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Ride the Wave

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In The Mechanical Bride, the Canadian media theorist Marshall McLuhan mentions the Edgar Allen Poe short story “A Descent into the Maelstrom.” The story involves a sailor recounting how he and his brothers got caught in a violent whirlpool at sea. As the sailor was being swallowed by the whirlpool, he looked around and noticed a few objects drifting to the surface. They were small and cylindrical—barrels and mast poles, for example—so he fastened himself to a cask and jumped overboard. Sure enough, by riding the current of the whirlpool instead of resisting it, he slowly rose to the surface and survived.

The behavioral science community tends to think about the mind as a press secretary, as if to say that our first-person reports are unreliable stories. In advertising, the goal is not to dismiss and circumvent our stories. Much like the sailor who escaped, it is to observe and exploit them.

Dumb Data vs. Smart Questions: The advantages of asking the right questions in an age of predictive analytics

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In 2012, New York Times reporter Charles Duhigg wrote a story about how Target used transaction data to create a pregnancy-prediction model. When the model predicted one customer was pregnant, Target promptly sent coupons for baby clothes and cribs. The only problem was that the customer was in high school. According to Duhigg, the dad stormed to the local Target to complain about the coupons but when he returned home, the daughter confessed. The model was correct.  

We’re living in an era in which brands use our data to anticipate what we need next with alarming precision. And yet, there’s one problem that our data can’t fully solve. Like a politician, a brand has a reputation to maintain. It has to design images and messages that charm and persuade. While it might seem like brands are using our data surreptitiously, one of their primary tactics—advertising—is plain to see. 

Last fall, a major retailer approached me with an interesting question. They were redefining a customer segment and needed help with some research. They knew how old, wealthy, and educated the segment was. Most consumer-facing brands have access to this kind of information. It’s not precise and it doesn’t need to be. The idea is to divide a customer base into a few big segments. 

However, if you’re a consumer-facing brand, you need something more. You need to observe something that your customers feel but have yet to consciously acknowledge. Then you need to broadcast that insight back to them. A great ad is not meant to move you off the couch and into the store. The goal is an involuntary head nod—the subtle “I get it” gesture.

The question my client asked me was: “What are our segment’s top ‘stress drivers’?”

When I sat down to draft a few survey questions, the first thing that came to mind was money. I knew from previous research that most people stress about not having enough—even people who have plenty. The client knew that. Like most retailers, their business was built around this central theme of consumer life.  

The next thing that came to mind was work, and then relationship problems. Writing survey questions is difficult. Some behavioral scientists compare the self-reporting mind to a press secretary and the brain to the oval office. A survey doesn’t have access to decisions that happen in the oval office. You can get a clue if you ask the press secretary the right questions. But you have to be clever.

I started with something I knew and argued outward. I imagined walking up and down the aisles of a store. For me, shopping comes with a dose of low-level stress and I wondered how many people were like me, so I jotted down a question: “When you’re shopping in the store, do you normally feel like you’re in a hurry?” Everyone had to pick: “Yes or No.”

Next, I noticed that my low-level stress doesn’t have an object. When I shop, I don’t really have a reason to be in a hurry. I jotted down another question. “When you’re shopping in the store, are you normally late for something? Yes or No?”

I shared these questions with the client who was initially hesitant. Most market research surveys are long and filled with questions that measure stated preference such as “What’s important to you when choosing a retailer?” and “How many hours a week do you spend shopping?” My survey was about 90 percent shorter than the surveys they normally conducted. It wasn’t obvious what it was measuring.  

Luckily, the client liked the idea and made a great suggestion. They pointed out that some people would say “yes” to the first question about feeling in a hurry and “no” to the second question about being late for something. For this group, they recommended the logical follow-up: “If you’re not typically late for something, why do you feel like you’re in a hurry?” It’s a great question because it catches the press secretary off guard.

When I analyzed the data, I found that about 30 percent of the respondents admitted that when they shop they feel like they’re in a hurry—even though they usually have nowhere else to be. When prompted to explain why they felt so rushed, this group responded with a variety of answers, each of which we categorized and then used to create a list of “stress drivers.” We found that some people shop during the day and can’t be late getting back to work, some rely on drivers who idle in the parking lot, and some have family members waiting at home. Some just don’t like shopping and some get anxious in crowds. Just about everybody dreads waiting in line. And then there’s the kids, which were universally described as ticking time bombs. For parents with small kids, a shopping experience is one tantrum away from an early exit.  

Customers in this group liked the retailer—they even preferred it over competitors, according to our research. The problem was that despite being filled with friendly employees, the store was getting in the way of something else going on in their lives. They didn’t expect the retailer to solve their problems. I imagine that they just wanted their problems acknowledged.

Duhigg’s juicy anecdote about Target’s pregnancy-prediction model is probably false. Many people on Target’s mailing list receive such offers—you just never hear about all the women who received the coupons who weren’t pregnant. In the digital era, Duhigg’s fabricated story offers a shift in perspective. Don’t ask, “How are brands using my data?” Ask, “Do brands know the right questions to ask about me?”

The media theorist Marshall McLuhan observed that agencies are trying to make “effective contact with a genuine feeling.” He urged us to see ads as more than a means of manipulation. Like a poem, book, or film, ads are simply participating in the “perennial flow of perception and impulse from the few to the many and from the many to the few.”   

The research we conducted will eventually make its way into this perennial flow in the form of more images and messages. I hope a few customers will see them and react with an involuntary head nod. 

Photo Credit: https://www.flickr.com/photos/sixthlie/

Is Rory Sutherland’s Wedding Invitation Analogy a Good One?

In an article published last summer in New Statesman, Ian Leslie, a writer and veteran of the ad industry, points out that a brand’s message can be far more powerful when it is visible to large groups of people at the same time—the Super Bowl or Times Square, for example. The creatives at ad agencies know how to take advantage of these shared moments to help brands. Whereas, as Leslie puts it, the engineers at Facebook and Google tend to conceive of ads “as a mere conduit for information about the product.”

According to Leslie, Rory Sutherland, Vice-Chairman of Ogilvy & Mather, compares viewing an online ad to receiving a wedding invitation by email. If ads really were just a “conduit for information” then it wouldn’t matter if a wedding invitation appeared in your inbox or your mail box.

But it does matter. Mailing is more expensive than emailing. And as every bride or groom knows, look and feel are powerful things. You get a pretty good sense of what kind of wedding it is going to be the second you glance at the envelope, well before you’re exposed to the actual information.  

Rory is right—the medium is the message. But his point might be too theoretical to provide ad agencies with a way to win back profits from tech giants including Facebook and Google, each of which now “has a market value exceeding the combined value of the six largest advertising and marketing holding companies,” says media commentator Ken Auletta in The New Yorker.   

Does receiving a wedding invitation via email really change how you feel about the wedding? Do you remember what the last invitation you received “felt” like? Is a Super Bowl ad worth it?

For decades the value of mass market ad campaigns has been assumed. But with the rise of data rich tech companies—and their unchallenged ability to show how we click and buy—the burden of proof has shifted. As one of my tech friends said to me when I was trying to convince him of Rory’s analogy: “I’ll believe you. Just show me the data.” 

I’ve heard Rory make his email analogy a few times—first in his entertaining presentations and then on an essay for Edge.org, a website dedicated to contemporary intellectuals and scientists. When I encountered the email analogy in Leslie’s article, I figured that it would be a good idea to test it.  

So that’s what my team and I did. We recruited a few hundred participants online and randomly separated them into two groups. The first group saw an image of a wedding invitation and the second group saw the same image embedded on a mock Gmail account. We told the first group, “Imagine receiving this wedding invitation in your mail box.” We told the second group the same thing but changed “your mail box” to “your inbox.” We asked both groups a question inspired by Rory: “What are the odds this wedding will have a cash bar?”

We found that the average result from each group was nearly identical—just around 50 percent, suggesting that people took one look at the invitation and randomly guessed.  

We decided to conduct a follow up experiment. We recruited another group of participants and asked a different question: “How would you judge the overall quality of this wedding?” This time, we found that participants who received the invitation in their inbox judged the wedding to be of worse quality.

The effect was small. But that made it interesting. Based on the data we could better estimate what a bride and groom stand to lose if they send their invitation over email. When you think about all the moments before a wedding that contribute to your expectation of it, from the save-the-date card to the choice of registry, it’s easy to see how small impressions add up. They color an experience in a way we rarely notice.  

As Rory says, “10 percent of advertising is information. The rest is inference.”  

Leslie ends his article with a quote from the French philosopher Gilles Deleuze: “It is not the slumber of reason that engenders monsters, but vigilant and insomniac rationality.” Leslie’s point is that the tech nerds who design our smartphones and engineer our social media feeds are indifferent to the concept of a brand. To them, shopping is an engineering problem. The goal is to “identify the precise moment that a consumer needs something so that it can trigger a sale.”

In 2013, the feminine hygiene brand Always launched the “Like A Girl” campaign. The T.V. commercial featured people of all ages interpreting the phrase “like a girl,” as in “run like a girl”, “throw like a girl” and “fight like a girl.” In the first few frames, the camera shows girls entering puberty who flail their arms unathletically after being instructed to “run like a girl.” Then the camera shifts to younger girls who had not been alive long enough for the link between the phrase and running style to solidify. So, when one of the younger girls was asked by the director “What does it mean to you when I say ‘run like a girl’?” she responds, “It means run as fast as you can.” She proceeds to sprint around the studio enthusiastically, uninfluenced by a stereotype that instantly feels outdated.   

Brands work on us. When Listerine famously placed a label “halitosis” on “bad breath” they didn’t pressure people into believing that their breath smelled bad. They convinced everyone that their friends thought their breath smelled bad and weren’t speaking up—hence the gossipy taglines “If your friends were entirely frank with you” and “They say it behind your back,” which appeared in the 1920s.

But how does that process work? How does a brand become part of common knowledge? These are the questions ad agencies spend their time thinking about. They study how people use brands to broadcast signals without consciously acknowledging them. They learn how to interpret and then redesign those signals. They know that advertising works not by preying on our emotions but by “changing the landscape of cultural meanings, which in turn changes how we are perceived by others when we use a product,” says software engineer Kevin Simler in a blog post.

The digital revolution is strange. It designs interfaces that make it easier for us to get things we want. Good design in this view is targeted and invisible. In the “Like a Girl” campaign, the opposite is true. Your thinking is interrupted. Your beliefs are addressed. A social norm is challenged.  

Like a wedding invitation buried in a pile of mail, a great ad momentarily interrupts mindless routine to create an impression. It stands out. It draws you in. It’s not invisible.

I’ll never fully convince my friend of Rory’s analogy. I ran the study and I collected the data. But the world is too chaotic to determine if Rory is right with the kind of certainty my friend is looking for. He insisted that brands did not “work” on him like they worked on most people. Based on his outfit, I was inclined to believe him. And yet, I wouldn’t be surprised if he had a bottle of Listerine in his bathroom.

A Digital Collaborator: The Future of Search

In 1941, Jorge Luis Borges published a short story about an unending library comprised of hexagonal rooms. The library contains every book ever written, every book that will be written, and every book that could be written, in all languages. One book contains a detailed history of the future. Another describes the true story of your death. There’s commentary on the gospel of Basilides, and commentary on the commentary.

The library contains books filled with every possible combination of letters—one book has the letters M C V repeated from start to finish—rendering most books nonsense. Some residents diligently search for a perfect index of the library, but it’s a quixotic search. How could they distinguish the faithful catalogue of the library from the innumerable false ones?

Borges’ short story, The Library of Babel, is an eerie illustration of a problem we encounter every day: information overload. We live in an era where information, once scarce and expensive, has become a commodity. And while access to more information is a good thing, it often comes at the expense of having to sort through heaps of gibberish. In a way, we’re all living in the Library of Babel.

Or are we?

If you trace the history of information, from the first spoken languages to the Internet, you’ll notice that each time we invent something that spews more information into the world, we ingeniously respond by creating a system that organizes the new information. Contemporary critics rightfully complain about information overload—we’re suffocating from “Data Smog,” as author David Shenk puts it—but it’s simultaneously true that we’re living in an era of extreme organization. It’s never been easier to store, retrieve, and share information. Not even close.

Yet the ability to access the world’s knowledge with just a swipe and a click might come at a cost. What John Stuart Mill said of happiness—that it “was only to be attained by not making it the direct end”—also describes the nature of discovery. We tend to descend on good ideas obliquely, as Financial Times writer John Kay puts it. That is, scientists and artists make discoveries when they’re contemplating something that is only vaguely related to their original question. It’s an overlooked aspect of the creative process that repeats itself—Archimedes in the bathtub, Darwin reading Malthus, Fleming experimenting with bacteria.

At this point, you might suspect that this essay is about the fundamental tradeoff between structure and serendipity. If we generate good ideas by welcoming a dose of unexpected encounters, then each time we organize information we risk impeding intellectual progress. Being productive and creative is about injecting the right dose of disorder and chaos into your daily routine, right?

The problem with this view is that it involves debating two abstractions. What’s at stake is not balancing the Apollonian with the Dionysian but answering a more concrete question: How do search interfaces influence search behavior?

This is where things get interesting. The field of information retrieval is based on a search model that we’ve inherited from the early days of computer science. That model assumes that retrieving information from a database involves going to a computer, searching the database, finding the document, and leaving. “It just wasn’t intuitive to imagine a cohesive information environment where people could search many databases at the same time,” Marcia Bates, Professor Emerita of Information Studies at UCLA, says.

Google was such a significant breakthrough because it indexed the World Wide Web and not just one database. It used an algorithm that ranked websites by the number and quality of inbound links instead of simply counting keywords. The logic of the algorithm, which Google co-founder Larry Page wryly called PageRank, is similar to the logic of academic citations: the quality of a paper is determined by how many times it has been cited.

Google has since improved search by incorporating slick new features such as Autofill. It can distinguish the meaning of a query from the words within the query better. Yet the difference between Google and Gerald Salton’s “SMART”, an early information retrieval system developed in the 1960s, is a difference of degree, not kind. In terms of organizing information online, we don’t need to worry about data smog. We need to replace an interface that’s over 50-years-old.

When search experts and information scientists talk about the future of search, they talk about having “a space to explore” and the opportunity “to go in various directions,” as Anabel Quan-Haase, an Associate Professor of Information Science at the University of Western Ontario in London put it to me. This is not the simple idea that Google will get better at answering your questions. It’s the more groundbreaking hypothesis that in the future, Google (or a competitor) might help by inspiring a few, too.

To understand the difference, I spoke with Tuukka Ruotsalo who leads a team of researchers at the Helsinki Institute for Information Technology. Tuukka and his team completed a new search engine called SciNet a few years ago. “The project started from the idea that search has developed dramatically in the last few years but search interfaces have not,” Ruotsalo says. “We still type in keywords and get a list of documents. We are trying to help users recognize topics they’re interested in, and a big part of that is visualization.”

SciNet’s interface looks like a Copernican solar system. The searched word or phrase appears in the middle (“machine vision”) and related keywords and topics dot the periphery (“nano-technology,” “neural networks,” “artificial technology”). Users drag new keywords toward the middle across concentric circles; the closer the keywords are to the center, the more they influence the results, which are listed on an adjacent column. A simple color-coding system makes it easy for users to spot useful articles. Taken together, it’s a wonderful experience.

Ruotsala said that SciNet is “not trying to beat Google,” emphasizing that his team “designed it to help scientific people find useful scientific information,” but they since established Etsimo, a company that will explore a commercial version of SciNet. If conducting research is about finding material at the periphery, this is a promising development. SciNet may bring us closer to the next generation of search by making it more visual and dynamic.

As I spoke with Ruotsala it became clear that the question of structure versus serendipity is misleading. If early IR systems were like hitting every red light down a long road, Google was the engineer who reprogrammed the lights to make the system work better. The future of search, breaking from this approach entirely, would play the role of an erudite driving buddy, stimulating the conversation at just the right moments. You’ll still take the shortest rout, but now you’ll have a digital collaborator to help you think through your hunch. In this view, the history of search is best seen not as an ongoing attempt to organize information, but as an ongoing attempt to simulate a real conversation, where critical feedback and original ideas are exchanged, not just facts.

And yet, when we contemplate the future of search we tend to imagine ourselves caught in Borges’ library, frantically searching for a way to escape. This fear emerges each time information becomes easier and cheaper to produce and share. And while worrying about overload is not completely misguided—imagine living through the 18th century, when the number of books in print doubled from about 331,000,000 to 628,000,000—it ignores a much broader and more important trend.

Right now, search is a completely unimaginative experience, akin to hanging out with a dull accountant. If the creative mind is fundamentally dialectic, constantly questioning and scrutinizing itself, thriving from exchange and dialog, then search must become a collaborator, a process by which a singular idea emerges out of interaction.

We extract two kinds of information when we collaborate with other people, the explicit stuff and the nonverbal cues—the smiles and subtle gestures that “envelop nearly all human action,” as Nietzsche said. If those cues are essential to human communication—psychologists insist that speaking and listening are fundamentally nonverbal—then our latest innovations in search are impressive but relatively primitive.

When you reflect on the inevitable rise of voice recognition software, virtual reality, and artificial intelligence, it’s easy to see what the future of search will look like: more human.