Watch any new phone advertisement, and you’ll see the focus has shifted from connectivity and call quality to data, lots and lots of data―from connectivity to your favorite sites to watching the game live and video connections. Data has become so consuming that a report from the University of California, San Diego entitled “How Much Information?” reveals in 2008 the average American consumed 34 gigabytes per day―before 4G was even available to the average customer.
With this much data, not to mention the amount of information available to the consumer, when someone makes the decision to reach out to a contact center, in most cases they will have as much information as the agent they reach. This isn’t saying the days of “Did you check if it’s plugged in?” responses are gone, but the contact center needs the ability to raise its game to keep up with the volume of data available to the informed consumer.
According to Google CEO Eric Schmidt, “Every two days now we create as much information as we did from the dawn of civilization up until 2003. That’s something like five exabytes (1018 characters) of data.” While the vast majority of this information is user-generated content (pictures, tweets, IMs, posts) there is still a massive amount of data collected on each individual. Your cell phone, car, and other devices can report your location along with any time you connect to any data network. Unified communications and other presence applications track what you’re doing and your availability nearly around the clock. Purchases get tracked by credit card, store and of course browser “cookies,” to say nothing of security cameras (a recent study found the average big-city resident walks into the view of a camera 75 times a day) and other devices designed to monitor access.
How much data does a contact center agent need? While only a small fraction of this information might be pertinent to why the consumer reached out to the contact center, access to the right information at the right time―especially to support cross-selling, collections, and even simply consumer relations―becomes even more critical. This is the foundation of “Big Data”―analyzing the huge volume of available customer information to determine what’s important to know.
Technologies such as Hadoop are considered foundational for data-intensive distributed applications such as business intelligence (BI). Microsoft SQL Server 2012 recently announced support for Hadoop integration to extend its BI functionality to the vast quantity of data available in social network and retail platforms such as Facebook, Twitter, and eBay.
Imagine a consumer tweeting about an issue they had with a recent purchase. The contact center monitoring the social networks correlates the post to a recent purchase made by the consumer and sends a text message or email with a “click to talk” link. The consumer uses the link and the agent is supplied with the information on the purchase, the tweet, and a list of knowledge base search results on the issue. The agent can resolve the issue and, when alerted to the consumer’s upcoming birthday, offers a coupon for a related item. Big Data within the contact center enables this kind of proactive customer service.
Does your contact center have the functionality to take advantage of all of the customer information it collects?