Small Data Read online

  Bear in mind that none of these examples had much, if anything, to do with big data, which can only take us so far. After all, humans dissemble, consciously or unconsciously. Most of us aren’t aware of our habits and desires. In a 2015 discussion at the Cannes Lions Festival between Tom Adamski, the CEO of Razorfish Global, and Will Sansom, director of content and strategy at Contagious Communications, Adamski went so far as to say that digital media, and big data, has contributed to a global decrease in brand loyalty. Why? In Adamski’s words: “Brands are not treating us as individuals . . . Brands are still relying on archaic—and quite frankly, flawed—segmentation processes that market to demographics. But they don’t market to me.”6

  Big Data rarely helps to identify the “needle” in the stack

  Illustration by Ole Kaarsberg

  If companies want to understand consumers, big data offers a valuable, but incomplete, solution. I would argue that our contemporary preoccupation with digital data endangers high-quality insights and observations—and thus products and product solutions—and that for all the valuable insights big data provides, the Web remains a curated, idealized version of who we really are. Most illuminating to me is combining small data with big data by spending time in homes watching, listening, noticing and teasing out clues to what consumers really want. After all, at age 14 when LEGO first hired me, I was that consumer, a kid enamored with the company’s building blocks. By observing my own behavior, and that of my friends, I was able to give LEGO executives insights on their product and company that any number of quantitative surveys could not—just as, in sharp contrast to what big data was telling them, the observations of an 11-year-old German boy were able to help reverse LEGO’s slide into bankruptcy.

  Intriguingly, we are now turning the tables on the Internet by circling back and finding human—not digital—insights about ourselves based on our own unconscious online behaviors.

  In 2013, for example, using data accumulated from 250,000 people over a period of ten years, a study appeared in the Journal of Personality and Social Psychology examining music consumption tastes as they evolve over the course of a lifetime. Music, it appears, adapts to whatever “life challenges” or psychosocial needs we face as we get older.7 The study divided music consumption patterns into five “empirically derived” categories dubbed the “MUSIC model”—an acronym that stands for mellow, unpretentious, sophisticated, intense and contemporary. Perhaps unsurprisingly, the first significant age of music-listening is adolescence, a time defined by intense, which possibly reflects increased hormonal activity or the creation of the teenaged “self.” Intense intersects with a rise of contemporary music, a trend that lasts until early middle age, when two other “preference dimensions”—Electronic and R&B—enter the mix, both of which are “romantic, emotionally positive and danceable.”8 The final musical age of humans is dominated by sophisticated—jazz and classical music—and unpretentious—country, folk and blues. These latter two musical forms are relaxing, positive and link indirectly to listeners’ social status and perceived intellect.9

  What do the sports we love the most say about us? A study carried out by Mind Lab surveyed 2,000 UK adults and found that bicyclists are “laid back and calm” and less likely than runners or swimmers to be stressed or depressed. Runners tended to be extroverted, enjoyed being the center of attention and preferred “lively, upbeat music.” Swimmers, the study concluded, were charitable, happy and orderly, whereas walkers generally preferred their own company, didn’t like drawing attention to themselves and were comparatively unmaterialistic.10

  Are you aware that people with a lot of Facebook friends tend to have lower-than-average self-esteem?11 Or that the more neurotic Facebook users are, the more likely they are to post mostly photos?12 Last year, an article in the New York Times Magazine analyzed the significance of the passwords we use to get online and access certain websites. The article reported that in the same way we leave a trail of emotional DNA in our wake, we also distill emotion inside our passwords—and that many of our passwords ritualize a regular encounter with a meaningful memory, or time in our lives, that we seldom have occasion to recall anywhere else. “Many of [our passwords] are suffused with pathos, mischief, sometimes even poetry. Often they have rich backstories. A motivational mantra, a swipe at the boss, a hidden shrine to a lost love, an inside joke with ourselves, a defining emotional scar—these keepsake passwords, as I came to call them, are like tchotchkes of our inner lives.”13

  Big data might find it hard to find meaning, or relevance, in insights like these. In every study I mention there is a missing question: How might these findings be combined with small data to affect or transform a brand or business? Subtext Research might reveal that a 16-year-old girl who listens to “intense” music might find it a poor fit with her teenaged identity, and a 45-year-old Englishman who listens to John Coltrane and Chopin might tell you he pines for the intensity of his teenaged years and, in fact, wears a black rubber band around his wrist as a badge of rebellion. But you would never know this until you sat across from these people in their living rooms or bedrooms.

  Nor, it seems, could an unnamed banking institution truly comprehend the behavior of its customers even after leveraging a big data analytics model designed to prevent customer “churn,” a term referring to customers who move money around, refinance their mortgages, or generally show signs they are on the verge of exiting the bank. Thanks to the analytics model, the bank soon found evidence of churn, and promptly drafted letters asking customers to reconsider. Before sending them out, though, the bank executive discovered something surprising. Yes, indeed, “big data” had seen evidence of churning. Thing is, it wasn’t because customers were dissatisfied with the bank or its customer service. No: most were getting a divorce, which explained why they were shifting around their assets.14 A parallel small data study could have figured this out in a day or less.

  Then there are the issues facing Google’s new self-driving cars, most of which it seems can be credited to the mismatch between technology and humanity. According to the New York Times, last year as one of Google’s new cars approached a crosswalk, it did as it was supposed to and came to a complete stop. The pedestrian in front crossed the street safely, at which point the Google car was rammed from behind by a second non-Google automobile. Later, another self-driving Google car found that it wasn’t able to advance through a four-way stop, as its sensors were calibrated to wait for other drivers to make a complete stop, as opposed to inching continuously forward, which most did. Noted the Times, “Researchers in the fledgling field of autonomous vehicles say that one of the biggest challenges facing automated cars is blending them into a world in which humans don’t behave by the book.”15

  As accurate, then, as big data can be while connecting millions of data points to generate correlations, big data is often compromised whenever humans act like, well, humans. As big data continues helping us cut corners and automate our lives, humans in turn will evolve simultaneously to address and pivot around the changes technology creates. Big data and small data are partners in a dance, a shared quest for balance.

  Earlier, I wrote that despite the 7 billion or so people inhabiting the earth, in my experience there are only anywhere from 500 to 1,000 truly unique people in the world. This isn’t to put down individuality; instead, it recognizes the degrees of connectivity aligning humans who ultimately can be “divided” by four criteria: Climate, Rulership, Religion and Tradition.

  Climate is only indirectly linked to the sun shining overhead, or whether or not your winters are cold or temperate. Rather, it refers to how your environment reflects and also influences behavior and diet. Scandinavian natives, for example, favor a diet weighted heavily toward richer, fattier foods, whereas the Mediterranean diet is lighter and more oil-based.

  Rulership refers to the power, or government, in charge, whether it’s Vladimir Putin in Russia, a Democratic
or Republican regime in the United States, the Communist Party in China, or the dictatorships of Iran, Jordan, Ethiopia, Sudan and elsewhere. How free are a country’s residents? Religion, of course, refers to the influence of belief in a country, how dominant or irrelevant it is, and whether a person’s belief system lies behind decision-making processes. Finally, Tradition focuses on a country’s unspoken protocols, whether it is the European habit to ignore other elevator passengers or the American predilection for friendliness. Once you’ve taken these four variables into account and set aside differences in class, race, skin color and gender, humans are the same no matter where they live.

  Until recently, I never considered what I did for a living as a repeatable methodology. But over the past few years, nearly half-a-dozen companies have asked if I could distill my Subtext Research into a training program. In some segments of Nestlé, where I’ve consulted for years, my techniques, or Subtext Research methodology, have become an integral part of analyzing new products, ideas, innovations and brands. Today, thousands of Nestlé employees spend 48 hours a year visiting consumers in their homes.

  I’m often asked the following question: What about sampling bias, where members of a population are unequally represented? With a smaller sample size, how can anyone, much less a company, hope to find a comprehensive solution or answer? If it does, is there any guarantee that your findings will accurately represent a larger whole?

  My answer is that a single drop of blood contains data that reveals nearly a thousand different strains of virus. Providing that your sample size is well chosen, there is little difference between a blood sample and the work I do, which is why interviewing 50 respondents (rather than 5 million) is often more than adequate to carry out a solid 7C methodology. Harder for many people, and businesses, to admit is that rather than basing their research on millions of consumers, sometimes all it takes is ten people to transform a brand or business.

  Working for Lowes, for example, I began my investigation with my own observations about American culture: the rounded shapes, the lack of physical touch and the homogenous retail landscape. I eventually connected these observations to a hypothesis, i.e., the high degree to which fear influenced American life. When I interviewed Trollbeads fans, one of the first things I picked up was how many of them said they missed the sense of community, family and collegiality they remembered as children and how, for many, Trollbeads was able to assemble a collection of highly personal memories that linked together the passing years.

  In every case, something was missing from people’s lives: a subconscious desire. By identifying an unmet desire, you are that much closer to uncovering a gap that can be fulfilled with a new product, a new brand or a new business. Remember that every culture in the world is out of balance, or in some way exaggerated—and in that exaggeration lies desire.

  Subtext Research helps to identify Small Data, which in turn leads toward the creation of a Concept

  Illustration by Ole Kaarsberg

  The 7Cs in my Framework stand for Collecting, Clues, Connecting, Causation, Correlation, Compensation and Concept. Consider the following as a pocket guide to how to take one, or several, small pieces of small data—a refrigerator magnet, a porcelain frog—and very possibly transform them into a winning concept. Throughout this book you have been traveling the world with me on an airplane, bouncing from place to place, culture to culture. It’s time you came inside the cockpit.

  Collecting, or, How are your observations translated inside a home?

  The viral Internet dress photo is a good reminder that none of us sees the world in the same way. Most of us are blinded by the familiar. We surround ourselves with people who are like us, who believe the same things we do. Our Facebook newsfeeds are no different, reflecting our interests, beliefs, concerns and biases.

  The first step in the 7C process, then, is to do everything you can to remove the filter that keeps you from seeing what is really going on. My advice? Get a haircut.

  Let me explain. The “collecting” step begins with establishing navigation points, on both macro and micro levels. This includes getting perspectives from cultural observers, for example, people who are new to the area, either expats or people who see the community through objective eyes. Ask them: What does the neighborhood, or city, or town, look like and feel like? Are the sidewalks deserted? Are there children playing outside? Are people friendly? Do you ever feel scared, and if so, why? Is there any sense of neighborhood pride? If you see people on the streets, do they meet your eyes or look away? Is the garbage picked up regularly? What makes a city or town come together? What divides it? Why? Visiting Brazil, I quickly found out that the nation is preoccupied with football and religion, and divided by restrictive class levels. There was a tension implicit in these layers. Did Brazilians need to escape? This tentative hypothesis was one I would eventually shape and refine.

  Now, seek out a hairdresser or one or several other “local observers” who can help you establish a baseline perspective, and who inhabit a more or less neutral space within a community. It doesn’t have to be a hairdresser; it could be a bartender, a mailman, or a church, community or sports club leader. Whoever it is, cultural and local observers are privy to information most people are not. They can tell you what’s really going on. They are more or less unbiased. They can also point you to their own networks of friends and acquaintances.

  The navigation points you gather from local observers will help you to frame your initial observations and create a hypothesis before you enter a consumer’s home. In turn, your initial hypothesis will help you create “tracks,” or topics of interest or focus, to follow once you begin interviewing consumers. Only rarely will one of your first six tracks be the final one, and half of them will later be disproven or tossed away. Think of them as stepping-stones that lead to bigger and better stepping-stones that lead, finally, to a concept.

  At this collecting stage, you are trying to capture as many different perspectives from as many trustworthy sources as possible. If you have any doubt whether these local observers are useful, or reliable, social media is a fast, easy way to confirm their degree of integration into a community. People active in social media are, by nature, extroverted and confident. Take notice of how often they post; their degree of curation; the relevance of their content; and whether or not there is a touch of swagger or exhibition to their postings—all of which combine to create an ideal local observer. Bear in mind that local observers often have both a public and a private Facebook profile, making it easier to contact them. During your preliminary phone call, by asking the same questions you asked of cultural observers, you can quickly discover if their perspectives are useful or not.

  If you are working on behalf of an existing brand, I also recommend interviewing the brand’s past, current and potential future users—a group that ideally should reflect 50 percent of the total aggregate of respondents.

  Clues, or, What are the distinctive emotional reflections you are observing?

  Remember, you are an investigator whose goal is to create a narrative, a cohesive story that hangs together. For this reason, nothing you see or hear is irrelevant or wasted. Imagine that you are equipped with a hypothesis and entering someone’s home for the first time. (Your hypothesis may be true, half true or false—you don’t know yet.) Think of a residence as a place that is home to an infinite series of small voices that owners are broadcasting in every room. Are the voices congruent, or are they out of tune? What unconscious, seemingly random pieces of small data are hanging from the walls, hiding inside “off-limits” zones like the refrigerator and the kitchen cabinets? Everything in the home, from the art on the walls to the insides of bathroom cabinets, is positioned where it is for a reason.

  Here, I regularly call upon a model to divide the assorted “selves” that make up the average consumer. First is the idealized self we project onto the world, the one focused around h
ow we’d like others to see us (which, I might add, is often very different from who we actually are). This manicured, public self is similar to the one we assemble on our Facebook pages and Instagram accounts. Components that also fall under the category of “idealized self” are the objects we collect and display in our homes, from photographs to heirlooms to tchotchkes. Over the years, I’ve observed that our collections form a timeline of our lives, a secondary calendar that offers a valuable perspective on who we are—or believe we are—and where we’ve been. The most common “recharging station” for reflecting on what we have accumulated is the living room, and for adolescents, backpacks and laptop covers.

  That said, the places where our idealized selves conflict with our actual selves tend to be private: our refrigerators, kitchen cabinets, wardrobes and—in the case of men—garages and online folders.

  Often, it is what is missing that forms the cornerstone of a successful hypothesis. Take Denmark, for example, with its countless “conversation kitchens” and untouched, unused Brio tracks. On the surface, most Danish homes are “perfect” in appearance. Get closer, and you will realize that room after room is, in fact, staged, and the country’s stress levels are among the highest in the world. Relatedly, take note of a small symbol that may, in fact, overwhelm every other clue. In a small residence inside a Brazilian favela, I saw a flower in a cup inside a beer can on a shelf. In a gritty environment, it stood out as a badge of hope.