Freeform Data Are Not Exactly Free
Let's start with simple examples instead of worrying about the CIA having to comb through billions of lines of emails and phone records to determine who has the intention to blow places up. Even when we just stick to marketing applications, there are plenty of examples. Product descriptions, product labels, service categories, offer types, channels, data sources, Web pages, surveys or business titles are often in freeform (yes, surveys, too), and they are definitely not ready to be used in advanced analytics. It is not just having to dissect everyone's tweets and determine their sentiments toward certain products. Useful data are hidden in the most obvious and immediate places. And in this world of uncategorized data, they are the lowest-hanging fruits and the most potent predictors in modeling and analytics.
Take, for instance, a simple data field called "Professional Title." If you have a stack of business cards in your drawer, pull them out and see if you can find any two titles that are completely identical to each other. And no, "SVP, Finance" is not the same as "Sr. Vice President/Chief Finance Officer." While you as a human being may assume that those two titles mean about the same level and function, try to explain that to your computer. It is common to find over tens of thousands of variations of business titles in a relatively small B-to-B list. As a result, even the most seasoned marketers often give up on that field, and only use them to address the contact.
To use it in analytics and reporting for marketing and sales, let us try to break the professional title field into two separate variables: one for the ranks within an organization, and the other by functionality. As I mentioned, deciding "what to define" is the first step. Then, set up the details of the final categories and rules regarding what should go into which category.
Stephen H. Yu is a world-class database marketer. He has a proven track record in comprehensive strategic planning and tactical execution, effectively bridging the gap between the marketing and technology world with a balanced view obtained from more than 30 years of experience in best practices of database marketing. Currently, Yu is president and chief consultant at Willow Data Strategy. Previously, he was the head of analytics and insights at eClerx, and VP, Data Strategy & Analytics at Infogroup. Prior to that, Yu was the founding CTO of I-Behavior Inc., which pioneered the use of SKU-level behavioral data. “As a long-time data player with plenty of battle experiences, I would like to share my thoughts and knowledge that I obtained from being a bridge person between the marketing world and the technology world. In the end, data and analytics are just tools for decision-makers; let’s think about what we should be (or shouldn’t be) doing with them first. And the tools must be wielded properly to meet the goals, so let me share some useful tricks in database design, data refinement process and analytics.” Reach him at email@example.com.