Your Data-Driven Marketing Is Harmful. I Should Know: I Ran Marketing at Google and Instagram

I didn't know it at the time, but I was about to join my very last "performance calibration session." This was late in 2018, when I was a managing director at Instagram, and these sessions had been a common part of my life -- just like they are at many big companies. They're a time for senior managers to discuss the performance of their individual team members, applying common organizational standards across job levels. HR specialists moderate performance discussions on a biannual, sometimes quarterly, basis. Conceptually, there's nothing all that weird about calibration. But that's conceptually.

Doug Chayka

I have held senior-level marketing roles at YouTube, Spotify, Google, and Instagram, so I've sat in on a lot of these. And the reality is this: A group of highly opinionated, often outspoken managers get together in a room shielded from prying eyes. Most managers gather in a physical conference room; others dial in by phone or video, making it nearly impossible for everyone to weigh in equally. The HR representative says a few obligatory words toeing the company line, and then the verbal battle swords come out. For the next several hours, we go around the room, screens, and phone lines making the best case for why one manager's team member deserves an "exceeds expectations" rating ("She's a rock star!"), while another's should be a "meets expectations" ("He's solid but hasn't gone to the next level") or, worse, a dreaded "meets most expectations" ("Her peers sometimes find her difficult to work with"). During one particularly memorable calibration session at Google, a young man's rating was under scrutiny because his manager argued that this employee needed to "grow a pair of balls."

Every so often, HR will step in to suggest that the group bump a few people down because we're aiming to hit a normal distribution of ratings. We're not looking for a perfect bell curve -- very few people are rated at the lowest or highest ends -- but the bell can't be too top-heavy. Although positioned as an objective method to evaluate employee performance, I have found calibration to be an almost entirely subjective experience, with sometimes dire consequences. One below-average rating means less bonus money; two in a row triggers a performance improvement plan that routinely ends with getting fired.

But I'll be honest; for years, these problems never really sunk into my brain. I was a devotee of data. That was the best way to reach customers, I believed -- and, naturally, that meant it was the best way to manage employees as well. Data was core to my Ph.D. work and the thing I dedicated my career to. And even when I was emotionally shaken -- a moment, only a few years ago, when I lost my father in a tragic and haunting way -- I reacted by submerging myself even further into a data-driven, analytical, emotion-free world. That space just made more sense.

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But during this performance calibration session, something inside me started to crack. I had a thought: By plotting performance on a normal curve, we're treating people as data points, not as human beings. I had been videoconferencing into this meeting and felt an urge to leave it. So I turned my camera off. I sat and thought. It was unclear how much time had passed when I turned the camera back on to rejoin my Instagram colleagues. I stared into the lens, past the lens, to see the looks of silent victory or resignation on the faces of my peers, most of them crammed around a small conference room table in Menlo Park, Calif., nearly touching elbows. I had entered a rare moment of silence, as if everyone were leaning in to hear the barely whispered secrets of the universe.

And that's the moment when I knew I was done. Done with Instagram. Done with the career that I had been building for the past two decades. Done with the notion that turning everything into data -- especially human beings -- is anything other than personally and professionally damaging. It was time to do better.

At the age of 20, like so many college students, I was in search of some kind of "truth." Math and the harder sciences lay outside my mental wheelhouse, so I settled on cognitive psychology, with a focus on language and reasoning. This was a bull's-eye on people skills, but backed by brain biology and a heap of statistical analyses. I became enamored with the vernacular of objectivity. People who participated in my experiments became subjects. To get published in the field, I was instructed to be in constant pursuit of statistically significant results. I learned how to run t-tests and ANOVAs and other math-y things that allowed me to abstract away from the individual in order to talk about populations. This was a version of truth I could identify with, and I was hooked.

After college, I entered a graduate program in psychology. I found new ways to experiment on subjects. By the time I was 26, I had earned my master's and my Ph.D. Then I went into advertising, where I was something of a corporate unicorn -- the guy with a Ph.D. in quantitative psychology who employs a data-driven skill set to help sell mainstream products like Cheetos and Slim Jims. I found this intoxicating, but I wanted even more. So after a few years at ad agencies, I made the leap to a marketing role at YouTube, and later to Spotify. With their well-known missions to organize the world's information in different ways, there seemed to be no better space for someone infatuated with the hunt for truth and objectivity.

I joined YouTube in 2011, and my timing was good. I'd been invested in data-as-truth for a long time, and suddenly data became the central currency of corporate America. Topics I had delved into as a doctoral candidate -- A/B testing, artificial intelligence, rational versus emotional decision-­making -- became mainstream business parlance. Everyone began talking more excitedly about adopting data-driven approaches to everything, and I watched as leaders across industries started to demand increasingly more data in order to inform -- and, in many cases, guide -- critical business decisions.

The field of marketing in particular has embraced the quantitative mindset. In part, this is due to a correction of the "Don Draper" era of advertising, where big, transformative ideas materialized toward the bottom of a martini glass. There's a logic to this: Marketing used to rely upon the whims of a few, but now we have the technical capacity to understand the interests of the many. And that, in turn, has enabled us to track and calibrate exactly how people react to different messages -- a perfectly reasonable interest for any business. Then this capability was democratized -- Facebook and Google, along with other technology platforms, have made it famously easy for any business to target people down to an exact science.

These massive digital advertising platforms quickly changed what it means to be a successful marketer -- it's no longer about establishing real, human connections with people as customers, assuming that was ever the goal. Today, the Holy Grail of advertising can be framed as personalization meets attribution. This is the mechanical process of delivering highly relevant and valuable communication to customers (personalization at scale), and then understanding in great detail the impact and result of that effort while gleaning new insights (attribution). That's why it seems like just thinking about buying a new pair of pants can result in chinos following you around the internet until you're beaten into clickable submission. Data drives statistically significant results.

I got this. I built new tools and strategies to optimize it, and I saw a return. And then: My own data set changed.

Coming back home from a work trip, just before wheels-up takeoff, I received a call alerting me that my father was in the hospital. He had been found in his suburban backyard that morning suffering from two critical blows to the head -- and there was no chance he would recover. Dead. Murdered? It appeared that way, although there were no witnesses and not enough evidence to know for sure. He was gone by the time I landed, and I had absolutely no clue how to process the noxious human cocktail of denial, anger, sadness, fear, and unabashed grief.

I took to the task of managing these emotions like an unflinching robot. I ate up the procedural minutiae as a proxy for feeling anything on a human level. There wasn't much conscious about the shift, but I reverted to seeing the world as divided objectively into two parts. There was the task of conquering the soul-sucking tactics of sudden loss, and there was proving to the world that nothing -- not even a tragedy -- would stop me from blindly achieving. The idea of pouring myself into work came so naturally that I never once paused to think about it.

This didn't make me an especially pleasant colleague. I was fired from Spotify. Then I went to Google, and onward to Instagram -- a believer in data as a corporate strategy but also, personally, as a method of separating work from my humanity. I wasn't ready to blend the two.

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But then I realized that this is exactly what we must do if we're ever to succeed in business (or, for that matter, in life). We'll never really reach people if we just focus on their output. We'll never build truly great, resonant brands if we don't connect with people as individuals. So to start, I quit Instagram.

After corporate life, I did what anyone in a career crisis does: I worried. Then I relaxed and traveled a bit, discovered the value of sleep, and enjoyed quiet mornings that didn't begin with an overflowing inbox. I learned that there's more to this world than the narrow band I'd been laboring in. I started speaking with others who felt stuck or were looking to make change. I confronted the issues I had put off; I properly grieved for my father and started, slowly, to learn how to talk about it with others. And then I tried to find my new place in this world. Which meant starting with new ideas.

As an oversimplification, I've come to think about business activity -- spanning departments, companies, even entire industries -- as running along a two-dimensional axis. On one end lies the operational, tactical, or transactional aspects of how organizations get things done. In marketing, these are activities like making a piece of advertising, running a story through a PR outlet, creating customer experiences, or deciding how and when to run a promotion. These, and other transactional activities, are tactics we can easily measure to tell stories about why what we're doing is working or not.

On the other end of the axis lies the foundational elements of how a business runs. For all organizations, this is about spending the time to craft or revisit the authentic mission and vision of a company, the core values the company holds, and how that business is positioned for greatness in the world beyond just the top and bottom lines. This work is based on telling human stories that resonate emotionally, not just rationally -- ­and, clearly, this type of foundational work is much harder to measure. And that makes it harder to think about.

All points along this transactional-­to-foundational axis contribute to the success of any organization, but corporate obsession with Big Data has made it far too easy to ignore the foundational elements of business entirely. After all, it is so much easier to focus on measuring KPIs and crafting stories about success by exceeding agreed upon, but often arbitrary, metrics.

For a long time, I simply didn't see this as a problem. Who needs emotional resonance when you have metrics? But once I stepped outside corporate life and started looking at business as a regular, feeling, grieving, unemployed consumer, I started to really appreciate the disconnect.

When businesses ignore the foundational elements of relationships, it can result in failure of epic proportions. Across the past few years alone, the marketing world has offered a constant string of cautionary tales. Pepsi launched an expensive ad starring Kendall Jenner in 2017 that had nothing to do with Pepsi's mission or core values; in the same year, Audi ran a Super Bowl ad talking about empowering young women, but its entire board consisted of older men; and just recently Gillette produced an ad aimed at tackling toxic masculinity without any regard for how it made its core customer -- men -- feel.

These all made news, and they were discussed as boneheaded missteps. But I know what they really are. They're cases of blindly embracing data ("Fifty-two percent of people say a brand needs to stand for something bigger than just its products and services"), without much recognition that there are humans on the other end, and that those humans have finely tuned bullshit detectors. This is what happens when organizations execute without clearly defining or aligning to their operating system, which comprises such foundational elements as the core reason why the company exists (beyond making money), why it does what it does or makes what it makes, and how it goes to market and positions itself to the world.

But this is exactly the direction we need to head in if we want to thrive in business and, more important, as human beings.

Today, I consult. I know, I know -- it's clichéd and expected: the man who left corporate life and now serves his old masters in new ways. But I find it satisfying in that I can now walk into data-driven places and say, Stop.

In corporate life, we are tempted to separate human emotion from business practice, just as I separated data from humanity for most of my career. But I have come to realize that the line between these things is completely arbitrary. Drawing a stark distinction puts us at a big disadvantage as businesses and as people. I hope I'm not alone in thinking this, and perhaps I'm not. In the summer of 2019, it was heartening to see executives from the Business Roundtable assert for the first time that companies need to invest in the well-being of customers and employees rather than focusing solely on shareholder value. We'll see how committed they truly are to doing that. But it is, if nothing more, a good way to start the conversation.

Related: Your Data Is Useless If You Don't Have a Management Strategy

The reality is that marketers have long understood the need to build and foster meaningful emotional connections between businesses and customers. The quality of these connections helps to define the world's most iconic brands. But as technology, data, and metrics have moved to the forefront of corporate discourse, the context in which to establish these emotional relationships has changed. The net result of the connected world is that people are producing more signals about who they are, what they talk about, and the things they like. So the temptation -- ­one I understand all too well — is to move away from individuals and to look for human patterns in the tangled web of data. There is value in doing that, of course. I'm not saying that advertising is pointless, or that targeted marketing doesn't work. But I am saying that you can't confuse those tools for what it means to build relationships with humans.

So how do businesses do the more important work? First, they need to acknowledge that there are living, feeling human beings at the beginning and end of every transaction -- and that a shift in thinking must be employed to really build emotional connections with their customers. For example, I've started to think about how businesses can construct a "business relationship arc" to help simplify their marketing goals.

Whenever a person interacts with a brand, they experience milestones or feelings. It's exactly like how they first interact with other people. At first, a consumer will only know that a brand "exists" -- they see it, maybe they try it and form some early opinion about it, but that's it, just like meeting a new person at a party. Over time, the relationship can develop. Consumers will attach deeper meaning to some brands, or will think about them in certain ways, or will attach some new meaning to the brand. Now the business relationship arc is developing. Things get interesting as they move further up the arc, where customers might incorporate a business or a product into a part of their lives, or think of the brand as something that shapes or defines them. Very few companies (or people!) are able to take the relationship beyond that, to a place where they are indispensable and would be forgiven no matter what happens. But it's possible.

Successful companies are the ones that find ways to move people up the arc -- to go from merely existing to being something people care about, and then something they'll defend. This requires thinking about what moves people as humans, not just what motivates them as groups.

Businesses also need to establish what I call their "brand operating system." In technology, operating systems support basic functions that enable more complex tasks to happen. Similarly, for companies, a brand operating system is what delivers a clarity of purpose to inspire and catalyze the potential, power, and humanity of any business. At the heart of a company's operating system is a core brand essence, a central idea. It's what the company is about -- and it's an internal thing, not a tagline or campaign.

At Nike, for example, there is the central belief that "if you have a body, you are an athlete." This is at the heart of who Nike is, serving as a north star for how it operates and communicates as a company. With that in place, Nike can build a holistic operating system that includes details about why the company exists, what it's trying to achieve, the distinct value it offers to its customers, fundamental beliefs that provide norms for how it makes decisions, and the collection of characteristics that represent the style in which it communicates. These are precisely the ingredients that make us unique as individuals, and they are essential to building companies that mean more to people than just the things they make and sell.

Belief is at the heart of any company's OS. But belief can't be established without good leadership. So here's where a business turns inward -- where it takes its philosophy on reaching customers and applies it to its own employees. Data got us those "performance calibration sessions." But a focus on humanity can get us somewhere else entirely.

Many employees, across all levels, care about what they do beyond a written job description. They might not do everything well, but they double down on their strengths, building successes from the things they're good at. Performance calibrations, as I've experienced them, are rarely about identifying or evaluating strengths. They seem designed to weed out employees who defy expectations or who don't check off all the mandatory boxes, arbitrary as they may be. There has to be a better way to get the most out of a human workforce.

So consider the advice I was given years ago. Originally meant to apply to qualities of leadership, I think the sentiment is best applied to how we can nurture human talent in the workplace and in daily life, beyond any traditional evaluation methods: Big or small, have a vision. People need to understand why you get out of bed in the morning. Then, discover and describe the passion in that vision. If you don't really care about what you're doing, neither will anyone else. Vision and passion fall on deaf ears without persuasion -- the ability to get others on board. And most important, embrace humility. This means bucking against the trend -- fueled by data -- of committing to being right and defensively closing yourself off.

Humility means being curious about other people, being open to what they offer, and realizing that we all have a lot to learn about what makes us tick. It took me a while to get there. And now, I believe, this can go a long way in allowing us to treat each other properly -- not as data points, but as fellow human beings.