Summary In today's episode, I walk through a practical methodology for building your own dataset of Amazon sellers when no public source exists. Here's what this means for you. You gain a reproducible framework for identifying e-commerce sellers using web technology signals, saving you from relying on unvetted vendor lists. You'll also learn these concepts:…
We read businesses, marketers, CMOs, and authors writing about marketing strategy, about which strategies are working and which aren’t. But have we ever asked, “what is the purpose of marketing strategy?” Defining Marketing Strategy For the purposes of this article, let’s define strategy using the standard definition in Leading Innovation: Strategy is the menu. Tactics are…
Jessica asks, “what should be the interview questions when hiring a good data scientist?” The answer to this question depends heavily on how fluent you are in the language of data science, in order to sniff out unqualified candidates. Focus a lot on scenarios, and work with a non-competitive data scientist to build out questions…
Summary In today's episode, I break down how to design interview questions that reveal whether a data science candidate has real experience or just crash-course knowledge. Here's what this means for you. You'll learn to spot the difference between a candidate who can recite answers and one who actually understands what will go wrong in…
Kim asks, “What advice would you give to persuade my CEO NOT to buy an email list?” Buying a third party list is a bad idea in today’s environment because your deliverability is contingent on how many people report your email as junk. The moment you use a third party list, your reputation gets trashed…
Summary In today's episode, I walk through why buying an email list is one of the worst moves a marketing team can make, from legal liability to permanent domain blacklisting. Here's what this means for you. You'll discover the fastest path to a healthy, profitable email list is content so compelling people volunteer their addresses…
Jessica asks, “What is most common scientific method to analyze data, so when I (business person) is working with marketing data scientists I can have a intelligent conversation?” To my knowledge, there is only one scientific method. What matters for marketing data science (and data science in general) is the implementation – particularly at the…
Summary In today's episode, I break down how the scientific method applies to data science and why the problem definition phase matters far more than most people realize. Here's what this means for you. You'll learn why rushing past exploration and straight to a hypothesis almost always leads to flawed experiments and wasted effort. You'll…
Alessandra asks, “The customer is getting leads organically in the same number as before the start of the ads campaign, so the few conversions (1 month running) makes him think it’s not worthwhile to advertise. My thoughts are going in the direction of explaining the value of impressions on their own, the values of clicks…
