Customer expectations are both changing and increasing, which means customer-centric brands must operate in a constant state of evolution while still maintaining a focus on the customer and their immediate needs.
According to Accenture’s 2012 Global Consumer Pulse Research, 63% of consumers point to service as the most important factor in their choice of a brand – and 44% have higher customer service expectations than they had a year ago. So what’s next in improving customer service and the customer experience? Giving customers what they want or need before they even have to ask.
How Well Do You Know Your Customers?
While predictive analytics have been a topic of conversation for many years now in customer service, the technology to make it a trend that all brands need to pay attention and adapt to is just catching up. A great example of this anticipatory service is Google Now, which combines information that Google knows about you from the devices you use, your location and your online searches to suggest information you might need before you even need it, whether that’s weather, traffic information or the nearest metro station.
Now think of this applied to all of your customer experiences, where data regarding your locale, the device you’re using, past purchases and searches, the data from your wearable devices, the time of day, even perhaps your latest song selections, will be applied to make your individual customer experience not only more satisfying, but spooky good.
Airlines will present you with travel updates as soon as you arrive at the terminal; retail sites will tell you when those shoes you wanted months ago but were too “thrifty” to buy are finally on clearance; dating sites will even alert you that the restaurant you’re about to take your date to has received terrible reviews over the past month.
The challenges for brands will not just be using customer data to predict and make suggestions, but for most brands simply collecting it across siloed channels including social, and then taking in as much data as possible (instead of selective data) to impress the customer with anticipatory service.
Solving Customers’ Problems Before They Even Happen
Predictive analytics can take companies beyond just impressive service near or at point-of-sale; analytics can give businesses the ability to anticipate customer service problems and take action before they even occur. For example, with IBM analytics, a global auto manufacturer used real-time data to better monitor the production quality of its cylinder heads. In 16 weeks, the company was able to use predictive data to reduce the defect rate by 50%, which ultimately led to an increase in customer satisfaction and reduced customer service requests.
“The world is entering a new era of smart – where decisions will be based on facts, data, and increasingly on the ability to apply analytics to massive data sets and extract very precise business insights,” said Fred Balboni, senior partner, Big Data Analytics, IBM Global Business Services, in a recent press release announcing IBM’s introduction of predictive analytics software and service that forecast asset failure.
What else will predictive analytics be used for when it comes to the future of customer service? Only time will tell.
