Time and again, I see companies make crushingly common mistakes with data and refuse to make room to experiment and fail. Data empowers marketers to make better decisions and take smarter risks, but sometimes the best intentions lead to the wrong solutions. Interpreting data isn’t always easy, and I’ve seen marketers come up short by not allowing themselves the space to learn from their collective experiences. A campaign that falls short of its goal can teach just as much as one that succeeds. And marketers who wish to do the right thing well can learn from how they do the right thing poorly. Here are three ways successful data-first organizations think, and how you can apply them to your business.

Look at metrics as part of a story, not the whole picture: One of the biggest mistakes a marketer can make is to look at data in isolation. If you oversimplify data, you’ll lose out on the magic that’s happening around you. Successful companies don’t capture metrics for the sake of it. For every metric they set, they go a level deeper by asking themselves key questions: Do I know what this metric truly means? What could influence this metric, and how? Am I limiting what I can learn from my metrics?

Expect human behavior: Machine learning is growing fast and teaching us a lot. But people aren’t machines, and that means they’re not always rational, efficient bidding and buying engines. They don’t necessarily respond the way you’d think they would. As a marketer, you have to understand the human story behind your data. I’m not suggesting you throw conventional wisdom out the window, but remember that successful companies know it’s not possible to predict every element of the customer journey.

Fall in love with failing: When we work with smaller businesses or startups, we tend to see some miserable marketing attempts. But we can learn so much from how these companies respond to those failures: They usually look inward, considering that perhaps their brand isn’t strong enough yet or that they haven’t properly optimized their campaigns. What they don’t do is look elsewhere to place blame. And here’s what I see repeatedly in larger organizations: If something they’re testing fails, they’ll pivot immediately to a strategy with which they can win, arguing that customers simply aren’t there or that the channel doesn’t work for their business. This is where doing the right thing poorly needs to become your new manifesto. Give yourself and your teams the ability to fail—it’s the first step to growth. Use failures — and successes — to ask questions, the key one being: What is the right thing for me to be doing? Even if you can’t immediately take action, acknowledging the answer is the start of doing the right thing well.


Neil Hoyne is Chief Measurement Evangelist at Google and a senior fellow for the Wharton Customer Analytics Initiative. This article was adapted from a piece originally published by Think with Google.

Published as “A Fresh Look at Analytics” in the Spring/Summer 2020 issue of  Wharton Magazine.