Big Demand for Big Data brings Big Profits?
Lately Big Data has made some very obvious, yet subtle, inroads targeting specific users with specific ads and content to their screens. One prime example is the analytics that tracks and analyses our online/mobile/social media behavior and displays relevant banner ads based on our likes, check-ins and interests. Most of the data gathered is often done behind the scenes, unbeknownst to casual user.
But has this new phenomena yielded increased customer insight? It depends on who you ask.
One scholar from the Wharton School of Business postulates that Big Data is just another wild-goose chase from years past. In an interview by Technology Review, Peter Fader from the Wharton’s Customer Analytics Initiative at the University of Pennsylvania said Big Data “reminds me a lot of what was going on 15 years ago with CRM (customer relationship management)… It [CRM] turned out to be a great big IT wild-goose chase. And I’m afraid we’re heading down the same road with Big Data.”
It would be hard to argue that the amount of data available today is unprecedented. But does all this data translate into discernible and predictive insights that brands can profit from. This conundrum reminds me of the old adage – ‘quality over quantity’. Big Data can be like drinking from the fire hydrant when what you really need is a straw.
The below and feature blog post screenshot demonstrates the power of Big Data to produce an ad based on my likes/preferences. I often check the train schedule for the LIRR and noticed that Adobe and The Economist (two brands I often consume and comment about) have been repeatedly displayed for my viewing pleasure. These ads are specifically targeted to my individual tastes. I tested this hypothesis, by checking the LIRR schedules on some friends computers and never saw an ad for either Adobe or The Economist.
Although like most people I have developed banner blindness, I wonder how long this targeting has been going on before I noticed. But now that I know I’m being profiled I don’t know if I should be creeped-out or feel comfortable with the fact that I’m getting personalized ads, even if I rarely look at banner ads.
This creepy vs. comfortable ambivalence recently came to a tipping point for Urban Outfitters. Users of Urban Outfitters’ website were covertly targeted and shown gender specific product offerings. The strategy became an abject failure when users, mostly women, voiced their displeasure for being targeted with gender specific products. It turns out women like to shop for men and found that being shown women specific products was more a inconvenience than a benefit.
Urban Outfitters is one example how using Big Data to ‘personalize’ a users experience backfired, but there are several success story where Big Data has increased profits for many brands. One site, My Revolve, has seen a million dollar increase in revenue from customization, as reported by the NY Times in a related article.
As companies experiment with customization via Big Data one strategy should be getting to know their customers better before systematically trying to find out what they want. Now a good argument can be made that users really don’t know what they want and just getting to know and understand them is a lot more trouble than its worth. This may be true, but developing relationships with customers in the digital age is a long-term commitment.
If companies took a a more strategic approach to understanding its customers and creating customized and evolving experiences from these interactions a more symbiotic and trusting relationship can develop. This approach not only establishes trust, while avoiding creepiness, but also strengthens the bonds that help connect people’s lives with brands in more powerful, meaningful ways.
The potential power of Big Data should not be used exclusively to strengthen a company’s bottom-line. In today’s social media saturated economy establishing lasting long-term relationships with customers could have more value, from the viral effect of social media, than a quick one-time conversion.
I believe Big Data and customization have enormous potential to gain insights that can be translated into unique and dynamic experiences for users. Knowing when and how to make those experiences seem genuine and un-intrusive can only happen when there is a signification amount of trust build-up over time. Brands that get this right will lead the pack.
Written by Marc Niola – The UX Acrobat
Follow Marc on Twitter: @MarcNiola