Summary In today's episode, I break down the five-tier hierarchy of analytics and explain exactly where today's tools fall short and how a data scientist plugs those gaps. Here's what this means for you. You discover why the dashboards in Google Analytics only deliver the bottom rung of what analytics can truly offer, and why…
Monina asks, “Not every marketer can (or wants to) be the data scientist for their org. What should we look for when hiring an FTE or partner?” This is a critical question because there’s a significant shortage of trained data scientists. Those who exist and are qualified are “reassuringly expensive”. Thus, be on the lookout…
Summary In today's episode, I break down how to hire a qualified data scientist or agency partner when your organization lacks that expertise. Here's what this means for you. You gain a practical framework for evaluating candidates across six critical skill areas so you avoid costly mis-hires in a notoriously tight talent market. You'll also…
Monina asks, “What steps make up a data science lifecycle? Where do you begin?” The short answer to this question is to define the problem and hypothesis, prepare your data, explore your data, test your hypothesis, build a model, validate the model, and then deploy and observe. Each stage is composed of multiple sub-steps. Watch…
Summary In today's episode, I walk through every stage of the data science lifecycle and explain why each step matters. Here's what this means for you. You get a clear roadmap for turning raw questions into tested, deployable models you can defend. You'll also learn these concepts: why defining the problem and stating a provable…
Monina asks, “What tools are useful to help marketers dig deep into their organization’s data?” The answer to this question depends on the level of skill a marketer has in data science, specifically the technical and statistical skillsets. I’d put the available tools in categories of beginner, intermediate, and advanced. Beginner tools help marketers extract…
Summary In today's episode, I answer a viewer's question about the best tools for marketers who want to dig deep into their organization's data, walking through beginner, intermediate, and advanced options. Here's what this means for you. You'll see why matching tools to your skill level matters far more than chasing the fanciest software, because…
Monina asks, “How can marketers adopt a data science mindset? Outside of hard, analytical skills, what soft skills should marketers possess?” Data science is exactly what it sounds like: performing science with data. The soft skills which make for a great scientist thus transfer to a data scientist and any marketer who wants to adopt…
Summary In today's episode, I break down the seven essential soft skills marketers need to adopt a data science mindset and use data more effectively. Here's what this means for you. You'll discover that traits like curiosity and resilience actually form the foundation that drives you to develop analytical skills, not the other way around.…
Monina asks, “What kind of analytics can data science uncover?” This is an interestingly worded question. Analytics are fundamentally about explaining what happened, the what in your data. Very often, as stakeholders we also want to know what’s relevant (data overload) and then why (insights). That’s where data science can help, especially with understanding what’s…
