Monthly Archives: December 2014

Why marketers know if you’ve been naughty or nice

santa watching

There is a story about a jolly old elf who tracks your behavioral data carefully, spies on you even when you’re sleeping, and runs algorithms to assess whether your actions are more positive or negative than social norms. Based on his calculation, the elf will reward you with financial gain in the form of material goods or will deduct from your status by tricking you with what looks like material goods but in reality turns out to be lumps of coal. The system is extensive, including a database of every youth in the world, and is updated annually. If you don’t like this surveillance, good luck: The elf’s privacy policy is unpublished, the observational data cannot be accessed by individuals, and your only recourse to correct misinformation is to send handwritten postal mail to the elf’s address at the North Pole.

Perhaps these childhood stories are why people often freak out about data. The legends of people recording others’ actions, especially those of children, as a form of behavioral modification have been with us for millennium. In Bavaria, the Santa myth is actually split into two figures, a Saint Nicholas who rewards good children with gifts and a devilish, horned Krampus who punishes bad children. Japan has a similar tradition, with an Namahage figure played by men wearing huge, ugly masks, who knock on doors and warn children not to misbehave. Religion is filled with data tracking, starting with God watching Adam and Eve’s naughty apple-biting in Eden, moving on to the widespread but vague idea that somehow all of your actions in your lifetime are being observed for a final post-death judgment. In our deepest beliefs, we perceive there is a connection between what we do, how others record it, and how we will be rewarded.

Which brings us to marketing surveillance 

If you collect enough data to form a baseline for comparing people, you end up with a “database” — and this idea has been around for at least 400 years.  In America in the 1600s, clergy tracked births, marriages and deaths; officials called “tythingmen” would also enter homes to inspect families for observed moral behavior. The first consumer database in the United States was set up in Massachusetts in 1629 to track property ownership. As data expanded, intrusions did too. In the early 1700s, U.S. postal mail was opened regularly to spy on message content.

And then marketers figured out they could make money from all of this information. Database marketing started in the 1940s, first driven by direct-mail marketers (who needed target lists of consumers to mail things to and then calculations to see what worked), later by credit-card companies and banks (who rapidly learned that not all consumers have the same credit risk), and then in the 1990s by Internet marketers who realized they could measure a treasure trove of consumers’ online behavior. While the basic approaches are the same — identify potential customers, differentiate by their value to you and what they need from you, continue to gather more information through interactions, and then customize your response — the cycle time of data marketing increased. Direct mail list updates used to take months; if you purchased a pair of boots at a store in December, it might be March before another company’s boot catalog showed up in your mail. But the Internet enabled a cycle time of identification, differentiation, interaction and customization within days, hours, and now even seconds. Visit zappos.com, look at shoes, don’t buy them, and you’ll see ads for similar shoes on other web sites within seconds. The prevalence of such digital “retargeting” has gotten so rapid that many consumers are beginning to freak out.

The systems are growing ever-more sophisticated. Digital media vendor Rocket Fuel has begun testing device fingerprinting to track consumers by their individual mobile phones; in a recent campaign for Brooks running shoes, it identified the mobile devices of everyone standing along the running route of the New York City marathon, and then later served ads to those devices for running equipment long after the crowds had dispersed to Baltimore, California or even foreign nations. Digital marketers can pick up the IP address of a home’s Wi-Fi connection, and then retarget multiple devices — based on a trigger of one person’s behavior — across the many iPhones, tablets and computers residing in a household. Creative-based retargeting is another digital approach in which banner ads or online videos can be retargeted based on a single ad appearing on any web page, whether or not a consumer clicks on it; for marketers, this provides the advantage of being able to “lift” a publisher’s audience, such as a reader of WSJ.com, and chase that individual around the web later with a pretty good idea of their demographic profile based on the original reading material.

Consumers are rebelling, so what is the balance?

Not everyone is happy about this. Early in 2014, a survey by Truste, a global data management company, found that 74% of Internet users had increasing worries about the use of online data. While only 38% expressed worry about government surveillance, 58% said they had concerns about business use of their personal information. Beyond simple consumer annoyance, the growing use of online data may actually be harming marketing results. 83% of survey respondents said they were less likely to click on an online ad due to privacy concerns. In a deeply ironic circle, the data collection sophistication used to make online marketing work better may actually be depressing response rates.

Smart marketers are recognizing this and beginning to tone down the creep-factor of retargeting, using tactics such as impression caps, dayparting, ad creative versioning, and opt-out options to allow Internet users more breathing room before they are inundated with braying offers.

Data tracking will not ago away, because it is how all of us assess the outside world to calibrate our actions. Marketing in particular is all about treating different customers differently, as the great Don Peppers once wrote — after all, if you have unique needs, you should receive messaging about products or ideas that appeal to your interests, and marketers who play this right will gain greater results from their advertising investments. Just as parents and Santa Claus watch over children to assess behavior, other people will always be watching you too. The practice isn’t creepy in and of itself; what has gotten scary is the instant cycle time it takes someone else to pass their judgment. For our clients, we recommend looking beyond just response and conversion rates to also assess the real end customer experience. You’re trying to share information that benefits the customer, so pace yourselves, people. Everyone likes an elf who brings presents, but we all get nervous if he’s watching us too much.

Understanding multiple device use: Meshing, shifting and stacking

woman smartphone 2

A young woman plops on the couch, turns on the TV, and as her favorite reality show casts a blue glow across the living room … she also boots up her smartphone to check on her friends in Facebook and … also swipes open her iPad to play Words with Friends.

All at the same time.

Marketers who want to reach a consumer on all devices concurrently often struggle with understanding how these touchpoints interconnect. The biggest challenge is consumers often use all these devices for different things. While TV is on for video entertainment, mobile devices are used more often for playing games or participating in social media.

Behind this is the fast-growing trend of, yes, people using mobile gadgets plus TV at exactly the same time. BI Intelligence just reported that 45% of all smartphone use by U.S. consumers age 16-44 is done with the TV on, as well as 37% of laptop use and 55% of tablet use. If mobile is ascendent, TV seems to be its constant companion.

To address this puzzle, we’ve searched for frameworks on how people actually use different screens at the same time — and found the best from Monique Leech, an analyst at global research firm Millward Brown. With a hat tip to Leech, here’s our own interpretation of her findings: there are three core ways people use multiple devices and each requires a unique marketing strategy.

Meshing: ‘Hey look, tennis is on ESPN. Let’s read tennis.com too!’

“Meshing” is when people use two or more devices to watch directly related content. For instance, when Jane Smith was watching the Super Bowl on TV a few years ago, she was surprised by a blackout in the stadium lights, and turned to Twitter on her handset to chat about it. Oreo famously leaped on this moment by tweeting “You can still dunk in the dark,” and Jane would have laughed. Marketers who want to leverage “meshing” behavior can either target integrated advertising content, such as a buy on a weekend sports event and a concurrent media buy on ESPN.com, or deploy “real-time marketing” responses on social media during major awards shows or sports events.

Alas, meshing is only part of the story, and typically not the dominant form of concurrent media use. Putting an ad on Tennis.com to match a pro tennis tournament on TV at the same time may not always be the best approach. The next behavior, “stacking,” explains why.

Stacking: ‘Hey look, Walking Dead is on TV. But let’s chat on Facebook too!’

“Stacking” behavior is different, and more common, in which, say, James Smith is watching “The Walking Dead” on television while simultaneously chatting with buddies on Facebook via his iPhone. Stacking means adding different content from one device to unrelated content on another media device, all at the same time. Numerous studies show this is the dominant form of concurrent device usage. Salesforce.com recently monitored 470 consumers for a month and found they spent an average of 3.3 hours on smartphones per day with the top activities being emailing, searching the Internet, or social networking. Tablet behavior was similar, with social networking and reading at top. What’s most interesting is so few reported watching TV-related content simultaneously on mobile gadgets, it didn’t make the list.

For marketers, this means you can’t just buy ads on CNN.com to align with viewers watching CNN on TV. Instead, you must explore audience targeting across content platforms at simultaneous times, to reach consumers on Facebook or in a game while they watch a show on television.

Shifting: ‘This content is fun, but I’ll pause now and continue it later.’

The third form of multiple device usage, “shifting,” is one of shifting from one gadget to another while pursuing related content. This could be as direct as watching part of a Netflix movie on a tablet and finishing it on TV, or more nuanced such as researching a trip to Italy on a smartphone and then completing the reservation via a computer browser window.

This “shifting” device behavior poses two challenges for marketers, in targeting and measurement. For targeting, it requires understanding how different media touchpoints may be used in sequence for a consumer to learn about, explore, consider, and then consummate a desired action — and for measurement, it means the combined impact of all these channels must be evaluated not in silos, but by their cumulative lift in results.

Three puzzles, not one

The punchline is each type of behavior poses unique challenges. You can try to intercept consumers who mesh their related content, but be aware they may actually be using different content at the same time. You can also try to reach consumers as they stack different content on different devices, but to do so you’ll need to be more clever in how you coordinate your ad messages. And for consumers who shift across devices pursing related content, you’ll need expert measurement systems to understand this pathway and how to influence it.