February is always the high point of the movie season. Oscar nominations are out and people are rushing to catch up on the movies they have yet to see. To date, I am 3 for 9. Not a very good average, but not bad if I were a left-handed power hitter.
Of the three I have seen, Moneyball really struck a chord. I liked it not only because I'm a life-long baseball guy and a fan of the book, but also because the message rang true for the current state of advertising.
One scene particularly resonated, in which Billy Beane (Brad Pitt), General Manager of the Oakland A's, is speaking to Paul Podesta (Jonah Hill), his assistant GM, about the idea of using sabermetrics to draft players for their team.
BILLY Why--You're not the only computer science major who likes baseball. If what you and Bill James are saying is right--
PAUL It's right.
BILLY It sounds right.
PAUL It is right.
BILLY If math isn't a theory--
PAUL It isn't.
BILLY If this is right, why isn't everybody doing it? In fact why isn't anybody doing it?
PAUL Because it's not what they were taught.
Marketers today are challenged more than ever to find new customers. The old ways of finding "prospects" – such as targeting with demographics – are growing as outmoded as thinking that a team shouldn't draft a player because his girlfriend is ugly (honest to god, it's in the movie). But it is the way we all have been taught. It's also safe and comfortable.
Is it fair to assume that our traditional ways of finding new customer prospects are akin to scouts looking at batting average, home runs or slugging percentage? Are we using old and inferior techniques to solve for new problems? Can we apply advanced statistical analysis to find new customers for brands, much as the A's found prospects in 1999? I, and many others, absolutely think so.
As with Billy Beane and his staff, marketers are now using data more than ever. In fact, we would all agree, there is more data available than we can usefully process. The mantra now has shifted from the amount of data collected to how it is utilized. How is that data put into action?
Much of that data is less valuable and actionable than we had expected. A browser that comes across a website with automotive reviews is not necessarily interested in buying a car, let alone a Ford. However, if that browser demonstrates certain web patterns, and it can be matched to other browsers who have proven to be strong Ford customers, then empirical evidence proves that it's a great "prospect" for Ford.
So, what does this new world look like? The new coda is to target browsers that will work for your brand, not your competitor's brand, not your product category, but your brand. The players that Billy Beane drafted for the A's were drafted specifically to play a role for that team. They were valued for the contribution they could make to the A's, and wouldn't have worked for another team (think Scott Hatteberg post-A's).
Our industry challenge is to find new customers, or prospects, that will engage with your company, brand, sub-brand, and even SKU. Why not pursue that challenge by finding prospects who have already shown the propensity to be interested in your brand? To put it simply, the techniques we have been using are not strong enough proxies for interest in a given brand with a specific appeal at a specific time online.
Our behaviors have changed dramatically as we have become more comfortable with this all-access anytime to anything world. Shouldn't we adjust to those new behaviors and look for new ways to find our customers?