Lessons in Marketing Analytics from Major League Baseball

Posted by admin on April 10

April marks the return of professional baseball. And while Opening Day means freshly cut green grass, hopes that ‘this is the year‘ and hot dogs, peanuts and Cracker Jacks to most, behind the simplicity that is baseball is new found quantitative analysis. 

Yes, statistics and analytics in the game were front and center in Moneyball, a popular movie that appealed to baseball fans and non-fans alike for its Michael Lewis script, A-List acting and its many parallels to good management based on data. For example, today in boardrooms and at office water coolers everywhere, ‘Moneyball’ is a part of the lexicon that means ‘surpisingly valuable', because the data proves it.

But today's use of analytics are even transcending Moneyball, which speaks to the proper evaluation of resources, placing more value on historically underestimated assets. Players and coaches are beginning to use more sophisticated advance scouting and analytics for in-game predictive strategy. With such a focus on strategy, forward-looking analytics are a whole new ballgame.

The Ft. Worth Star Telegram, recently featured an article about the ‘Analytics’ that ace pitcher Cole Hamels is using to prepare for games – and execute. As a pitcher with what Manager Jeff Banister calls a “high baseball IQ”, Hamels utilizes data that the Texas Rangers extract from advance scouting – and video – to better understand his opponents.

Data-points such a ‘bat exit velocity’ against different pitches are key predictors of future outcomes. And while not mentioned in the article, locational pitch preferences and weaknesses – inside, outside, up or down – become more than dugout talk with analytics. Statistics are assigned to each location, enabling predictive power to give the pitcher an advantage.

And the analysis is getting increasingly complex. So much so, that last year, it was reported that a ‘Mystery MLB team’ was utilizing a Cray Supercomputer which are $100,000 - $1 million computational beasts made for crunching unfathomable amounts of data. 

The impact of improved data can make a big difference according to Cray VP of Marketing Barry Bolding:

“Baseball is a game of averages, and at the end of the day the data can get a game wrong or make a bad choice. But if you can improve your averages — maybe your batting average goes up 10 points — that can have a huge impact on a 162-game season.”

According to Cray, 95% of baseball analytics have been generated over the past 5 years. But baseball has always been a stats game. Baseball cards have listed stats on the back for almost a century. And groups like the Society for American Baseball Research (SABR) have analyzed baseball data and statistics for decades.

So what has changed? A focus on future probability and not past results.

Baseball analytics have moved from results-oriented ‘statistics’ – “how many home runs”, “batting averages”, “lefty-righty matchups” – to future-looking predictive analytics.

It’s a fundamental shift. No longer are statistics simply the detail to support the results of a player or team’s performance, but they are a fundamental predictor utilized to strategic advantage.

Suddenly, the data is 'one' with in-game strategy. And when pitchers with the control – and changeup – of Cole Hamels have the power of big data behind their strategy, it’s increasingly unfair for hitters. In a sport where you could already become a Hall of Famer while failing 70% of the time, the difficulty will only increase with predictive analytics.

This is where marketers should learn from baseball.

Analytics, from the ubiquitous Google Analytics to any other report on marketing results, have, like baseball, often focused on the past.

“What kind of unique visitors, or conversions, etc. etc. have we historically seen?” has been the question of the smart marketer.

And just like baseball, marketing stats have been utilized a long time.

But the power will be in the transition to predictive analytics and forecasting. The move to proactive from reactive. To utilize known data points in real-time, guiding strategic decisions such as pricing, what to market, how and to whom, to conversion-optimization, segmentation and more. And today’s marketing technology ecosystem enables plenty of tools to fuel these insights, from A/B testing platforms to advanced analytics and more.

Baseball is not unlike business. And as a marketer, like a baseball manager, you face competition and must also assign value and potential to customers – additional data points and analytics on which to value investment.

With strategic segmentation, for example, marketers can leverage analytics to more confidently make significant investments towards customer acquisition. Perhaps the ideal customer acquisition cost within some segments is as high as $2500, whereas others should be valued at much less based on net-present-value (NPV).

How can you predict this value, and utilize it in strategy? Start thinking predictive and not reactive with your data and analytics.

That doesn't mean that every instinctive decision should become quantitative. As in marketing, much of baseball doesn’t require analytical rigor to make a good decision. Don’t, for example, throw an inside fastball to Bryce Harper - that's just common sense.


But over time, with the power of predictive analytics, you’ll find more wins, fewer losses and make better decisions with improved ROI by looking to the future instead of the past with your use of marketing analytics.

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