Our good friends at DataLab Data Solutions are back with another thoughtful article on data. This time, COO David Flam explains the necessity of combining performance data with external data to drive optimal results.
Few will argue that “big data” is perhaps the most overused term in business today. It’s also most likely the least understood.
“Without big data, you are blind and deaf in the middle of a freeway,” noted Geoffrey Moore, the oft quoted marketing theorist.
So what exactly does that mean, especially in the context of effective direct marketing? Everyone agrees there is a ton of meaningful consumer information that can be leveraged today for targeting. Beyond that, there is tremendous disagreement, as evidenced by the disparate approaches taken today by the country’s largest B to C marketers.
In the years that DataLab and IWCO Direct have partnered to provide comprehensive solutions to our mutual clients, we have encountered dozens of marketing programs undoubtedly blessed with rich levels of historical performance data – and some access to external data – but with numerous competing theories about what do to with it all. “Blind and deaf in the middle of the freeway” is a little extreme, but on more than one occasion it has felt like that description wasn’t too far off.
Internal performance data often comes in the form of mail history. It’s a critical pillar for any effective program development. What’s different today, more than ever before, is the strength of its companion column: external data. Just how much is out there? Today, DataLab processes and manages more than 15 national consumer files, which on the aggregate provide more than 5,000 attributes on every U.S. consumer, or roughly 1.1 trillion data points. Without any context or experience, it would all be useless, but understanding the basic starting principles will provide any marketer with an effective start.
Where to Begin When Combining Performance Data and External Data?
We often hear clients ask whether they should use “credit” or “demo” for name selections. Many believe that credit is better. While credit data is more effective than demographic data in many environments, making credit vs. demo the first decision is not the strongest strategy. Data should be thought of as lending intelligence toward either a specific behavior, or, a particular condition. Whether we care about one more than the other is really driven by the product being sold.
Generally, the more ubiquitous the product, the more behavior becomes relevant. An automobile insurer should care more about identifying consumers actually in the market for car insurance than almost any other attribute. True, a carrier will want consumers with certain attributes, such as being a car driver, and for some, a specific credit threshold is required. But for a ubiquitous product, most consumers will by definition meet the necessary conditions. In this particular circumstance, the most relevant performing data attribute will be insurance inquiries – showing that a consumer is shopping – and thus identifying the very behavior that the carrier is seeking to target. In this example the attribute happened to be credit derived, but note that credit wasn’t the start of the hypothesis. It emerged as the most appropriate choice as the means to identify a specific behavior.
The other end of the spectrum might be targeting consumers for consumption of “niche” products, such as high-end travel or wealth management services. Unlike purchasing car insurance, not all consumers will need a villa in Chamonix this winter, or sophisticated assistance managing multi-million dollar portfolios. These oversimplified examples are screaming “condition” far more than “behavior.” While it would be nice to know when that expensive vacation urge is present – and there are indeed seasonality factors that can be implemented into any campaign – these products rely heavily on conditions: primarily, the presence of accessible cashflow in the travel example, and actual wealth in the portfolio management example. Here again, the assets (no pun intended) are in fact available and far more sophisticated than they’ve ever been. Suffice it to say, it’s not just income estimates anymore.
The improvements in – and depth of – external data assets are among the most energizing developments in database marketing today. Today we discussed two or three attributes of more than 5,000 that are available. Imagine being able to take targeted conditions or behaviors to even deeper levels of sophistication – for virtually any product or solution. The attributes, analytic skill and power are out there. Not taking advantage of them is risking being lost in the middle of the freeway.
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