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Chapter 6
Themes
and Colors
Key
LitCharts assigns a color and icon to each theme in The Power of Habit, which you can use to track the themes throughout the work.
Habits, Human Behavior, and Success
Habit Change and Personal Growth
Social Habits and Cultural Influence
The Moral Consequences of Habits
Summary
Analysis
Just after the eclectic statistician Andrew Pole started working at Target, he was tasked with building a model to figure out if customers are pregnant. He had spent six years analyzing greeting card sales for Hallmark before working for Target, which collected vast amounts of data about their consumers’ buying habits. From their purchases, Pole learned about shoppers’ lifestyles, families, and interests. Pregnant women were great customers because they subsequently turned into new parents, who would often buy everything they needed for their children in one place. Trying to figure out if customers were pregnant was an interesting challenge for Pole, but it eventually showed how surveilling customers can be dangerous.
Pole’s assignment again shows how habits are absolutely central to people’s lives. In fact, shopping habits reveal so much intimate information about people that it’s possible to build a complex profile of them based simply on what they buy at Target. Thus, Pole’s job also points to another important side of habit change: companies can profit by understanding and appealing to—or sometimes even manipulating—consumers’ habits on a mass scale. While transformative, this possibility also raises important ethical questions about how much control and responsibility people have over their own habits.
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For a long time, retailers like Target were more likely to hire psychologists than data analysts. By learning about consumers’ psychology, they learned to change the placement of products and increase sales. These days, though, they try to target individual shoppers. Studies have shown that people’s unique habits drive the way they shop. In fact, habit determines what people buy even more than what’s on their grocery list.
Target’s switch from psychologists to data analysts again shows how new technology transforms our ability to understand and change our habits. Just like scientists discovered the cue-routine-reward habit loop through brain scans, Target has been able to study and target individual shoppers’ habits through its mass data collection.
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To understand these habits, Target started collecting data about its consumers and linking their activity to a Guest ID number. It also began purchasing other data about them, including ages, addresses, ethnicities, job histories, and brand preferences. Target started using this data to guess what a customer buys habitually, then send them ads and coupons for those items at Target. Virtually all major American retailers use the same tactics, but Target is one of the most successful—largely due to its talented analysts, like Andrew Pole.
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In the 1980s, the professor Alan Andreason discovered that shoppers tend to change their habits (like by switching brands) in response to major life events like moving, getting a new job, or—most importantly—having a baby. This is why “pregnant women are gold mines” for Target. Their shopping habits are flexible, they have to buy thousands of dollars of items for their babies, and once they go to Target, it’s easy for them to start purchasing everything else there, too. Companies even market to new mothers by giving them free samples in hospitals.
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But Target wanted to push things even further by getting to couples before they had babies. That’s where Andrew Pole came in. He analyzed data from the Target baby-shower registry to determine what women bought during pregnancy. For instance, he found that women tended to buy lots of lotion during their second trimester and vitamins during the first half of their pregnancy. He put together a list of 25 products that allowed Target to predict if a woman was pregnant and, if so, when she was due. Based on this list, he found several hundred thousand Target customers who were probably pregnant. Sending them ads could be hugely lucrative.
But advertising to these women could also be dangerous, because they didn’t know that Target knew so much about them. One Minnesota man angrily complained that Target was sending his teenage daughter coupons for baby items—only to find out a couple days later that she was pregnant. Therefore, Andrew Pole had to figure out how to get ads to pregnant women without them knowing they were being targeted.
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In 2003, Arista Records started promoting Outkast’s genre-bending song “Hey Ya!” The company was using a new algorithm that forecasted a song’s popularity based on factors like its tempo and melody. These algorithms were more reliable than industry experts’ predictions, and they suggested that “Hey Ya!” would be a massive hit. But radio listeners hated it—a third of them immediately changed the station when it came on. Arista Records wondered if they could do anything to make the song into a hit.
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The radio station manager Rich Meyer has been analyzing the most popular radio songs around the country and publishing his findings in a newsletter since the 1980s. In the early 2000s, he started wondering what made some songs “sticky”—meaning that listeners usually listened to them all the way through. Some sticky songs were by popular artists like Beyoncé. But others were bland and forgettable, and others were by artists that many listeners disliked, like Celine Dion.
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Rich Meyer concluded that sticky songs sound more familiar than other songs. In other words, they are closer to the average of their genre, so they sound like what the brain expects to hear on the radio. In fact, the parts of the brain that process music tend to seek out patterns and familiarity. This prevents music from overwhelming the brain or distracting the listener. This explains why people habitually listen through familiar-sounding Celine Dion songs on the radio, while they turn off unfamiliar-sounding ones like “Hey Ya!” Arista Records getting listeners to like “Hey Ya!” is like Target trying to send pregnant women ads without them knowing that Target is spying on them. The key is to “mak[e] the unfamiliar seem familiar.”
During World War II, the U.S. exported so much meat to support the war effort that it started facing meat shortages at home. The Department of Defense led a successful campaign to popularize organ meat in the U.S. by making it more familiar—for instance, by telling Americans to add it to dishes like meatloaf.
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Radio DJs did something similar with “Hey Ya!”—they played it between two popular, sticky hits. The portion of listeners who turned off “Hey Ya!” fell from 26.6 percent to 5.7 percent. And as it kept playing on the radio, it became more and more popular. Now, it’s remembered as a hit.
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Andrew Pole also followed the same formula with his algorithm to predict pregnancy among Target customers. His department learned that pregnant women wouldn’t get offended if Target mixed together coupons for baby items and random coupons for items that pregnant women wouldn’t buy. Essentially, Target disguised what it knew about its customers. And its sales skyrocketed in the “Mom and Baby” section. Organ meat, “Hey Ya!,” and Target’s ads show that, “if you dress a new something in old habits, it’s easier for the public to accept it.”
This lesson also applies to lifestyle change. For instance, the YMCA hired researchers to boost membership retention rates by analyzing customer satisfaction surveys. The researchers found that customers didn’t keep coming back because of high-quality facilities, but rather because of their emotional connection with the gym. So, the YMCA trained its employees to remember customers’ names.
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Soon, Duhigg concludes, companies will often know more about their customers than those customers know about themselves. But to get customers to actually take on new habits, companies must make new things seem “familiar.” Duhigg notes that his wife is about to have a baby, and he’s already noticing new Target coupons for diapers quietly arriving in the mail.
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