How to Find the Truth in Data and Marketing Analytics

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Which “left hearts” of your brand are waiting to be discovered?

Seth Stephens-Davidowitz asked a variation of this question in his keynote address at the Marketing Analytics & Data Science Conference.

Let me explain.

Seth, a data scientist and New York Times bestselling author, tells the story of Jeff Seder, an entrepreneur and self-proclaimed innovator in horse racing analytics.

With three degrees from Harvard University, Jeff quit his banking job to pursue the outdoors and horses. His mission was to use data to discover what makes racehorses great. It was an era before Michael Lewis explained the use of analytics in Major League Baseball in his 2003 book “Moneyball.”

How do you find the winning formula for data analysis?

Jeff analyzed the characteristics of racehorses to determine which predicted success at the champion level. The characteristics he examined included:

• Size of the nostrils
• Volume of fast twitch muscles
• Size of stools

None of them could have predicted success. But Jeff kept trying and after 20 years found himself on the verge of bankruptcy.

But then the tide turned.

Jeff created the first electrocardiogram to measure a horse's internal organs and discovered that the left ventricle was a valid indicator of champions. Case in point: American Pharaoh. In 2015, the horse won the Triple Crown, the first horse in 37 years to win all three famous three-year-old Thoroughbred races. But two years earlier, no one but Jeff knew what a great racehorse American Pharoah would become.

Consider these characteristics of the American Pharaoh:

• Height (56th percentile)
• Weight (61st percentile)
• Pedigree (70th percentile)
• Left ventricle size (99.61st percentile)

While his height, weight and pedigree weren't overwhelmingly impressive, American Pharoah's oversized left ventricle accurately predicted his Triple Crown success.

Seth tells the story to illustrate these insights to data-driven marketers:

• The value of a data set is usually not its size but its novelty.
• Big data winners are entrepreneurial.
• Big data winners often fail to find the big winner.
• There are discoveries about the “left ventricle”.

By leveraging these insights, you can make your data model 10x better than anyone else's, says Seth.

MADS lesson: You can discover your brand’s “left hearts” in analytics data (e.g. web, email marketing, social media marketing, paid search). Form a hypothesis by asking a question. Analyze the data to answer the question. If the answer is “no,” ask another question. Keep going like Jeff Seder did until you find the “left ventricle” that will lead your campaigns to Triple Crown success.

Can you trust what people say?

However, not all data is necessarily helpful. Take surveys for example. Seth explains that the format commonly used by Gallup and Pew Research Center can be used to understand why people do things. However, there is an inherent problem with measurement.

People often say what they think will impress someone else. It is called social desirability bias. Seth gives an example of people saying they voted when they didn't, or saying they voted for one candidate even though they voted for another. They knowingly give incorrect answers because they want to give the impression that they are doing what is socially acceptable.

But where can marketers find pure honesty? On Google searches, says Seth. He calls it the “digital truth serum” because people confess it. They ask questions about their health, relationships, and anything else that comes to mind. They feel free to be honest because they feel like there is no one on the other end judging them.

Seth says Google knows more about people than its own partners and family members. So instead of asking what people are doing, use Google Trends. It's better than Gallup at predicting voter turnout, unemployment rates, and measuring racism.

However, Seth cautions us not to treat all big data as the same truth serum. If Google is a digital truth serum, Seth calls social platforms like Facebook the “digital serum that lets me brag to my friends about how good my life is.”

To illustrate his point, Seth shares his research on the term “husband” in social media posts and Google searches. Here are the key phrases that complete the statement “My husband is ___________” based on the platform:

As you can see, spouses on social media want to project positivity toward their husbands, while Google searches reveal what they really think.

MADS lesson: Study what users say (e.g. survey data) and what users do (e.g. web or app analytics data). Find your source of digital truth serum and use it to guide your marketing and business strategy decisions.

Should you believe your gut?

Seth says everyone lies. He even wrote the book “Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are.”

This doesn’t just apply to surveys and social media posts. People lie to themselves. In other words, their gut feeling can be wrong. Seth tells a story about an app called Mappiness. Users receive a ping at different times of the day asking how they are feeling and what they are doing.

The first-person data showed that these activities are most strongly associated with happiness:

• Intimacy/making love
• Theater/dance/concert
• Exhibition/Museum/Library

These activities are least associated with happiness:

• Care or assistance for adults
• Working/Studying
• Sick in bed

While these two lists may not surprise you, the research revealed a surprising finding – the difference between what people believe makes them happy and what actually makes them happy. This is what the Mappiness data revealed.

Underrated activities that made people happier than expected included:

• museum
• sport
• drink alcohol
• Gardening
• Shopping

Overrated activities that made people less happy than expected included:

• Sleep
• Computer games
• TV
• Eat
• Surf the internet

Seth says the data is clear: If you want to be happier, spend less time indoors. Get outside, be active and explore the world.

MADS lesson: Collect data to analyze how well your marketing gut (i.e. your perception) is working in reality (i.e. overstated, understated, targeted).

What role does appearance play?

Seth brought the personal into the conversation when he cited research from Alexander Todorov, a professor at the University of Chicago Booth School of Business. His study examined predicting election winners based on their appearance.

In the experiment, participants looked at photos of two candidates side by side and were asked to determine which one looked more competent. The study concluded that 70% of elections were won by the candidate that users selected as more competent.

Before reading this research, Seth said he never paid attention to his appearance. But now he was thinking about changing it and, like any good data scientist, turned to data analytics for support.

Using the AI-powered FaceApp, Seth created 100 versions of himself. Following Alexander's research, he presented people with two versions and asked them which one looked more competent.

Using regression analysis, he concluded that the only two factors that influenced skill preference were a beard and glasses. Wearing both increased his competency rating from 5.8 to 7.8.

Unsurprisingly, Seth appeared on stage with a beard and glasses.

MADS lesson: Just as a candidate's appearance influences the viewer's perception of competence, so does the appearance of websites and apps. Use focus groups to understand which design elements users associate with feelings of joy or satisfaction.

How will you use data analytics in your marketing?

I left Seth's keynote speech inspired to find new and creative ways to use marketing analytics to make decisions. Now I'm going to do better because I've heard Seth's “left ventricle” thinking. Data should be the decision maker, but only if it is true and accurate.

All tools mentioned in this article were suggested by the author. If you would like to suggest a tool, share the article on social media with a comment.

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Cover image by Joseph Kalinowski/Content Marketing Institute

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