July | 2014
Wouldn’t it be awesome if you could just turn on your television, sit back, and let it pick your favorite show? How about instantly connecting to the person you wish to talk to—by merely pressing the “call” button on your phone or stepping into your car and letting it decide where you want to go? Anticipatory computing makes all this and more possible through recommendations based on your past behavior. It is defined as "systems that learn to predict what you need, even before you ask”.
This technology is complimented by the development of large data sets that capture the data stream generated by people every day through various mediums such as mobile phones, credit cards, RFID devices, and chatter on social network.
In fact, did you know that applications such as ‘Google Now’ and other location-based services already use anticipatory technology to provide information to people when they need it? This could range from alerts on movies, concerts, and stock updates to news cards based on the user’s location and search history. These applications can also monitor an individual’s flight status or get real-time traffic updates that help commuters get to work or their favorite coffee shop.
Even online retailers like Amazon have already filed patents for "anticipatory shipping"—a method to start delivering packages even before customers click “buy". Amazon focuses on online shopping patterns or trackers that monitor factors such as past orders, product searches, items in the shopping cart, or wish lists to predict consumer behavior. This could significantly cut shipping time and discourage consumers from visiting physical stores. The packages could even wait at the shippers’ hubs or on trucks until an order arrives.
Another area with plenty of potential for anticipatory technology is voice interaction. In fact, apps such as ‘MindMeld’ already listen in to entire conversations between participants to predict the information that they might require. MindMeld also adds pertinent photos or videos to the conversation as it interprets what is being said. Elsewhere, certain apps in large contact centers also utilize this technology to listen to conversations between customers and call center agents, understand them, and find relevant information—enhancing the rep’s efficiency and productivity.
Anticipatory intelligence has implications not only in the retail space, but also in other areas, including utilities. Organizations can leverage anticipatory computing technology to make better decisions and enhance end-user experience. It helps consumer-oriented companies to go a step beyond conventional customer service to predict and proactively fulfil users’ requirements. In the years to come, this technology promises to affect just about every company and industry.
How else do you think anticipatory intelligence can change or enhance the consumer experience? Please leave your comments in the section below.
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