It all started with Amazon. A while back, Amazon started tracking what its customers were doing on the site so that it could more accurately recommend people to individuals. With every look at a new product, click on a review, or purchase, Amazon increased its understanding of what each one of its customers was interested in, allowing the company to tailor the experience of their store to each visitor in order to increase the amount of money someone spends with them.
The practice of gathering user data to personalize their experience on the internet took off from there, with companies like Netflix and Zynga leveraging that data to improve their users’ experiences and yield increasing revenue from the improvements they made.
Over the last few years, the field has grown so much and generated so much information that it was given the monicker of “Big Data” and a new industry has popped up around the massaging, analysis, and leveraging of such information. In the gaming world, for example, most social games are modified based on what works and doesn’t with its players. This is not an unusual phenomenon as game studios have, for a long time, observed test groups of players to identify areas where games needed improvements. That data was then used to improve products but also to make them more addictive to players, bringing them back again and again. Zynga has taken the model one step further by essentially watching players in near real time and making adjustments accordingly. My own company, Keepskor, does something similar to keep the games interesting to players by measuring how successful interactions are within the system on multiple dimensions.
Meawhile, the social media age has benefited marketers, thanks to the increased sets of information being made available by users whenever they updated their online status on a service like Twitter or Facebook, or when they checked in on services like Foursquare. It is not uncommon today for smarter companies to monitor this stuff in real-time and target offers or send out messages in real-time. While many of those triggers are crude, they are increasingly allowing brands to customize experiences to a near-personal level for some of their users.
Since the introduction of the iPhone, mobile devices have been moving into individual pockets at an ever increasing rate. With each new smartphone making its way into a user’s hand, there are a flurry of new data points emerging, from where users are located (thanks to the GPS on their phone) to what they are seeing (thanks to the front and back facing cameras on the devices) and even what they are purchasing (thanks to embedded RFID chips in an increasing number of devices).
Increasingly, this information is grabbed without more than an on-first-use authorization, and works to customize the user’s experience to meet their needs. Google Maps, for example, automatically grabs your phone’s GPS information to present a map of what’s near you. The Bing search engine on Windows Phone dynamically tailor search results based on your location. Pandora in your car or on your phone tailors music based on what you liked and didn’t like.
Going one step further, connected devices like the Fitbit tracker or Nike Fuelband track how much walking or exercising you’re doing, reporting that information back to a server when one gets near a reporting spot. Similarly, smart scales like WiThings and sleep trackers like Zeo provide further data about your health. A few years ago, I talked about how cheap sensors could unleash a new world of potential and here we are. Thanks to an increasing trend in miniaturization and acceleration of processing power combined with lower battery consumption, those devices are tracking our everyday movement and we are starting to see how this data can be used to make our devices and our computing substantially more personal.
For many years, a branch of computer science called ubiquitous computing (or ambient computing) has been focused on making computing devices disappear. Today, this era is upon us and it brings with it a new era of computing focused around the individual. I call this new era…
Thanks to the ubiquity of data flowing from individual’s pockets, combined with the ability to analyze data in near-realtime, we are now entering a world where the device in your pocket can start acting as your personal assistant. A few week ago, Google unveiled “Google Now“, a new context-aware application that can tell you to leave earlier for a meeting because there is traffic on your way there or tells you that your flight may be delayed before you get to the airport. Meanwhile, the Android-based Friday app, released this week, launched a platform allowing other developers to create applications that trigger events based on your location (note: this kind of geo-fencing event triggers is something we have built into the Keepskor platform for gaming purpose so I’m a bit biased on this.)
All this points to an era where our devices are listening to what we are doing, tracking our every move and reacting based on that information. It’s a world where the privacy barrier is going to be shattered, as cameras start tracking and identifying people in every corner of the world, as phone-based GPS and motion sensors as well as other sensors will automatically broadcast what you’re doing, where you’re doing it, and who you’re doing it with (thanks to overlay of data from the like of Foursquare, Twitter, and Facebook, all the information and infrastructure necessary for this is already in place) and where the information will be used by marketers to narrowly target you with increasingly personalized messages that will come at you whenever you look at information (some ruder application may even try to force their attention on you by leveraging the alerting mechanisms like push technology.)
Along the way, each device and increasingly each piece of software will look increasingly customized, with no two users experiencing the application in the same way. Just as no two customers of Amazon sees the same website once logged in, expect a world where dynamic pricing and dynamic software are the rule and where your experience of the online space will be radically different from that of the person next to you.
Today, most people get a first taste of dynamic pricing when trying to book an airline ticket: given a particular flight and flight time, it is hard to find 2 customers who have paid the same price for their seat. Writ large, the new world of You computing is one where dynamic pricing will be the norm and not the exception to the rule.
I would venture that within the next decade, we will see some stores that stop advertising prices altogether. Individuals who want to see the price on an item will have to use their mobile device (either a smartphone, which will look antiquated by that point, or some form of smart glasses like Google project glass) to get pricing on an item. They will then be presented with a price that has been optimized to them based on a variety of data points available.
Think it’s a futuristic thing? Think again. After all, we’re already at the point where machines are repricing lemonade dynamically based on the weather. It’s only a question of time before it is priced based on what the lemonade stand knows about you.