A ‘Moneyball’ Approach to Marketing and Big Data
Remember the movie (and book) "Moneyball"? The story depicts baseball's budget-challenged Oakland A's. Outmuscled by richer teams when it came to signing the most coveted players, the A's changed the game by pioneering a new approach to data.
That probably rings some bells for marketers. Marketing stands at a similar crossroads as it grapples with the right approach to big data.
In baseball, conventional wisdom held that to win games, you need to field players who deliver big numbers for home runs, RBIs, batting average and other traditional metrics. Those players are expensive, however. A's General Manager Billy Beane saw that he'd be unable to keep up if he played by rich-team rules. Ahead of the 2002 season, Beane zeroed in on then-peripheral metrics — chiefly on-base percentage — to unearth players who produced more than their modest price tags would indicate. What could an entire team of undervalued performers do?
The 2002 A's won a league-best 103 games — as many as the free-spending New York Yankees. Now data drives baseball.
In marketing, spending big money for TV and other "heavy hitters" was common sense for 50 years. Marketers today have many more ways to "get on base" and connect with customers, yet old-school mind-sets persist. And while at first glance big data promises revolutionary transformation, in practice it can be overwhelming. Marketers are actually making fewer data-driven decisions.
Inspired by the Oakland A's intentional focus on a few meaningful metrics, you can begin to optimize your marketing and avoid getting stuck in the data weeds.
Workhorses over bling
The just-released catcher who could barely throw wasn't a hot commodity, but he had a history of getting on base. The A's picked him up, converted him to first base, and he delivered. In the "Moneyball" mind-set , you don't just emphasize TV and high-concept campaigns, you focus on what drives results.