also learn these concepts: why the codebook is…
Dasha asks, “I want to take some classes on analytics and visualization skills – what would you recommend?” I’d start by learning the principles of data visualization first. Edward Tufte’s book, The Visualization of Quantitative Information, is the classic textbook to start with. Then look at Data Studio’s introductory course, followed by Microsoft’s free EdX…
Summary In today's episode, I walk through how to scrape fanfiction data from Archive of Our Own and use IBM Watson AutoAI to predict what drives story popularity. Here's what this means for you. You'll see how exploratory data analysis turns messy scraped data into a testable content marketing hypothesis. You'll also learn these concepts:…
Summary In today's episode, I explain two efficient ways to find online groups targeted at a specific audience without relying on basic demographic searches. Here's what this means for you. You'll learn how to use specialized jargon to uncover niche communities and sub-segments that standard keyword searches miss. You'll also learn these concepts: how every…
Summary In today's episode, I explore how to define a bot on Twitter by inspecting the inner workings of an open-source machine learning package rather than blindly trusting its output. Here's what this means for you. You gain the critical habit of questioning every algorithm you encounter and recognizing that software encodes opinions just as…
Jim asks, “Are there any resources that evaluate marketing platforms on the basis of how much racial and gender bias is inherent in digital ad platforms?” Not that I know of, mostly because in order to make that determination, you’d need access to the underlying data. What you can do is validate whether your particular…
Jessica asks, “What are the best tools for cleaning data?” That’s a fairly broad question. It’s heavily dependent on what the data is, but I can tell you one tool that will always be key to data cleansing no matter what data set. It’s the neural network between your ears. Can’t see anything? Watch it…
