A: Companies use data-driven models to get the specific data inputs necessary to determine how to proceed with their business.
There are many types of data-driven models, and which model an organization chooses to use depends on their goals and what information they need to discover. An A/B test, for example, is a data-driven model that offers two different options. A company will run both options against their audience to see which performs better, and then use the data collected from the test to inform future content or campaign strategies.
Most product development, marketing, sales execution, and sales operations programs have one or more data-driven models that they follow as part of their methodology. When you're selecting a model, it's valuable to evaluate it against your use case to determine where it may have blind spots or may have an unacceptable level of false positives. A false positive occurs when a data point indicates that things are in a desired state when they aren't. For instance, in a home alarm system, a false positive would be a motion sensor detecting motion, when it wasn't the kind of motion you intended the alarm to warn you of. If a plant is next to a fan, the moving leaves may set off the alarm. The alarm did its job of detecting motion, but it caught a plant, not a burglar.
In digital marketing, false positives can be very costly because they skew the data in your model, which is why it's key to evaluate any model against the use case you're looking at. It’s important to determine if there's going to be noise in the data that will cause you to make the wrong conclusions, and therefore the wrong decisions.
A vital aspect to data-driven decision-making is inspecting the data. You need to understand not just the actual information the data is telling you, but what its capabilities are. There are often limitations to what information can be gleaned from a specific data source. When evaluating a customer’s journey, for example, you might be trying to find which touchpoints had the largest impact on their decision to convert. With SEO and SEM, however, you can over-allocate credit to those interactions, instead of some other point that was really the ultimate conversion event.