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Big data: What's helpful, what's hype

Big data: What's helpful, what's hype Michael Estrin
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Do you want to know how to use big data to achieve your marketing goals? Do you worry that the big data revolution presents both big opportunities and significant obstacles? Have you begun implementing big data into your marketing? Are you almost there, or do you have a long way to go?


Join the club. The vast majority of marketers have either implemented big data and are doing great (thanks for asking!), begun using big data and are almost there (we just need the recipe for that secret sauce, please!), or they've started thinking about big data and concluded they have a long way to go (seriously, we didn't think there'd be math on this exam).


Big data: What's helpful, what's hype


So how do I know what the vast majority of marketers are thinking? Data. You see, eMarketer recently asked marketers about big data, and nearly all of them said it was either an opportunity or some combination of opportunity and an obstacle. In fact, only about 5 percent of marketers said big data was a total obstacle. By contrast, the majority of those surveyed (61 percent) said they see big data as both an opportunity and an obstacle, but acknowledged that they have a long way to go when it comes to harnessing big data and using it consistently in their decision-making process. A much smaller group (19 percent) agreed that big data is both a challenge and an opportunity, but they were pretty sure that they were "almost there" in terms of implementation. And of course, a confident few (15 percent) said they've got it under control; not surprisingly, they see big data as a total opportunity.


With 95 percent of marketers interested in big data, it's little wonder that this one-time cottage industry has gotten so, well, big. Spending on big data is expected to reach $18 billion this year and grow to $47 billion by 2017.


But it's not just about big money. Big data is a big topic in marketing circles, especially because many marketers see it as a high-impact, low-cost difference-maker. Not surprisingly, there are stories about the handful of brands that are winning with big data. There are stories about brands that are failing with big data. And predictably, there are lots of stories about how big data is changing marketing and how marketers can adapt. And of course, as with any big topic, there are the critics and the haters.


Unfortunately, the more we use the term big data, the further we seem to get from understanding what it actually is and the closer we get to turning it into one of those meaningless marketing buzzwords. In fact, there are some marketers, and even some data folks, who worry that big data already has an image problem.


But regardless of what you call it, the data revolution is in the process of transforming our world. Marketers can't afford to ignore big data, but right now the bigger risk is that they're losing the forest through the trees, according to Joe Rospars, CEO of Blue State Digital and the principal digital strategist for Barack Obama's presidential campaigns in both 2008 and 2012.


"A lot of marketers think that they can just collect data and that it will tell them what to do," says Rospars. "That's not really how big data works. And what you want isn't so much big data as smart data."

What can big data do for you?


So what can big data do for you?


"Data is very good at validating past activity or opening up new ideas," says Dane Atkinson, CEO of SumAll. "But it won't tell you where to go."


SumAll is one of dozens of analytics firms that work with marketers to help them better understand and use big data. But SumAll is also somewhat unique. Its analytics suite is designed with small and medium-sized clients in mind, but they also work with about 10 percent of the Fortune 1000 companies, including brands like Starbucks and Siemens.


I asked Atkinson if marketers big and small are really able to harness big data to their advantage. He told me yes, but then added that he sees a lot of CMOs fall into one of two camps. Either they think big data will change everything they do, and they buy into the hype without thinking it through, or they know they need big data, but are worried because they really don't understand how to use it and end up fumbling the ball.


The answer, according to Atkinson, is actually somewhere between hype and fear."Big data isn't the whole wheel, it's a spoke in the wheel," he says.


While each marketer is going to encounter different issues with big data, there are some general principles to consider. First, says Atkinson, marketers need to adopt a culture that sees information as a key driver of success. "A lot of people point to Netflix as an example of that attitude," says Atkinson. "They amassed and analyzed all this great data and then used that to create new products that their customers love."


But as much as Atkinson sees people pointing to Netflix as a good example of how to use big data to your advantage, he says people often miss the key lesson of Netflix. "They didn't gather all that data and then say this is the kind of original programming we need," he says. "Netflix used that data to better understand its customers."


And that brings us to Atkinson's second piece of advice for marketers. "Make sure you're using big data to measure the things that are driving your success," says Atkinson.


Back to Netflix; it's easy to say that the company wins because it has a lot of data, but the way Atkinson sees it, Netflix is successful because it uses a lot of the data to focus on improving things that drive its success. Here's how Ashlee Vance of BusinessWeek recently described Netflix's successful foray into original content:


"Netflix is always testing things. It will select a group of customers, typically by the tens of thousands, and use them as guinea pigs. One group has been given the ability to create avatars for each member of their families, who in turn get individualized recommendations. Others who watch Netflix via the Sony PlayStation have been greeted by a voice that asks what people in the room want to watch. The most rigorous testing concerns recommendations. Netflix has a vast catalog of movies and shows, but much of its content is old and of limited appeal. To make its service feel valuable, Netflix tries to maximize the likability of the titles that get displayed on someone's home page."

There's a lot to unpack in that brief description of how Netflix deploys its data. But the focus on recommendations should be illuminating to all marketers. After all, Netflix lives and dies with its subscribers. Without a cutting edge recommendation engine, subscriptions will level out and fall off. So while you can say that Netflix is successful because of big data, it's more accurate to say that Netflix is successful because it applies big data to one of its most pressing concerns.


Here's how Atkinson puts it more generally: "Big data can help you measure sales, for instance, and you can correlate that information to your latest campaign, but that won't tell you what you need to know," he says. "Suppose you've figured out that it's new customers that are driving your business. What you really want to look at is the data that's specific to those new customers." 

Data-informed creative


Data-driven creative. We hear that a lot these days, and depending on who you are, the phrase either means great work or total garbage. Usually, it's the former, unless you're talking to a creative. In that case, there's something of a backlash directed at big data.


Writing in Ad Age, Traction CEO Adam Kleinberg elegantly and passionately addressed what he sees as the folly of data-driven creative. "A few weeks ago, I overheard a principal from another agency proudly boast, 'data drives every piece of creative we put out today,'" Kleinberg wrote. "My immediate reaction was, 'boy, your creative must really suck.'"


But jokes and jabs aside, Kleinberg makes a good point about the creative process and the need for brands to stand for something that probably can never be reduced to data. "Data doesn't tell you to hire Betty White. Data doesn't tell you to invent the Nike Fuel Band," Kleinberg wrote. "When my agency created a campaign for Adobe around a game called 'Real or Fake?' there was no data involved. Somebody threw out the idea in a brainstorm and our creative director said, 'That's it!'"


I wasn't surprised by Kleinberg's take on big data. He and I have talked about this topic before, and he's been pretty outspoken about the danger of devaluing qualitative approaches to marketing and what he sees as the appropriate use of data. But I was surprised when Rospars told me that he tends to agree that there are significant limits to big data. "A lot of brands and agencies see the world as either creative or data, but I think both views miss the larger point," Rospars says. "We try to say that both are equally important."


Of course, that's easy to say, but what does it mean in practice?


The way Rospars sees it, brands shouldn't be talking about data-driven creative. On that he agrees with Kleinberg -- data won't tell you what your creative ought to be, and you shouldn't ask the data to drive you toward the answer. But that doesn't mean there isn’t a place for data in the creative process. "We choose ideas that we are passionate about," says Rospars. "But we also use the data to help us better understand those insights."


In a nutshell, that means using something other than data to figure out what you want to do, and then optimizing around that goal with relevant data. To do that, Rospars says, brands and agencies need to do a better job of pairing creative teams with quantitative teams. But it's not enough to simply "put them in the same room," says Rospars. "You need to look at them and ask if each iteration of the idea represents one side building off of the other's previous concept."

Privacy


Call it the elephant in the room. But it's hard to talk about big data without mentioning privacy, even if you don't think privacy exists anymore.


"It's that old saying, if you're not paying for the product, then you are the product," says Atkinson, who concedes that he might be somewhat jaded on the topic. "We don't have privacy. But that doesn't mean marketers should ignore the privacy issue."


The privacy issue -- distinct from actual privacy -- is important because the success of your marketing depends greatly on complex cultural forces that move at the speed of the internet.


Consider Facebook, which seems to bounce from one privacy kerfuffle to the next. Or look at the initial public reaction to the NSA's Prism program compared to how the NSA's critics believe we should be reacting.


"Marketers need to be sensitive about big data because you don't want to be right on the line of creeping out your customers," says Atkinson. But anyone who tells you they know just where that line is, is either lying or selling something. The truth is, we don't know.


When I spoke with Atkinson, I told him about a recent experience where an advertiser's retargeting had proven to be both a good use of big data and a little clunky. Driving around my neighborhood, several billboards for a Universal thriller called "The Purge" caught my eye.



Outdoor billboards are notoriously hard to track. But I can honestly say that this one drove awareness the first couple of times I saw it, and that awareness eventually drove a specific action a few days later when I went to YouTube and searched for the trailer.



So far, so good.


After watching the trailer, I opened up Pandora and went about my day. But the first ad that Pandora played was for, you guessed it, "The Purge." That was the first time I had heard any ad for the movie, and I think it's pretty safe to say that what I heard was retargeting in action.


To be fair, retargeting has been around for a while, long before we started talking about big data. And it's not really big data per se, although it is certainly a data-driven marketing tactic. But when I told some friends about what had happened, more than a few of them said, "big data."


When I told Atkinson about that experience, he asked me to characterize the reactions of my peers. As it turned out, about half of them didn't really care. But the other half thought it was kind of creepy.


For Atkinson, that's bad news. The advertiser should have delayed the ad so that the retargeting wasn't so obvious. In this instance, there wasn't much harm. I still saw the movie, and I even told some friends about it. But even if we're talking about a harmless occurrence, I think it's safe to say that no brand wants to even come close to creeping out a customer.


So what's a brand to do?


Well, not being creepy with data seems like a good start. But the trouble is, it's hard to say what is and is not creepy. The way Atkinson sees it, brands are best served by acknowledging that there is no privacy and then accepting the fact that consumers should have just as much access to their data as the advertiser. That won't make everyone happy, but it will dampen the outrage and backlash that seems to happen from time to time. More than that, the privacy issue really does underscore the need to think about this topic with some context.


Calling it big data almost certainly brands it as something that will swallow all of marketing. That kind of myopic thinking can be dangerous for marketers for a variety of reasons. But what should be most disconcerting is that the inability to use smart data will only widen the gulf between marketers and consumers, and that's never a good thing.


Michael Estrin is a freelance writer.


On Twitter? Follow Estrin at @mestrin. Follow iMedia Connection at @iMediaTweet.


"Autumn forest trees" image via Shutterstock.

Michael Estrin is freelance writer. He contributes regularly to iMedia, Bankrate.com, and California Lawyer Magazine. But you can also find his byline across the Web (and sometimes in print) at Digiday, Fast...

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Comments

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Commenter: Sione Palu

2013, July 07

Big data is not new. Its just that marketers are late to the party. Physicists have been doing big data modeling and analysis since the early days of computing. The Manhattan project (World war 2 atomic bomb super secret project) was the earliest adoption of compute intensive analytical methods by mathematicians & physicists who were involved in the project. Mathematician/Physicist Prof. Jon Von Neumann was a lead principal in the Manhattan project responsible for the modeling nuclear fission process at the time. A method that he and others developed at the time which he code-named Monte-Carlo (after a place in Europe - just to conceal their work), was as popular back then as it is today. I've seen a research paper that uses this method in marketing data-analytics, however the method is still mainly dominant in engineering/science disciplines.

Amazon, knows really well of how to apply big data analytics for for automated marketing (recommender systems).

Commenter: Adam Kleinberg

2013, July 02

I think Joe hits the nail on the head. It's not about data so much as insight.

That Kleinberg fella, on the other hand.

Seriously though, data definitely has a role in helping derive insight — and insight is what smart creative is based upon. But creativity is what makes great creative great.

@adamkleinberg