Part II of Successful Data Mining: 80% Data Prep, 20% Modeling & Assesment
At a high level, there are two types of data — primary and secondary.
Primary data are data that the customer has directly provided (e.g., from product registrations, web-page profile registrations, surveys, etc.) and data that you have collected directly from customer interactions, like purchases. Secondary data is data that is acquired from another indirect source. These data elements can include demographic (for B2C companies) or firmographics (for B2B companies) elements. Some of these data elements may be specific to your customer or inferred. An example of inferred is to assume that a specific customer has the same household income as that represented by the average of all households at the zip code or zip+4 level – a level provided by the U.S. Census.
The most important data elements are those related to prior transactions (primary data). These data almost always give the most lift to predictive models. Secondary data is not always found to be important in terms of explanatory power. However, they can be very helpful when building customer acquisition models and for profiling customer segments to help deliver the right message.
So, if you want to use data mining to increase your marketing ROI, start collecting these data at the customer level today!
Next posting will address, “How much Data Do I Need”, or “How Many Customer Records Do I Need to Have Confidence in My Models?”
Filed under: Data Mining, Marketing Automation, Predictive Analytics
