Getting Started With Data-Driven and Database Marketing
If you’ve covered this base, then you’d be surprised to know how few brands have the data in place and organized. The biggest reason for this is the data is often tied up in an “IT” database, where it’s logged by the POS, website CMS or another system.
Moreover if you examined a transaction file, you would likely see many tens of thousands of rows of transactions, many of which are anonymous given the process in which they were captured. This creates some challenges. Without PII, we can’t associate the transactions to the customer. Even when we have the customer PII, the data is virtually never “clean” enough out of the box to just match on the name ― “John,” “Jon,” “Jack,” and “J.” are not the same to a database or POS system ― but they have to be in a comprehensive marketing database.
Data processing matching programs repair, cleanse and transform transaction data from a set of “raw transaction data” into a comprehensive buying history by customer.
For now, let’s assume we’ve completed this data transformation phase and have repaired various missing fields, and solved for the typical data capture problems that we should expect. We’re on to doing something with our newly minted customer data file. First, we can get a clean customer count! We now know we have 100,000 or 10 million customers.
Now we can begin to leverage the timing of those transactions. We’ll know not just how many units we sold, but who we’ve sold them to, and what else and when those customers bought. We can derive the timing of those purchases and begin to mine for statistical significance and opportunity. Before we go too far with leveraging timing data, let’s take a step back and first understand the breakout of new, repeat and loyal customers, too. Our first big question of course was “How many?”