3 ways to avoid creeping out consumers with big data

By now, you’ve probably heard about the father who found out his daughter was pregnant when Target sent her coupons for diapers.  Or the dad who opened his mailbox to find direct mail from OfficeMax addressed to “Mike Seay, Daughter Killed in Car Crash, or Current Business.”

In this age of big data, it’s become all too commonplace for data-driven marketing to feel creepy, overly familiar, or just plain wrong.

This uneasy feeling is known as the uncanny valley. Robotics professor Masahiro Mori coined the term to describe the way people react positively to increasingly humanlike representations, until the point at which they become too close to a real human being, when they suddenly become repulsive. It’s this phenomenon that makes clowns and zombies so unsettling, and it’s at play when targeted marketing goes awry.

Rather than the personalized and relevant interactions that these methods promise, consumers experience targeted ads as an unpleasant mix of accurate, annoying, and alarming. As tech writer Farhad Manjoo put it, “Targeted web ads are too dumb to be useful and just smart enough to make you queasy.”

But when big data promises marketers big results at the push of a real-time bidding button, where do we go from here?

To better understand the tightrope that brands face with targeted marketing, we studied more than 8,000 consumers, working with them to understand their opinions on everything from data privacy to loyalty programs. We conducted this research during the summer of 2013 across 52 of our private online communities, using surveys and open-ended discussions.  Group difference tests were performed with age, gender, and country as independent factors.

We found that consumers overwhelmingly prefer anonymity online: 86 percent of consumers would click a “do not track” button if it were available and 30 percent of consumers would actually pay a 5 percent surcharge if they could be guaranteed that none of their information would be captured.

On the flip side, consumers may be willing to share their data if there’s a clear value exchange: 70 percent said they would voluntarily share personal data with a company in exchange for a 5 percent discount.

Some attitudes towards data privacy seem to be age-driven; general interest in exchanging personal data for deals, for example, decreases with age (62 percent of the “Silent Generation” would keep their data private rather than get perks, while only 40 percent of Millennials say this). However, when presented with specific personalized marketing scenarios, consumers showed similar levels of acceptance across age groups.

It is also important to note that not all targeting is created equal; familiar brands have more freedom to use data in marketing efforts.  Offers based on purchase history with a known company are perceived more positively than those based on predictive models or targeted marketing from unknown companies. Indeed, we found 74 percent of consumers think its ok for companies to offer personalized coupons based on their purchase history, but only 13 percent think it’s acceptable for any company to buy or sell personal data in order to personalize.

Consumers are not just distrustful of targeted marketing; they don’t find it to be particularly useful, either. Only 14 percent of consumers, if given the choice, would shop by receiving targeted offers based on their online search and purchase history. Sixty-two percent would prefer to find promotions and discounts from multiple vendors at one centralized site, while 24 percent (more for males and those under 50) would like the opportunity to broadcast their shopping needs to invite retailers to bid for their business.

So what can brands do to avoid creeping out their customers?

1. Exchange eyeballs for engagement.

   Instead of trying to reach everyone all the time, push at moments of intention. Consumers express a desire for a more open marketplace in which they can bypass targeted efforts and proactively initiate brand interactions based on their unique needs.

   These consumers feel that brands should focus their marketing efforts on times of active shopping rather than infiltrating their online lives hoping to distract them with advertising.

   For example, Valpak, an icon of the direct marketing industry, recently added an augmented reality component to its digital coupon app. Consumers hold up their device to see which local businesses have Valpak coupons available; businesses with coupons pop up on the map with information that allows the user to interact with the business at the same time they’re ready to make a purchase.

   Stop chasing reach and instead think about how to respond to customer needs dynamically and in real time.  What would a “consumer RFP” look like for your brand?

2. Don’t become a slave to the big-data machine.

   Just because you have information, doesn’t mean you have to use it.  Our data shows that acceptance of targeted marketing practices varies widely depending on the type of data being used (e.g., earned, inferred, bought) and the nature of the existing relationship with the brand.
   So know your boundaries, avoid sensitive topics (e.g., birth, death, finances), and respect the relationship (or lack thereof).

   Remember, helpful personalization from a familiar company becomes invasive targeting when it comes from a stranger. Marketers need to tap into their own empathy and judgment, and couple machine-driven methods that rely on volume and velocity with collaborative, interpersonal approaches such as private communities.  Doing so is key to finding meaning, not just patterns, and to telling stories, not just visualizing points in time.

3. Use data to create value.

   Big data can be used to personalize the entire brand experience, not just advertising. This means giving customers the keys to drive their own personalized defaults to shape their ongoing interactions with you (e.g., how they navigate your website, type and frequency of communications, privacy settings).

   Also, think about new ways to use data to serve customers rather than yourself.  Show them how their behavior compares to others, or provide tools for tracking, analyzing, and even exporting their transaction history.

   The UK’s Midata Initiative, for example, is working with utility providers, mobile operators,  banks, and others to share data back with consumers, allowing them to track, analyze, and spot  correlations and trends in their behavior over time. In this way, individual consumers become liberated actors who are both more engaged with your brand and actually armed with better data when they do want to share.

And above all, remember the golden rule. You wouldn’t want someone hunting through your trash, real or digital. So stop looking through the window and instead ring the doorbell.  Better yet, unlock your own front door and welcome your consumers inside as true collaborators. When there is a fair and explicit exchange of data for value, consumers are quite willing to share; to be tracked, even.  You might just find that what they have to give is better than what you would have taken.

Katrina Lerman is senior researcher at consumer collaboration agency Communispace.