Make Sure Data Isn’t Your Downfall

The internet was an amazing boon for poker in the early 2000s. Not only could you play high stakes games without going to a casino, but the technology was transformational. Traditionally, you rarely get to play more than 30 hands per hour in a casino game. Online, you can play twice as many hands per hour. More importantly, you can play multiple tables at the same time.

The real game-changer, however, was data. With hand history, you could build a perfect database of every opponent, tendency, and mistake. It didn’t take long for technology like heads-up display (HUD) to come along to track how someone gambled. Playing too loose in early position? Overplaying hands like pocket nines or pocket tens? The database would tell you all and encourage you to improve the leaks in your games. Instantly, my results improved and profits increased.

A few years later, in 2007, I decided to record every poker hand I played in a notepad. I was playing quite a bit at the time, so when I sat down at a table, I wanted to make sure I had a data-driven advantage. In addition to online games, I played roughly 10 tournaments that year, including a few events at The World Series of Poker. In total, I logged more than 1,000 live hands.

Looking back over a decade later, I’m not sure I made the wisest decision. Sure, it sounded great in the moment, but I didn’t improve as much as I hoped. The goal became to collect as much data as possible instead of trying to become the best possible player and make a little money. (I didn’t cash at the World Series, but the 2017 main event winner took home $8.15 million.) By the end of the year, I came to my senses and put the notepad away for good. Frankly, I found that data alone was not the solution. In order to be at my best, I needed to optimize my decision-making more than my data collection.

You may be surprised to hear me push back against data collection. I’m Contently’s VP of revenue marketing, which means my days are filled with Salesforce reports, spreadsheets, and discussions about ROI. To be clear, marketers need strong quantitative evidence to prove the value of their investments, especially to executives and boards of investors. My issue, though, is that many of them seem to be fixated on gathering all the data when they should really put all of their chips into finding the right data.

It’s easy to see why. Every marketing solution on the planet promises that it can measure the most important metrics for your business. The truth is some can; some can’t. Just like poker, the lure of both real-time data for better decision-making as well as databases for more serious analysis can be seductive. But when marketers pile their stacks with more software, they wind up drowning in data. A 2018 study from InsightSquared and Heinz Marketing found that “the more experienced a marketer is, the more likely they are to be dissatisfied with their marketing automation system’s reporting and attribution capabilities.”

Data alone was not the solution.

So what can you do to use analytics more effectively? The answer, gleaned from a few of our clients, is deceptively simple: start with one data point that shows clear business impact. That’s it. Walmart, for example, started to gradually get more budget and buy-in over the years when the editorial team discovered that customers who engaged with content had an average order size 7 percent larger than customers who went straight to shopping.

Of course, Walmart couldn’t coast on that one stat. As the editorial team got smarter about what content to create, there were other signs of progress—bounce rate improved by 22 percent, for instance, and time spent jumped by 30 percent. But the larger point is marketers can’t get hung up on showing success 10 different ways when that’s rarely plausible in the early days of a content program.

We love to talk about storytelling here. And while I’m definitely more of a numbers guy than a scribe, I do appreciate a good narrative. When I comb through those spreadsheets and calculate the ROI of our internal marketing efforts, I think of it as telling a story with data. It’s my job to build trust with my audience—without overwhelming them or straining my credibility.

There’s an interesting parallel here between content creation and content analytics. Brands have mostly adopted a quality-over-quantity mindset for storytelling. They’d rather prioritize one great e-book that has lasting impact than five blog posts with ambiguous results. For whatever reason, that level of thinking isn’t as widespread as it should be on the business side in a lot of organizations. But as brands start to understand what they can do with a few powerful stats, I bet that’s going to change.