Just because you can predict what your customer wants to hear, when, where and how doesn’t mean that your customer wants their behavior to be that obvious. Learning the dynamic balance between “convenient” and “creepy” won’t be easy. But will be essential to maintaining effective consumer engagement.
No advance in technology is without potential unintended consequences. Services like Uber or Lyft not only make life more convenient, they also act as information gathering points for their users’ movement patterns (from where, to where, when, how often and so on). If you mine this data in the aggregate, you can develop insights into transportation logistics and economics and improve the services you offer. But you can also build behavioral profiles at the individual level, and that’s where things can get a little scary.
Suppose everything you do (shop; eat out; travel; walk your dog; use your phone; adjust the temperature of your home or office; watch a movie online; order pizza….) generated a data trail (which it already does in most of these examples) and then suppose (because almost everything talks to almost everything else) that all these individual data trails get combined into a “life profile” for each person, updated continuously as you interact with all the smart elements around you and easily available as input to the predictive analytics algorithms of the world’s product and service marketers.
It’s likely that this will be both possible and common within the next decade. Is this a good thing?
For the “innovation” industry (the ideas and capital flows that create things like Netflix, the Nest thermostat, Twitter and Uber) there will be rich opportunities. Smart homes that ordinary people can actually interact with in useful ways; smart buildings that use less energy and provide better environmental management; smart cities that can manage traffic flows and services better than they do today; a smart grid…. a long list of things that have already been thought of and an even longer list that no one’s thought of yet. Probably a good thing (as long as we get the grid part right — everything’s going to need power). Not every idea will work out, but we can hope for some big winners here.
For marketers, better targeting, more conversions to product and service sales; more relevant offers to the right person at the right times; less wasted resources making offers to the wrong person or to the right person at the wrong time. Not to mention less pushback and fatigue around ads and messages that miss the mark, interrupt other content or are just plain annoying. Globally, marketing represents a huge industry and depending on who’s data you believe, too many offers and messages still miss the mark. Better profile data could be a true revolution and a big win in marketing efficiency and effectiveness.
But what if that means the big loser will be individual privacy and to some extent choice? If every part of everyone’s life is in a profile somewhere it’s going to be hard for anyone to (a) hide and (b) beat the behavioral prediction algorithms. Maybe that’s a good thing —more convenience for consumers, more targeted innovation for companies, less opportunity for crime, fraud, misrepresentation, and so on — but nothing comes for free. Criminals (who can often blend seamlessly into our social fabric) are smart and well-funded too, and so far, seem to be better at exploiting new technologies than most “ordinary” people. The more pervasive predictive technologies become, the more exploit opportunities may be created. And think beyond the breaches and hacks you hear about in news. Even routine online shopping becomes an opportunity for an “exploit” such as personalized pricing — what a customer pays for something might be calculated in real time and based on a dynamic assessment of what they can afford rather than a standard price that everyone pays or a discount for loyalty or some other differentiation point. Good for the merchant perhaps; not so good for the customer.
A decade is a long time into the future and anything this far off has many uncertainties built into predicted outcomes. So we have time to weigh the convenience and opportunity against the risks and get this right — or at least to debate the range of outcomes we might find acceptable. Better get started.
About Authors:
John Parkinson is a founder and managing director at ParkWood Advisors, LLC and an affiliate partner at Waterstone Management Group. He has been a strategist and advisor for over three decades. He can be reached at: john@parkwoodadvisors.biz .
Nicolette de Guia is the Founder and Managing Partner at N7 Momentum LLC, bringing over a dozen years of experience to the ever-evolving challenges of product marketing and brand building. She can be reached at: ndg@n7momentum.com
