“Netflix knows what its subscribers want to watch next, airlines know when their passengers arrive at the airport and Facebook knows, well, everything,” Says Robert Barba writing in American Banker.
Wharton Business School Professor Peter Fader’s book Customer Centricity makes a good case for using this data to help companies evolve from being product-centric to customer-centric. His premise is that with the customer data available today, companies should be able to align their products and services with the wants and needs of their most valuable customers.
Take Starbucks for example. Fader believes they are missing out on customer-centric opportunities because they aren’t connecting the dots on their customers’ behavior. The barista in your local Starbucks in Boston may know how you like your daily coffee, but when you travel, does the barista in Ohio or San Francisco know what your usual order is? Fader points out that they easily could.
This example made me pause. How much do I value the convenience of Starbucks knowing how I like my coffee? How does that value compare to my dislike of people knowing all about me and trying to predict my every move? Is this all a bit creepy?
Larry Downes, writing in Harvard Business Review thinks this type of concern is just the result of unfamiliarity: “When specific data is used in novel ways, the initial response is often the creepy factor… [but] over time, the creepiness decreases, ” he says. However Downes points out that companies must be sensitive to overstepping. For example, LinkedIn suffered a backlash when using photos of contacts along with their recommendations. “What we’ve learned now,” says LinkedIn’s Ryan Rolansky, “is that, even though our members are happy to have their actions, such as recommendations, be viewable by their network as a public action, some of those same members may not be comfortable with the use of their names and photos associated with those actions used in ads served to their network.”
Banking is an area where we might expect the creepy factor to be at its height. Yet, according to American Banker, “a recent Accenture consumer banking study found that 63% of the 4,000 respondents said they were willing to give their banks direct access to various personal information, such as credit card, mortgage and student loan data, in exchange for products and services tailored to them,” so the benefit here outweighs the concern.
When it comes to research products and services the value of tracking customers’ preferences and using that data to anticipate needs becomes clear. When Tom Danbury and Bev Weiman founded SSI 40 years ago, they were told by several esteemed researchers that trying to automate sampling would never work because every research project is different. Those esteemed researchers were obviously wrong –technology can improve quality while standardizing and speeding up the delivery of high quality sample. Yet there are also custom elements to many if not most research projects. By using the data we have about SSI customers’ preferences and needs, we can customize what we do to match what they want.
Examples of this are understanding the frequency and type of project communication customers expect, anticipating their known workflows, ensuring critical information is shared to the right teams and knowing when and how to keep them up-to-date on new developments.
There’s a place for using data to smooth the path to purchase. But using data clumsily to make too many assumptions about consumer needs and preferences risks creating a backlash and turning people off from taking part in the loyalty programs that feed those vast databases in the first place.
Chris Nichols, CSO at Florida bank CenterState uses “anticipatory banking” to track life events and recognize likely home purchasers or monitor business growth patterns to suggest appropriate additional services. That’s pretty sensitive stuff, but Nichols points out that the key is “making sure the message does not feel intrusive. If presented right, it is not creepy. If presented wrong, it can be.”