Jen asks, “How can brands find out which kind of Facebook Ads work best for them?” One way to approach this problem is with large scale data analysis. In your industry, gather up a list of Facebook Pages and use any service which can address the Facebook API like Facebook’s Crowdtangle, then filter to only…
Wanda asks, “How do I know if my A/B test is statistically significant?” Statistical significance requires understanding two important things: first, is there a difference that’s meaningful (as opposed to random noise) in your results, and second, is your result set large enough? Watch the video for a short walkthrough. Can’t see anything? Watch it…
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…
Erika asks, “What are your tips and best practices for topic and keyword research in content marketing?” It depends on the size of the content and how much domain expertise you have. Scale your research efforts to the level of risk the content poses and how important it is that you get it right. Can’t…
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…
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…
I had a chance to sit down with Jason Falls to chat about analytics, data science, and AI. Catch up with us over 35 minutes as we talk about what goes wrong with influencer marketing, why marketers should be cautious with AI, and the top mistake everyone makes with Google Analytics. Can’t see anything? Watch…
Steve asks, “I’m looking for a dataset of companies that are actively selling on Amazon. How would you as a marketing data scientist approach this problem?” That’s an interesting question. To my knowledge, there aren’t publicly available, free datasets of this sort (though please leave a link in the comments if you know one), so…
