The Red Sox, Tina Fey, and Your Marketing Strategy: An Argument for Balance

Updated: Nov 26, 2018

Q: What do the Red Sox, Tina Fey and the best marketing strategies have in common?

A: They find the perfect balance between two extremes: quantitative, structured, data-driven tactics on one hand vs. qualitative, creative, big-picture tactics on the other.

Let’s take a closer look.

I. The Red Sox and Moneyball: Sabermetrics vs. Old-School Scouts

In Michael Lewis’s Moneyball, Oakland A’s general manager Billy Beane is portrayed as aggressively adopting the data-only approach pioneered by Bill James, (called Sabermetrics) much to the dismay of the old-school scouts on his team. The old-school scouts (lead by head scout Grady Fuson) had their decades-old methods of evaluating players based on immeasurable metrics like swing quality and confidence, and the quantifiable metrics they did use often bore little correlation to winning. As the story goes, the more Beane pushed his new data mindset, the more his scouts grew disgruntled, until Fuson ended up leaving in a furor. The A’s enjoyed an unprecedented win streak, but couldn’t break through into genuine playoff success.

The Red Sox winning the World Series in 2004, their first in 86 years.

It wasn’t long before the Boston Red Sox hired Bill James (and attempted to hire Beane). But the Sox understood the importance of the existing scouts they had on staff. Instead of pitting one side against the other, they created a system that integrated the old-school qualitative analysis of baseball scouts with the new-school quantitative approach of James. There were no intra-staff protests about the new approach, since the organization used its breadth of expertise (and, to be fair, a sky-high payroll) to make decisions. It was only by building a cohesive system that they achieved an ideal balance of two distinct schools of thinking: traditional qualitative analysis and new-age analytics.

The result: one year after hiring Bill James and adopting a holistic, balanced approach, the Red Sox won their first world series in 86 years, and they’ve won 3 more since.

II. Tina Fey: Ivy Leaguers vs. Improvisors

We see the same concept at play in Tina Fey’s work, most notably on SNL and 30 Rock. In Bossypants, Fey describes the magic formula to building a successful writing staff:

“The writing staff of Saturday Night Live has always been a mix of hyperintelligent Harvard Boys and gifted, visceral, fun performers[...]too many of one or the other would knock the show out of balance.”

She then sums it up perfectly:

“The Harvard Boys check the logic and construction of every joke, and the Improvisers teach them how to be human.”
The writing staff of 30 Rock's show-within-a-show, TGS, many of whom were actually writers of 30 Rock and SNL.

Fey and SNL creator Lorne Michaels generally believe great writing to be at the center of a successful comedy show, and this philosophy drives the construction of those teams. In other words, the key to achieving success in this setting is striking the right balance between structure/logic and imagination/the human touch.

The result: this holistic, balanced approach has made Saturday Night Live and 30 Rock among the most successful comedies in TV history.

III. Marketing Strategy: Performance Marketing vs. Mad Men

So, we've covered the balance between sabermetrics vs. old-school baseball scouts and ivy leaguers vs. improvisors. What’s the parallel in marketing? Performance marketing vs. Mad Men.

A successful marketing strategy needs to follow the same model as the Red Sox and Tina Fey’s writing staff by balancing these two sides of the equation. Yet just about any time I speak with a company that’s falling short of growth goals, they’re leaning way too far toward one side or the other.

Mad Men character Don Draper presents an ad concept.

Mad Men

Once upon a time, marketing strategies were heavily weighted toward qualitative approaches. In the so-called Mad Men model, Don Draper and his ad men (obviously fictional characters but very much based on the reality of the ad industry of that time period) came up with ideas that felt good based on an empathetic view of the customer. It's worth reiterating that empathy was key...the process of marketing a product to customers required a deep understanding of those customers and what it was like to see things the way they did. Conversations revolved around resonant messaging and powerful imagery. What would move a potential customer to purchase?

The major downside of this approach is that it's dependent on assumptions and is therefore not data-driven. This is best summed-up by what's likely the most oft-cited marketing quote of all time: John Wanamaker's infamous complaint that "half the money I spend on advertising is wasted; the trouble is I don't know which half." The Mad Men model lacked the data clarity that we enjoy today, which meant far fewer opportunities for A/B testing and validated learning.

Performance Marketing

In the past decade or so, the pendulum has swung in the other direction: performance marketing (AKA growth hacking, growth marketing, etc.) is taking over. It brings with it incredible advantages: the ability to set up clean A/B tests and legitimately implement the scientific process, audience/targeting capabilities like never before, and unprecedented visibility into funnel metrics and data in general.

But with all this comes a common trap: the assumption - either implicit or explicit - that great branding (and great creative) will be a natural outcome of testing. If you A/B test 10 images, you will likely end up with a winner. But that's not the same thing as identifying the best visual approach for your brand. The input is therefore crucial...if you test a bunch of mediocre images, you'll find the best mediocre image. Conversely, if you test a bunch of meticulously-planned, empathetically-designed, brand-driven images, your tests will produce actionable outcomes and validated learning. This leads to a concrete creative strategy...and one that drives conversions. If you pair that creative ideation with specific hypotheses (e.g. humor resonates with our customer persona and will drive more purchases) then you are setting your tests up for genuine validated learning. And if, for example, you make said humor hypothesis, then you need to come up with some ideas that are legitimately funny. This is where most test plans fall apart; they either have an unclear hypothesis or test variants that don't accurately represent their test group (in this case, "funny" variants that aren't actually funny). These half-baked tests inevitably result in mediocre winners and no clear next step. For brands that struggle with this (and I argue most startups do), this means tremendous amounts of missed opportunity. In metric-speak, this usually manifests as lower click through rates, higher cost per acquisition, and lower retention rates. Improving those metrics doesn't just require better ideas, it requires great ones.

In other words, the existence of A/B testing cannot be a reason to get lazy with creative strategy and ideation. The great irony of digital marketing is that your conversion rates will suffer if all you focus on is your conversion rates.

This is a pattern we've seen before. As history has shown, a natural outcome of improved systems capabilities is an overcorrection away from imperfect processes. With the emergence of performance marketing, many companies have been quick to aggressively adopt it for its strengths while failing to consider and adjust to its weaknesses. This is often due to adopters lacking a thorough understanding of the system they're adopting. Eric Ries warns of this exact phenomenon in The Lean Startup:

“We cannot afford to have our success breed a new pseudoscience around pivots, MVPs, and the like. This was the fate of scientific management, and in the end, I believe, that set back its cause by decades. Science came to stand for the victory of routine work over creative work, mechanization over humanity, and plans over agility. Later movements had to be spawned to correct those deficiencies.”

Unfortunately, this is precisely what we’re seeing in marketing today: A/B testing and the scientific method have come to stand for a lack of creativity, ideation, and, perhaps most importantly, empathy. It’s time to correct these deficiencies and reintroduce the human element to data-driven marketing.

By aggressively adopting a strategy that balances good-old-fashioned, outside-the-box creative thinking with conversion rate optimization and data analytics, you’ll wind up with the formula that has given the Red Sox 4 World Series wins in 15 years and made SNL one of the longest-running shows on television. Not bad.