The Naked Future

by Patrick Tucker

  A screenplay, too, is a machine that is part of a larger apparatus. It’s no wonder we often refer to characters, tropes, and plot developments as devices: they are precisely that. Once the screenwriter has undertaken a wide number of decisions, several readers must then decide whether to pass the script along up the ladder (not without some personal cost) or to kill it. At the pinnacle of the long, strange dance known as the green-lighting process, a studio makes a grand choice about a project and all the other decisions that project entails. A new machine is set in motion, that of production and release. Once it’s concluded, the budget has been allocated and spent, the actors have made their way across the set, the helicopters demolished, the gratuitous nudity edited out (or in), the marketers have done their marketing, the result is presented to the moviegoing public at movie theaters around the world.

  And there stands Jehoshua Eliashberg. What he offers is nothing more than a view, a set of inputs to change the decision-making process, a feedback mechanism. Hollywood, video-streaming services, and moviegoers are presented with a new choice: whether or not to listen.

  CHAPTER 6

  The Spirit of the New

  THE lobby of the Saatchi & Saatchi building in downtown Manhattan prominently features three enormous multimedia paintings by Frank Stella. They explode off the marble wall in a shriek of color and movement. These were procured in the 1980s during the financial peak of the New York art scene. The ’80s also marked the apogee of American advertising, and the building’s namesake, the Saatchi & Saatchi firm, occupies the top floors.

  The view from the company’s office is clear over the Hudson River. The waiting area is sleek and modern. When I arrive I discover a handful of young, attractive executives in a meeting room. They’re judging radio spots. The men wear V-necks beneath their tweed sport coats. Their tapered, skinny jeans descend toward canvas shoes. Everything about this scene, and the people in it, suggests a bright present branching toward a better future. Probably no organization in the world understands the value of appearances better than Saatchi & Saatchi, and so it’s not surprising that the first thing a visitor to their offices will encounter is a subtle advertisement for the firm itself.

  Make no mistake, the company’s wrinkles have been Photoshopped away and Saatchi & Saatchi is running on borrowed time.

  I meet Becky Wang, the company’s director of insights and analytics. Wang uses market research; Facebook and Twitter posts; cookie, click, and app data to help Saatchi create better marketing campaigns. Some of these ad campaigns still come in the form of one-way ads to generic customers during football games, in magazines, on the radio. These are just a bit smarter than they were ten years ago. Other messages don’t fit with the classic definition of a commercial at all. They’re Web and iPhone apps, tailored promotions, and digital interactions that collect information as much as they pitch specific products.

  Becky Wang, her clients, and the other smart folks trying to sell things across the digital landscape know that the latter—apps and interactive sites that cost little to create—are becoming more important to clients than TV spots that can run into the millions.

  “The advertising industry was starting to move behavior, but we used to think that if you told someone something and evoked some sort of emotion, that was enough. We now know that’s not the case,” she says.

  The premise of traditional advertising is that exposing consumers to your product or brand repeatedly through pictures and images will get them to buy it. This is a flawed perception. A 2010 McKinsey study of twenty thousand people showed that the process by which consumers discover and develop an appetite for new goods is now circumventing such traditional outlets as radio, television, and magazines.1 Today, consumers hear about new products through targeted online ads, searches, and friend recommendations.2

  The study also found consumers walk around with a broad familiarity of all sorts of brands all the time. We know what Coke, Samsung, Apple, and American Airlines are and what they do. Therefore little commercial reminders about the existence of American Airlines can be a nuisance. It’s only when consumers enter into a state where they’re actively looking for a product, when they’re “in the market,” that advertising actually brings the consumer much closer to pulling out her wallet. This underlines a fundamental dysfunction in traditional advertising. A Super Bowl spot can’t measure whether the audience is actively looking for the product being pitched. Chief executive officers are growing increasingly fed up with throwing money at marketing and ad firms. Two-thirds of the CEOs polled by the Fournaise Marketing Group said that they doubted the efficacy of traditional marketing and felt there was no clear connection between ad spending and sales.3

  CEOs showed that they felt like they were investing in ad campaigns but there was no way to track with precision how those campaigns were bolstering the bottom line. That may not sound like a new predicament for marketers and advertisers but today CEOs who want to break up with Madison Avenue have alternative places to invest their money. The idea that big data poses a threat to traditional marketing practices has been so widely accepted that software firms such as Adobe use it to actively market their big data solutions to marketers.

  In his 2011 book The Daily You, communications expert Joseph Turow documents exactly how the decline of traditional advertising began almost unnoticeably in the 1990s when more and more content providers such as newspapers and magazines began going online where engagement could be tracked through click-throughs, rather than speculated on via circulation or Nielsen ratings. But the single biggest factor in the death of the Mad Men model was the rise of the cookie, a little piece of software code that embeds itself on your computer and records your movements around the Web. Thanks to the rise of such integrated ad networks as Yahoo!, personalized ad delivery platforms such as Google’s AdSense program, and data-exchange companies, ads now follow you from site to site and collect information about you as you go. It’s the cookie that enables Google, Yahoo!, and Facebook to show you ads for vacation homes in Florida because you once looked at the South Beach, Florida, page on TripAdvisor.

  Turow calls this the “decoupling of audiences from context.”4 One effect of this decoupling is that ads that transmit a carefully conceived and constructed image in one direction, the sorts of images and campaigns that built the Saatchi & Saatchi fortune, have become financially less attractive no matter how pretty those pictures are to look at. When Saatchi receives less money for photos of Jennifer Aniston holding Louis Vuitton handbags, magazines charge less money for ad space, both in print and online. That means they have less money in general for reporters, fact-checking, and making product.

  Today, magazines such as Wired, the Atlantic, and my magazine, the Futurist, deliver important stories and beautiful photos in an online environment even faster and better than we did in print. Unfortunately, it doesn’t matter; as an editor, you can invest the last of your budget in an eight-page piece on aquifer depletion but when the reader moves away from your Web site to go look at Tumblr blogs of cats in Halloween costumes, the ads follow her. Why should a company buy an ad at one location when it can buy access to a person’s attention virtually anywhere?

  The migration of content from print to the Web is not a good thing for anyone who cares about great journalists doing good work. But the shift is a positive one if you’re a company interested in acquiring lots of behavioral data about where online your present and future customers go.

  Advertising is just one of several components that drive product sales. The others include price, placement, demand, and the quality of the product itself. All the gears have to be working in concert for a sale to happen. But the amount of information about how those components interact is exploding, which is changing how clients value creative firms like Saatchi & Saatchi.

  “We’re no longer held to one basic metric like how sales or market share improve” as a result of an ad campaign, says Wang. It’s
a change she welcomes. Advertisers, she says, have long felt they get the blame for things they can’t control, how products are designed, placed, and priced. Today, “We’re held to how much time customers spend on site or with brand. If I have three hundred thousand moms actively using an app that becomes a success metric, I’m no longer beholden to something I have no control over.”

  One example of a product that reveals the importance of time with brand, as opposed to sales, is rap artist Jay-Z’s album Magna Carta . . . Holy Grail. Electronics giant Samsung partnered with the artist to promote the release, scheduled for July 4, 2013. Samsung, which makes the Galaxy S4 smartphone, announced they were going to give away downloads of the album to the first million individuals who downloaded a free app for the phone. At first glance, this would seem to be an extremely generous move on the part of Samsung. The music industry may be in a shambles but surely Jay-Z can still sell a million downloads on the opening week of a new album, so Samsung was leaving money on the table, right? Sometime between downloads one and five hundred thousand, Atlanta rapper Killer Mike took a look at the terms of service agreement for Android users, which stated that the Jay-Z Magna Carta app needed access to the phone’s system tools, network communication records, phone calls, GPS location, and more. This prompted Gawker writer Adrian Chen to ask, “Why does Jay-Z need your GPS location? Is he going to cruise by on a platinum-coated jet ski, personally chucking out copies of the album to people who downloaded the app?”5

  Jay-Z naturally has no interest in your location; marketers working with Samsung do. Another example of how continuous user data is becoming more valuable than a one-time product sale is Nike+, a self-tracking system much like Fitbit. It allows you to create individual data streams of your activities. You learn about how you run, what conditions work best for you, and you can compare your scores with those of your friends or people around the world. If you go in for all the available Nike+ merchandise it becomes an expensive system. There are wristbands, clips, and the cost of constant upgrades. Not surprisingly, Nike wants people to interact with the system as much as possible, so the company created a set of little games in which people could take part. They can compete against their own scores or against other people with Nike+ watching to see how, when, and how often people use the Nike+ system.

  Nike learned that people who didn’t take challenges didn’t continue to use the shoes. Suddenly, selling the Nike+ system wasn’t enough anymore. The company also had to sell consumers on using it the right way, in the way that gave Nike actionable data and encouraged customers to use the product continuously, to make a new habit of it.

  For an advertising company, pitching the right way to use a product such as Nike+ isn’t necessarily easier than pitching the product itself. People don’t adopt new habits simply to suit sports apparel manufacturers. Habits, even the ones we don’t like, are personal. “We are what we repeatedly do,” said Aristotle. But information about what we do is now part of our digital trail and thus our naked future. For advertisers, understanding those often repeated behaviors is the first step toward changing them.

  In March 2011, before Wang joined Saatchi & Saatchi, she collaborated with Drew Breunig, a young technology director at a data analytics group called Annalect, on another project. The client in that case was an antismoking group looking to discover what sorts of conversations people were having on Twitter about tobacco, and whether those conversations could be used to predict something specific about smoking behavior.

  “We created an entire dictionary of smoking-desire statements, like ‘Man, I really want a cigarette right now,’ or smoking-consumption statements like ‘I’m having a cigarette outside,’” says Breunig. “We counted all the synonyms, all the different statements that would fill up this dictionary.” They wound up tracking consumption of a whole host of compulsive substance habits, not just smoking but also alcohol and caffeine intake. When Breunig and Wang applied the dictionary to a large data set of tweets from New York City, they found that Monday through Tuesday on weekdays, coffee drinking would peak and go down right around two o’clock in the afternoon. Alcohol consumption would start around seven o’clock, peak at about ten, and fall off a cliff at two in the morning.

  “Cigarettes were the liminal vice,” says Breunig. They came between consumption of coffee and alcohol. When it was too late in the day to have a morning cup of joe, people tweeted that they were grabbing a smoke and then, later, that they really needed to try and quit smoking . . . while they were smoking, outside a bar between one and two in the morning.

  For an advertiser looking to place a digital ad across an ad network at a particular time, that’s extremely useful information. “If I can predict you’re a smoker, I can predict that you’re going to have a craving during weekdays, right when it’s too late for coffee. So if I’m the [antismoking group], and I want to help people not be smokers, I’m going to buy every banner ad I can in that time slot and these ads will say, ‘Hang in there, man,’” says Breunig. It’s a good thing Drew Breunig’s clients wanted smokers to quit.

  Surprisingly, data-driven marketing didn’t begin in the Internet era but long before. To understand how we got to this particular point, where communications scholars are writing eulogies for advertising firms and start-ups are predicting when you will want a cigarette, you have to go back several decades.

  The future of advertising resembles its past.

  What Happens in Vegas Will Follow You Everywhere

  In the mid-1990s Gary William Loveman found work at Harrah’s casino chain where, in just a few years, he changed the industry forever. With a PhD from MIT’s Sloan School of Management and a résumé that included work at the Federal Reserve Bank of Boston, he could have gone anywhere. But at Harrah’s (now owned by Caesars) a brilliant quantitative mind saw a field full of low-hanging fruit. Loveman was not a creature of Las Vegas but an analytical anti-gambler, a man with a deep suspicion of hunches. The customer-service-driven casino environment offered the opportunity to apply his quantification mind-set to an area dominated by big personalities, intuition, and instinct. “There was very little formalization of service as a discipline,” Loveman told Karl Taro Greenfeld of Bloomberg News in 2010 (emphasis added).6 “There is a long history of research and engineering around factory optimization, scheduling, and throughput. On the other hand, the service sector was seen as a poor cousin.”

  The Las Vegas casino business model before Gary Loveman was built entirely around the concept of bigger: bigger signs, bigger fountains, bigger volcanoes and attractions visible from the Strip, bigger names on the marquee to pull people in, bigger lobbies, more of everything. In the fight for flash Loveman saw a war not worth winning. He turned his focus to the job of remaking Harrah’s utterly unglamorous customer loyalty program, transforming it from a simple thanks-for-coming voucher scheme into a massive, data-run, telemetric decision engine.

  Loveman didn’t invent the customer loyalty program; the airlines did. In 1978 the U.S. airline industry was deregulated, big carriers expanded their routes and slashed their prices, and a vast frontier was suddenly open. American Airlines relocated to the Dallas–Fort Worth area the following year, where an executive quickly realized that the company could offer lower-price fares for the customers that used the airline most often. But finding these people was no easy task. Fortunately for American Airlines, they had one of the world’s biggest computerized databases, the Semi-Automated Business Research Environment (SABRE). SABRE allowed travel agents and American Airlines’ clerks dispersed around the world to book passengers on quickly filling flights in something like real time. In what might be considered the first case of a major company using a computerized database for customer profiling (outside the insurance industry), American Airlines scanned their database to figure out who were their 150,000 best customers.7, 8 These people became members of the world’s first computerized customer loyalty program, AAdvantage, in 1981. (Frank Lorenz
o, Texas International Airlines CEO, came up with the first frequent-flyer club in 1979, but this small airline lacked the computer resources of its larger competitors.) After the official launch, other big airlines developed their own programs within a matter of days. These soon included not just deals on airfare but also rental cars and hotels in such trendy spots as Las Vegas, Nevada.

  Loveman took what the airlines had been doing for decades, and was in place already at Harrah’s, and perfected it. In 1998 he created the Harrah’s Total Gold program, today called Total Rewards. Here’s how it works: when club members book their hotel or restaurant reservations, when they swipe their Total Rewards club card in one of Harrah’s video slot machines or use their Harrah’s account to place table bets, when they win, when they lose, when they hesitate, when they cash out, feel the itch, and come back to hit the one-armed bandit one last time on their way out of town, the system knows . . . and remembers. But the database is more than just a play-by-play record of plundered 401Ks. Customer service reps both in the casinos and at call centers around the world look to learn everything they can about Harrah’s Total Rewards members to tailor very specific offers to them.

  It’s not cheap to collect, keep, and utilize all this data. Harrah’s reportedly spends more than $100 million a year on IT, but Total Rewards has more than earned its investment back. What started with 12 million subscribers in 1990 hit 26 million in 2003, more people than the combined populations of Greece and Portugal. By 2010, 40 million people were in Harrah’s system. This gives the company access to the lives of the people in its casinos. Instead of rigging the table games, the system works to rig the customers.9