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Moneyball is a baseball story, turned book, turned movie, now-turned PPC (pay per click) management lesson. While the story is years old (even the silver screen adaptation is aging quickly), its impact continues to be felt across Major League Baseball and beyond.
It’s a story about David versus Goliath, where one of the poorest teams in baseball, the Oakland Athletics (OA), managed to reach the playoffs and nearly defeat the game’s richest team at the time, the New York Yankees.
This scenario of David and Goliath is familiar to many PPC managers. With limited budget and time, you’re tasked with the incredibly challenging task of creating ads with better positioning and higher performance than competitors that seemingly have unlimited resources.
The Moneyball strategy uses statistical analysis to identify opportunities that are undervalued by the competition. It is a mindset that positions PPC managers ahead of the curve by ignoring traditional tactics in favor of new and more-promising ones.
This discussion will delve into the Moneyball story and the world of statistical analysis in baseball to find actionable insights that PPC managers can use to influence their campaigns positively.
(The background of Moneyball; setting the scene)
If you haven’t seen or heard of Moneyball before, you may want to take the time to watch the film version. It’s less a movie about baseball than it is a movie about data and statistical analysis.
In case you don’t have the time or patience to watch a 2-hour movie about baseball, here’s a recap of the movie’s premise.
Michael Lewis, the book’s author, eloquently summarizes the core of the Moneyball story in the forward: “The idea for the book came well before I had good reason to write it – before I had a story to fall in love with. It began, really, with an innocent question: how did one of the poorest teams in baseball, the Oakland Athletics, win so many games?”
Here’s the backstory that sheds some more light on the author’s proposed question. Between the 2001 and 2002 seasons, OA won a combined total of 205 games. The New York Yankees, on the other hand, won 7 games fewer for a total of 198 wins across the two seasons.
The 7 game difference between these two win-totals seems reasonable and innocent until you look at each team’s salaries. The OA had a meager team payroll of around $40M, while the Yankees had a $140M budget.
In other words, the OA was able to win more games than the richest team in baseball despite having 350% less money.
Moneyball focuses on the 2002 season but begins before the season opens. After coming within a few outs of toppling their rich archrivals, the New York Yankees, OA was facing a severe problem.
Three of OA’s best players were leaving. The team could no longer afford their salaries, which lends further evidence towards how disadvantaged the OA was compared to higher budget teams.
With the 2002 season rapidly approaching, OA needed to replace these three All-Stars with players that fit in their budget. It seemed impossible, until the OA general manager, Billy Beane, discovered a statistical advantage that would change the game of baseball forever.
In 1999, Beane met Paul DePodesta (renamed Peter Brand in the film adaptation), a Harvard graduate (or Yale, if you’re watching the movie) with a degree in economics and a penchant for sports.
DePodesta told Beane that the ways that Major League Baseball teams evaluated players were archaic. The problem was that managers relied on vanity metrics, biases, and their own opinions and experiences to make decisions on hiring new players.
With scouting strategies largely managed by guts and feelings, there was a complete lack of data in the equation. “Mathematics cut straight through that. It’s all about getting things down to one number. Using stats the way we read them, we’ll find value in players that nobody else can see.”
The two set to work using their newfound statistical advantage to answer the right questions and find a team of undervalued players that would fit within their budget and fill the void left by the departure of the three-star players.
By the start of the 2002 season, Beane and DePodesta had added several new players to the roster that had been undervalued by the rest of Major League Baseball. While their team would lack the star-power of the richer teams, they were able to put a competitive team on the field using the right data to inform their decisions.
The Moneyball strategy was about using data and analysis to find opportunities and baseball players that other teams had passed up or undervalued. What was the result of all of this Moneyballing?
For one, the ragtag group in OA had one of the longest winning streaks in the last century. They won an outstanding 20 games in a row.
Second, the OA once again managed to reach the playoffs. In fact, they won more games without the three all-star players that they lost in the off-season. This is significant evidence of the success and legitimacy of their statistical strategy.
Moneyball has many parallels to managing PPC campaigns and marketing in today’s Digital Age. There is a lot to dissect here! Again, this movie is as much about data as it is baseball.
The author’s concept of “an unfair game” hinges on the disparity between the game’s richest and poorest teams. This gap grew over a number of years until it became such a disadvantage to the game’s poorest teams that they could barely compete.
This is not unlike today’s PPC environment. More and more companies are turning to pay-per-click ad and Internet marketing to reach audiences. Yet, the number of available spots on search results pages remains the same.
In other words, there’s the same amount of real estate, but an ever-increasing number of interested parties.
Many PPC managers feel out-moneyed by larger companies with more time, personnel, and cash to commit to their campaigns. PPC managers can also feel outclassed by accounts with established Quality Scores that result in better (and cheaper) positions.
Like Beane and DePodesta, today’s PPC managers need to think outside the box and use their budget appropriately in order to win.
One of the challenges that Beane and DePodesta faced throughout the 2002 season was time relative to success. At the beginning of the season, the OA was dead last. Staff, fans, and players demanded immediate results, but Beane and DePodesta knew that their strategy required time to develop and snowball.
PPC managers face the same dilemma. Strategies often grow exponentially, which means progress is slow at first, before trending sharply upwards.
In the early phases, it can be difficult for PPC managers to face stakeholders and other parties because these individuals want to see those immediate results and they rarely are receptive to a wait-and-see mentality.
Obviously, you can’t ignore your stakeholders or customers. Your marketing efforts impact the activities of other departments, which means open communication is vital. That said, how you communicate results is crucial, especially when you’re in that initial, slow period.
“Our Goal and our expectation are: by mid-July, to be within 7 games of first,” DePodesta explains to the team’s owner.
No team owner wants to hear that their team will be 7 games behind first-place with half of the season already over. But, by sharing this goal, it explains that progress, while slow, is expected.
This is an important strategy to use when demonstrating long-term growth. Setting a benchmark goal will illustrate that progress is happening and beginning to snowball, even if that progress is slower than what the stakeholders may prefer.
PPC managers and baseball professionals are both easily misguided by vanity metrics. These are stats and figures that look interesting and important, but they don’t actually matter all that much.
Vanity metrics have far less influence than the actionable metrics that you should be focused on.
In PPC, for example, campaign managers can easily be misguided by lots of ad clicks. It feels good to see website traffic spiking and clicks can be a great indication that your ad messages are effective.
However, if you aren’t converting those clicks into customers and revenue, then what is really the value? Clicks matter, but they aren’t a good measure of a campaign’s success. Instead, you’re better off focusing on your return-on-ad-spend (ROAS), cost-per-acquisition (CPA), cost-per-click (CPC) and other metrics that connect to dollars and cents.
The heroes in Moneyball were able to find a competitive advantage by ignoring the vanity metrics that many scouts glorified, such as home runs and high batting averages. Instead, they focused on the metrics that provided tangible results and performance.
In PPC management, it’s also crucial to highlight opportunities that others, particularly your competitors, have accidentally or incompetently ignored or overlooked.
Baseball and PPC marketing are both heavily influenced by stats, metrics, and other numbers. Data is a powerful tool that can be used to draw conclusions, find connections, and make better decisions.
When you have all of these different data competing for your attention, you are much more likely to fall victim to vanity metrics or follow the wrong data. You have less actionable data distracting you from the metrics that are most important.
How can you filter out the noise?
First, you need to know what metrics matter. More specifically, what data directly relate to your marketing goals and PPC objectives? These metrics are your priority above others because they lead to the tangible results that help you achieve milestones.
Next, you need to figure out how to translate the metrics that are peripheral, or less tangible, into goal-oriented results. Everything, even vanity metrics, matters to some degree.
This difference between tangible and peripheral changes is the Pareto Principle. Also known as the 80-20 rule, the Pareto Principle says that 80% of your business results come from 20% of activities. These are the tasks that directly relate to your goal and need to be prioritized accordingly.
The other 80% of peripheral tasks, while still useful, don’t have that much influence on your goals. You need to do some extra legwork and connect those dots. If you can understand how each seemingly insignificant part affects the metrics that directly connect to your goals, then you can effectively get everything down to one number.
When Beane and DePodesta are faced with replacing three, star players, Beane tells his scouts that there are no players in the budget that can replace them. Thus, they need to “recreate [them] in the aggregate.”
In other words, they couldn’t one-for-one replace each player. Instead, they needed to recreate their performance and stats in other ways.
The aggregation of marginal gains is a concept for improvement where continuous, small improvements are made. When these seemingly insignificant parts are added up, they create momentous increases.
Successful PPC managers are doing this constantly. And, if you’re not, then you should be.
Between adding and subtracting players and winning or losing games, baseball teams are always changing, adapting, and improving. Your PPC campaigns also fluctuate and require ample attention and tinkering.
When PPC campaign performance dips, and you begin to see a decline in conversions or other KPIs, you need to discover alternative ways to recreate those numbers in your other strategies and campaigns.
It’s all about continuous effort and improvement. No one fails at PPC management because they put too much effort into it. By constantly working on creating continuous improvements, even small ones, the aggregate of those changes grows exponentially.
So, days when campaign performance is stagnant or below expectations, it will be easier to facilitate growth elsewhere in your PPC strategies. Similarly, your efforts become near-impossible to replicate by competitors because they require effort overtime to produce.
It’s the concept of a synergistic equation, where 1 + 1 > 2. If two people work together, the results they produce are far more substantial than if the two worked independently.
The same is true of your campaign management efforts. The synergy of many small improvements creates an exponential benefit. Or, as Aristotle said, “The whole is greater than the sum of its parts.”
In the film, Beane has a gruff encounter with one of his scouts. The scout confronts Beane over how he can trust data and science over the opinions of his staff. Beane himself was a scout, which meant that he was questioning his own experiences and know-how about judging baseball talent.
“Adapt or die” is Beane’s response.
Okay, it’s not quite that dire, but it is a good lesson that PPC managers should take to heart. Again, PPC is in a constant state of change. Your competition is always changing its strategies and improving; search users are altering their behaviors, and ad platforms are revising their rules and best practices.
Even the changes you make when managing your PPC campaigns create ripple effects that cause other metrics and performance indicators to fluctuate!
If you aren’t able to adapt to these changes and utilize the new technologies affecting the landscape, then you are going to be outperformed by the competition again and again.
It’s not just about meeting new changes but also testing new possible channels and tools. You never know where the next breakthrough advantage may come from.
Experimentation is an essential part of the PPC management process. Yet, it is often overlooked or forgotten.
Successful marketers keep a small portion of their budget for testing these new avenues, formats, and tools. Call it a PPC slush fund.
It’s about remaining flexible and expanding your strategies beyond your typical activities. You can’t keep turning over the same rocks and expect new results.
Success comes from change and the ability to effortlessly adapt.
The sample size is critical in any data-based activity. Moneyball does an excellent job of addressing the concept of sample size. When DePodesta and Beane meet with the team owner, they report that the sample size is too small to reflect accurate results. They need to wait for more games to understand if their strategies are paying off and what adjustments need to be made.
As a PPC manager, you also have to consider sample size when making changes to your campaigns. Often, search marketers are too quick to pull the trigger on making changes to their PPC strategies. They see a downturn in performance metrics that makes them hit the panic button.
Historical data is very telling in understanding when these adjustments need to be made. When you make decisions based on small sample sizes, it’s near-impossible to know if it is the right choice or not.
Why? Because data in a small sample size lacks maturity, which undermines its accuracy. The trends and correlations that you’ve worked so hard to detect and strategize around may not be as viable as you first thought.
When PPC managers make decisions based on inaccurate data conclusions, the results can be disastrous, especially when these decisions are made with lots of confidence. After all, how can cold, hard numbers be wrong?
A lot of naysayers in the baseball community argued against the Moneyball theory because the OA didn’t manage to win the World Series. Beane himself called the playoffs a “crapshoot” because they didn’t accurately showcase a team’s success.
The problem was the sample size. The regular baseball season is 162 games, which creates plenty of data to judge a team and its players accurately. The playoffs, on the other hand, are sometimes decided by a single game.
There are plenty of parallels between Moneyball and PPC management and lessons to be learned. The concept of using data to find high-value opportunities at a low cost is at the heart of digital marketing. You don’t need a movie to tell you that.
The question that keeps digital marketers up at night is how do you find these winning opportunities? And more importantly, how do you find these PPC opportunities before the competition identifies them?
The answer is in the data tools that you implement to aid your PPC management efforts. One solution is the PPC Signal.
There are several factors that influence your PPC campaigns. The landscape is always shifting and moving, which makes managing a PPC account is a demanding process. Operating a successful PPC campaign is less about creating compelling ad copy than it is monitoring and adapting to these shifts.
Complacency can be a severe detriment to your PPC marketing efforts. Even if your campaign is performing phenomenally now, there’s no guarantee that this success will continue in the future.
The moment that you stop putting in the effort and stop trying to improve your campaigns is the moment that your success begins to wilt and your competitors find the advantages that they need to hurdle past you.
At its core, PPC Signal is about making this task of managing and improving campaigns easier and less tedious. By automatically detecting shifts, trends, and outliers in your campaign performance data, PPC Signal quickly alerts you to potential and noteworthy changes that need your attention.
Then, it is your responsibility to prioritize the alerts and choose the avenues that you feel promise the most significant rewards at that time. You can follow alerts with low dimensionality (simple and easy to resolve) or tackle the more complex alerts that involve three or more dimensions.
“Change” is an ambiguous term, especially in terms of PPC management. There are many different types of changes that a marketer can make to a campaign. Sometimes, it is not readily apparent what kind of change is reflected in your data.
PPC Signal alleviates this problem by quickly separating alerts into two categories:
The tool goes a step further than the risk-opportunity classification by labeling each performance change as either a shift, trend, or outlier.
By defining the different types of changes, PPC Signal doesn’t just alert managers of noteworthy items in their campaign data; it also explains why the change is occurring based on historical data.
The tool even assigns value to alerts, as either good, better, or best. This helps PPC managers quickly identify the most noteworthy alerts from the list.
Whether a risk or an opportunity alert, PPC Signal returns potential areas of improvement at the campaign, account, ad group, or keyword level. These improvements will positively affect your PPC efforts.
Making continuous improvements is a key to success, no matter if you’re managing a baseball team or a PPC account. What many marketers fail to realize is that small, positive changes have a compounding effect.
Again, this is the concept of recreating performance in the aggregate. Your accumulative advantage grows with each improvement you make. It isn’t simply 1 + 1 = 2, but rather 1 + 1 > 2.
The edge that PPC Signal provides to managers is an always-available list of potential improvements to make. All of the alerts provided by the tool are changes that create this positive, accumulative growth. And, you don’t have to go digging through your data to find them because the tool will do it automatically for you.
This means you can spend more time improving your campaign and enacting these changes and less time searching through data for insights into how and where to improve!
Without this tool, identifying these changes is time-consuming and, depending on the alert, extremely complex. There are hundreds of thousands (if not millions) of combinations to explore within your ever-growing PPC data. There just isn’t enough time to find every possibility manually.
Simple changes (low dimensionality) are easy to identify, even with the naked eye. High dimensionality changes, on the other hand, are incredibly complex and near-impossible to identify without the help of sophisticated AI.
These complex changes are the ones that open doors to substantial opportunities towards improving PPC campaigns.
Everyone has a unique PPC experience. Maybe you’re a marketer with a too-little budget that needs an out-of-the-box way to get ahead of the competition, as the OA.
Conversely, maybe you are in the fortunate position of the New York Yankees with a bottomless budget. But, more money can mean more challenges, more opportunities, and more questions.
This makes PPC management very challenging. There are countless resources on the Internet (you’re reading one now!) about how to approach digital marketing and PPC advertising. The problem is that the shoe that fits on one marketing team isn’t guaranteed to work for you and your unique campaign efforts.
Success and growth, however, are universal. Everyone wants to improve. The trick is knowing how. The beauty of PPC Signal is that it provides alerts specific to your PPC strategies. Thus, there are no concerns that the changes it suggests are irrelevant to your campaigns.
Every alert is driven by your historical data and the current status of your PPC campaigns. That means every PPC Signal suggestion that you investigate provides immediate value and improvement to your account.
It’s your job to measure how much potential value is behind each alert and which path you need to follow first.
Improvement is an ongoing goal. “It’s a process,” as Beane reiterates again and again in the film. Your goal should be to improve daily, especially when you consider that the competition of PPC marketing is increasing every second. Competition never rests.
Since every change you make to your PPC strategies builds off each other, these daily and incremental improvements lead to monumental changes that can’t be replicated by competitors because they require time to establish.
Continuous improvement is what PPC managers should strive for. Again, the challenge is ensuring that the changes you make to your PPC strategies are continuous.
PPC Signal offers a much faster way to identify sources of improvement. Thus, making incremental changes part of your daily PPC routine is easy.
The lessons that PPC managers can learn from the Moneyball story can be summarized into four main points:
What Billy Beane and Paul DePodesta were able to achieve with the Oakland Athletics was a breakthrough change. It was a tremendous shift in strategy that not only changed the OA ball-club but the entire game of baseball.
Breakthrough changes are as rare as they are significant. Typically, they only provide real growth to the earliest adopters. Then, everyone catches up to the new way of doing things.
Incremental changes, on the other hand, happens slowly and are attainable by anyone that is willing to put the time and energy into continuously improving their strategies. And, incremental growth isn’t so easily copied by competitors, which means you’ll hold onto your competitive advantage for longer.
PPC Signal is a powerful tool for utilizing the takeaways from Moneyball and applying these concepts of changing and growing over time. Not only does it alert you of opportunities and risks hidden within your PPC account data, but it also saves time and resources in the process.
You’ll have a clear list of opportunities to explore that are backed by clear evidence from your own PPC data.
Now that is a home run.
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