Perspectives Matter in Analytics
Even that relatively simple “who” part of prediction calls for some debate, with all kinds of data being pumped out every second. Some marketers employ data and toolsets based on availability and price alone, but let us step back for a second and look at it from a different perspective.
Hypothetically speaking, let’s assume we as marketers get to choose one superpower to predict who is more likely to buy your product at a mall, so that you can address your prospects properly (i.e., by delivering personalized messages properly). Your choices are:
- You get to install a camera on everyone’s shoulder at the entrance of the mall
- You get to have everyone’s past transaction history on an SKU level (who, when, for how much and for what product)
The choice behind Door No. 1 offers what we generally call clickstream data, which falls into the realm of Big Data. It will record literally every move that everyone makes with a time stamp. The second choice is good old transaction data on a product level, and you may call it small data; though in this day and age, there is nothing so small about it. It is just relatively smaller in size in comparison to No. 1. Now, if your goal is to design the mall to optimize traffic patterns for sales, you surely need to pick No. 1. If your goal were to predict who is more likely to buy your product, I would definitely go with No. 2. Yes, some lady may be looking at shoes very frequently, but will she really make a purchase in that category? What does her personal transaction history say?
In reality, we may have to work just with No. 1, but if I had a choice in this hypothetical situation, I would opt for transaction data any time. In my co-op data business days, I looked through about 50 model documents per day for more than six years, and I have seen the predictive power of transaction data firsthand. If you can achieve accurate answers with smaller sets of data, why would you pick any reroute?
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 firstname.lastname@example.org.