Sheri asks, “What is AI good at? What kinds of problems is it good at solving?” There are two sets of answers to this question. First, we need to know what AI delivers as an outcome: Acceleration of results Accuracy of results Alleviation of repetitive work Second, we look to understanding what we know and…
Kevin asks, “How do we standardize metrics and measurement, especially when different parts of the company do things differently?” Great and very common question. The answer is, unsurprisingly, a framework: Goal alignment Exploratory data analysis Model creation Model validation Model deployment Adoption, training, and compliance Measurement of compliance Refinement and improvement If this sounds familiar,…
Magdalena asks, “Can you share two or three good practices of using data in tracking our efforts?” Great and important question. Many marketers don’t have, for one reason or another, a solid understanding or past experience in statistics. Let’s look at a few of the most basic rules that apply, especially when we’re digging into…
Magdalena asks, “What are your favorite tools to track data and which one are you using on daily basis?” I’m a huge fan of source data, so whenever a practical API is available, I’ll use it. For social media, I use Brand24 and Crowdtangle almost daily. For owned digital, Google Analytics is my one source…
Magdalena asks, “How much should our actions depend on what the numbers and indicators show us? Is there any space for what we feel works well, even if after a month or two, the results don’t prove that?” There’s plenty of room. First, consider the data. Data must meet the 6C Framework for Useful Data:…
Magdalena asks, “From your point of view, what are the main indicators of performance in marketing?” It depends. What is the goal of your marketing? That’s what the key performance indicator is. I define KPI as, if this number goes to zero (or the maximum bad state), you get fired. So for every company, and…
Kevin asks, “What’s the difference between unrefined and refined data?” As part of a larger discussion about metrics in marketing, Kevin’s question came up in reference to the importance of data. Unrefined data is as useful to business as crude oil is to a car – which is to say, it isn’t useful at all.…
One of the consequences of machine learning is that our data is part of a mosaic of data used for training. We’ve voluntarily given companies enormous amounts of information and while, historically, they’ve been really bad at using it in any meaningful way, that will change. Companies who want to get ahead of the curve…
Kerry asks, “How do you choose data science software if you’re not already a data science expert? My company is evaluating some vendors and I’m not sure what to ask.” By definition, a data science platform should be flexible enough and robust enough to fully embrace the classical scientific method. Be VERY suspicious of anyone…
Yariv asks, “What are the differences between data analytics, data science, business analytics, and business intelligence?” It depends on who you ask. Thanks to consulting and marketing, these terms all have varying degrees of overlaps, and companies which make their money on clarifying terms like this – consulting shops – often have conflicting definitions. You’ll…
