Goodbye, Smartphone; Hello, Predictive Context Device
The current phase of the "mobile" discussion focuses on location as the next platform. The growth of Foursquare and Gowalla serves as evidence and as a great demonstration of Metcalfe's law on the mobile net, and tiny players such as Google, Twitter and Facebook have recently rushed to add location features to their platforms.
But, when looking through the POV of the consumer, location isn't quite enough. Mobile technology is now theoretically capable of providing us with real-time contextualized and personalized services and information. The full potential of what this technology can provide should be seen through the aggregated filters of our location, our timeline, our social graph, what we did just before and what we're expected to want or do later on. All of the above (and not just the location), completely change our needs as consumers.
If I'm going scuba diving in Florida with a group of nerds on a Friday afternoon, I have one set of contextual needs. If I'm taking my daughter to school on a snowy New York Monday morning, it's a very different set. The best way to understand the potential of this technology is to realize that it is sort of "aware." Your device kind of "knows" (through GPS/3G/Wi-Fi/accelerometer data, etc.) where you are in the physical and social time and space. It is also "aware" because it holds a complete record of your past actions and habits and of your future intentions -- where you are heading and who you will meet (via calendar entries, contacts, web/search history etc.).
So, one could argue that your device is "you-aware." At that moment we're leaving the realm of the "mobile network" and moving into a new territory where there is only one network -- the network of you. Your new personalized contextual device will actively assist you -- and in being active lies the huge potential leap compared to current technology. I have no doubt that very soon context-based technology will actually predict our needs and desires.
Here are few scenarios that, at the moment, may seem a tad science fictional, but the required technology to realize them already exists. What's missing is a software-based solution that will tie up the loose data ends:
- My context device "knows" it's noon. It also knows (via accelerometer data) that I haven't moved from my desk for the last couple of hours. Because it "knows" I have a TBD lunch scheduled for 12:30 (it reads my tagged calendar entries), it will remind me I should leave. As soon as I move the device, it displays the list of places where I had lunch the last couple of weeks. Since most were Italian restaurants, it suggests Chinese or falafel and generates the latest consumer rating of the restaurants offered. At the same time, it also highlights restaurants located within walking distance that will allow me to be back in time for my scheduled 2 p.m. meeting.
- I am on a business trip to Madrid, have just finished my meetings and have three hours until my flight back to New York. My device "senses" I started moving and "knows" my schedule, therefore it asks me if I prefer to get a taxi to the airport, or if I prefer to stay in the city since the drive to the airport takes about 15 minutes. I choose the second option, slide the "ambient media streams" all the way from "privacy please" to "hit me with everything you've got," and the device offers me all the tourist attractions around me, even a nearby coffee shop that has received exceptionally high ratings (I love coffee). I choose the coffee shop, and as I am drinking my second cup, the device alerts me that my flight has been delayed by an hour and will board through gate E32. I drink another cup of coffee and read from my device the history of Madrid until the next alert updates me that I should call a taxi -- immediately providing me with an application that directly books one.
- I leave my office to interview someone at a nearby bar. My device "knows" it is a job interview (tagged in my calendar), therefore it automatically Googles the applicant, uploads his resume and image, and then provides me with a summary of the available information found about him from HR, the web and other social sources. As I approach the bar, my device turns itself into "meeting" mode, in which I can view a map that displays two dots approaching each other. As we meet, the device asks me if I would like to record the conversation and send it to HR.
And the list goes on. Once we've learned to connect location and time with personalized social/behavioral data, there are endless scenarios. Using not-too-complex algorithms, the context device can continuously study our lives, making ever-improving "guesses" to actively help us.
So, goodbye, app phone; hello, predictive context device. On one hand, the scope of personal information that a device like this will collect about our behavior and preferences is straight-forwardly scary. On the other, whether we like it or not, most of this information is already being collected today. Wise usage and leveraging of our personal information will allow context-driven technology to provide us with services that will turn the next generation of mobile devices into smart and efficient personal assistants that will continue to improve our quality of life.
For marketers, this is the ultimate wet dream of the marketing world since day one: a target audience of one. You.
The original and often forgotten purpose of marketing was to add value to consumers' lives, what MRM Worldwide defines as Customer Utility. Marketing that is context-based -- the kind that provides tangible value in real-time with the professed permission of the consumer -- is an excellent basis for a new type of relationship between marketers and consumers, one that is finally based on win-win.
|ABOUT THE AUTHOR|
Oren Frank is global chief creative officer at MRM Worldwide. During his career, Frank has worked with such brands as Honda, Volvo, Microsoft, Yoplait, Heineken, Axe and McDonalds.