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SmartData Collective > Analytics > Predictive Analytics > The Moneyball-itzation of Marketing
Predictive Analytics

The Moneyball-itzation of Marketing

PaulBarsch1
PaulBarsch1
7 Min Read
The Moneyball-itzation of Marketing
Illustration generated with FLUX.2 [klein 4B] via Cloudflare Workers AI.
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Oakland A’s General Manager Billy Beane started the “Moneyball Revolution,” where analytics replaced intuition as the primary method of evaluating talent and assembling a professional baseball team. And while Beane’s critics entertain some self-satisfaction from the recent mediocrity of the A’s, there’s no doubt that quantitative analysis has changed baseball forever.

Similarly in the marketing discipline, while practitioners often debate whether marketing is more “art than science”—a trend towards analytics is afoot.

Tradition and convention are certainly hallmarks of Major League Baseball. And for many years, the status quo reigned—especially in the processes used to construct a baseball team.

Using knowledge, intuition and experience to evaluate talent, field managers and scouts would scour high schools, practice fields and colleges looking for the missing pieces that could potentially elevate them to a championship. Gut decision making ruled—until Billy Beane and the Moneyball analytics revolution started.

An ESPN Magazine article shows how based on geographical location, Oakland was forced to compete in a smaller market with revenues far lower than teams like Boston or New York. Attempting to level the playing field, Billy Beane took a different approach to baseball resourcing. Instead of trying to sign big name players with the best batting average, Beane used statistical analysis to discover indicators that he believed would have a better correlation with offensive success.

Michael Lewis, author of Moneyball—a book on Billy Beane’s methods, writes:

“By analyzing baseball statistics you could see through a lot of baseball nonsense. For instance, when baseball managers talked about scoring runs, they tended to focus on team batting average, but if you ran the analysis you could see that the number of runs a team scored bore little relation to that team’s batting average. It correlated much more exactly with a team’s on-base and slugging percentage.”

And for awhile, Moneyball worked. In the early years of Moneyball, the Oakland A’s were competitive with payrolls in the $50 million range whereas larger market teams were spending $100 million plus. It wasn’t that Oakland was choosing to pocket the $50 million annual difference—they simply didn’t have that kind of money to spend. Oakland needed a way to compete and they chose analytics.

Unfortunately for Billy Beane, his competitive advantage didn’t last very long. Other baseball teams adopted statistical analysis and General Managers like Boston’s Theo Epstein quickly combined analytical prowess with the advantage of a major revenue market to assemble a perennial powerhouse. Like it or not (and some GMs still don’t), the adoption of analytics drastically changed baseball and now the use of analytics to help build a ball club is a standard process.

Similar to the adoption of Moneyball, marketing is in the throes of an analytical revolution.

Specifically, practitioners of marketing know they need fresh and accurate data for advanced marketing functions such as better segmentation, devising more effective campaigns and offers, and creating relevant interactions with the customer across multiple touch points. This data must be clean, modeled and managed—a large undertaking that involves marketers working closely with IT.

Marketers also are realizing that some understanding of analytical applications and business intelligence know-how is necessary to help analyze and translate data into actionable information that can be used to create better customer experiences. Hundreds of case studies in business publications and books have emerged over the past five to seven years as a testimony to these trends.

Analytics helped a small market team like the Oakland A’s compete with clubs that had much larger budgets. Indeed, Oakland enjoyed a period of success before larger teams “caught on” to Beane’s analytical approach.

In the same vein, the window of opportunity for marketers to adopt business analytics—before their competitors—is closing rapidly.

  • With the early success of Moneyball, Billy Beane parlayed himself an ownership stake in the Oakland A’s. For marketers, how valuable will analytical skills be in the near future?
  • Are you competing with companies that have much larger budgets and personnel resources? If so, what strategies are you using to win?
  • Critics of Moneyball say that one cannot run a major league baseball team with a computer. Going forward—in marketing—will knowledge and intuition win out over analytics?

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