For the most part, we've accepted the new reality that a lot of companies have a whole lot of data about us. And, thanks to Edward Snowden, Americans now know that the Government is officially the biggest brother of them all. But, according to a new piece of consumer privacy research from McCann Truth Central, when it comes to data, it's not how much data companies have, it's what they do with it.
If we explore consumer attitudes toward specific brands, the usual suspects of Facebook and Twitter still top the corporate charts of perceived privacy threats.
But as scrutiny of Silicon Valley intensifies, there's a data giant that seems remarkably resilient in the privacy shakedown. Amazon, which has buckets of powerful purchasing information, is not only the most admired company in the privacy research, but the level of admiration leapt to 47% in 2013 from 34% in 2011. Indeed, only 7% of American consumers regard Amazon as a threat in privacy terms.
The truth is, consumers trust Amazon and this trust translates into consumer affection. It's this love and affection that insulates the brand in privacy and security conversations. As a consumer in our focus group stated, "Every time I see that green tick security sign, it's like a child's lolly . . . I just can't resist."
There is a simple distinction in the consumer mind when it comes to these companies: Facebook and Google are seen to "own" my data, while Amazon "uses" my data. The enduring power of sentences like "customers who bought this item also bought" and "recommendations for you" has convinced people that their data is being consistently and simply used for their own good (even if it might be bad for the pocketbook!). On the other hand, when talking about Facebook, Twitter and Google, consumers use language like "taking" and "owning" my data. It's not that their data is being used today in a way that upsets them; it's the belief, rightly or wrongly, that it is being stored for some future, unspecified purpose.
And yet, as we enter a whole new era of data convergence, it will be interesting to see if Amazon can maintain this insulation. Amazon and Facebook recently announced a partnership that would offer users a personalized Amazon page, where people could see product recommendations influenced by friends as well as their own tastes. The partnership means that, with permission, Facebook would now have access to key pieces of data, and could quantify the effect of social recommendations to sales figures. As powerful data partnerships become de rigueur, all companies need to get ahead of the game in terms of how they compensate consumers for the data they are sharing.
It's well known that people are more willing to give up personal information if they receive benefits in return, most commonly expressed as discounts or deals. But as companies increasingly compete to access consumer data, companies need to recognize that not all compensation is created equal.
For example, image database Foap has created a platform that invites consumers to upload their photos, which could be featured in a brand's ad campaign. Consumers are financially compensated but, beyond that, feel a kinship to and trust for the brand that has chosen to showcase their work.
At the top of the ladder, some compensation is so intrinsic that consumers believe that it helps them to be a better person. Health and fitness apps and products like Nike Fuelband have led the way here. WebMD recently launched WebMD Pregnancy App -- a free service that helps people "Keep Track Every Day, Until That Special Day." Women input the intimate details of their bodies and, according to the company, more than half of the women who use the app spend over an hour a week getting or sharing pregnancy facts. The difference between these companies' services, and the Facebooks and Googles of the world, is that consumers do not even think of this process as explicitly "giving up their data". Rather, consumers perceive the service to provide such an invaluable benefit to their lives, it doesn't feel as if they are giving up personal data in the traditional sense.
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