In customer service, knowledge is powerful. In American Express’ 2014 Customer Service Barometer, 99% of customers said that getting a satisfactory answer or being connected to a knowledgeable agent was an important part of a great customer service experience.
Unfortunately, expectations don’t always match reality. A Dimension Data report found that one of the top three reasons first contact resolution (FCR) is dropping is because of a lack of knowledge. But that’s not to say customers aren’t getting knowledgeable service—it just may not be a human they’re getting it from.
Psychic customer service
Customers want a service experience that knows who they are and what they want. Luckily, companies can figure out just that using predictive analytics, which anticipates how customers will interact with a brand and what decisions they’ll make regarding purchases.
Several big brands are providing the “psychic” experience customers want using the power of predictive analytics:
- Netflix—The popular streaming service provides TV and movie recommendations using an algorithm based on users’ rating histories. According to a ConversionXL article, they also look at other factors, such as “when did a customer pause, how many times did she pause, what was the color of the movie title that attracted the customer, etc.”
- Gmail—Google’s proprietary email service presents you with targeted offers based on the content of the emails you’ve received. This “automated processing” shows you offers it thinks you’ll find interesting, but you can still report those messages as spam if they’re not relevant.
- Amazon—Everyone’s favorite online retailer displays items that they think pair well with what you’re currently looking at. They reference factors like customers’ past purchases, items they’ve rated, purchases compared to other customers, and even items sitting in virtual shopping carts.
The best part about these recommendations and predictive analytics is that they’re automated—customers can view options quickly and easily and self-serve, something 40% of customers would prefer to do. These services anticipate what customers want before they even know it themselves, saving your company time while still making sure customers get the information they need.
Granted, the companies listed above are big organizations with a lot of resources at their disposal, and access to the latest and greatest technology. But you’re likely already collecting data on customers, whether it’s their name, email, or the company they work for. So what are some ways you can start using that customer information to deliver a smarter automated service experience?
Using predictive analytics in customer service
There are a number of ways your business can start using predictive analytics in customer service, including but not limited to:
- Recommendations/Upsell— There’s a reason the companies listed above provide recommendations: to make life easier for customers. If you know what items your customers have been browsing, you can use predictive analytics to offer up items you think they’ll like, saving them the time it would take to have to search through items manually. Just don’t go too overboard with recommendations—Target learned this the hard way by sending a twenty-something customer pregnancy-related coupons based on her purchases before she even knew she was pregnant.
- Reminders—Customers may forget things, but that doesn’t mean your business should drop the ball. If you’re a company that provides medical equipment, for instance, your customers may forget to reorder on time. But by using predictive analytics to determine when they’ll run out of supplies, you can send targeted recommendations that arrive at just the right time. This way, your customer stays healthy, and your business makes a transaction that would have been forgotten otherwise.
- Retention—Studies have shown that a 5% increase in customer retention can increase profits by 25 to 95%. If customers aren’t opening your emails or haven’t interacted with your brand in a while, you can use predictive analytics to schedule outbound communications that reengage them on a channel they prefer.
It’s not hard to get started with predictive analytics—companies like IBM offer great predictive analytics services, and partner companies allow you to incorporate their intelligence over channels like voice and SMS. We predict your customers just might love it.