There’s a new idea that’s fast gaining speed in many areas of business, and it’s called predictive analytics. It’s a complex process with a relatively simple definition. Predictive analytics is a branch of advanced analytics that is used to create predictions about what might occur in the future.
By combining processes and methods including data mining, statistics, and artificial intelligence, predictive analytics programs are able to analyze huge amounts of data - both structured and unstructured - from the past to develop predictive intelligence.
Here are just a few ways that predictive analytics can help your contact center perform its tasks more efficiently.
Customer retention is one of the most important ways that predictive analytics can help contact centers improve their outcomes.
The traditional thinking is that it costs more money to seek out new customers than to keep the ones that already exist. In fact, some statistics suggest that it can cost almost 10 times as much to gain a new customer as it can to hold onto an existing one.
Predictive analytics can help a call center maintain and improve their customer retention rate through the use of applications like speech analytics.
By analyzing a company’s speech analytics data, and combining that with analysis of other data sets, predictive analytics programs can identify the customers who have the highest probability of ending their relationship with the company.
These customers can be flagged, which allows agents to be more focused on those specific customers and on trying to repair the relationship.
Predicting the success of follow-up contacts
When it comes to collections and sales, the rate of success on a first call can be relatively low, and it’s often necessary for a second or even a third call for your efforts to bear fruit.
Figuring out which customers actually warrant a callback isn’t always an easy process. In sales and collection situations, customers’ responses may not clear the first time around, leaving it up to the agent to figure out whether or not a follow-up call is worthwhile. This is a spotty method at best.
But using predictive analytics can make that process much more precise.
Using data like the number of times they’ve contacted or been contacted, phrases they’ve uttered, their buying history, and plenty more, a predictive analytics program can predict the likelihood that further contacts will result in a sale.
Once that analysis is completed, the customers can be put into a ranking that lets the agent know which ones are most likely to say yes or no to their efforts, allowing them to prioritize calls.
Increased quality and efficiency
Under the old systems of analysis, it could potentially take weeks for an agent’s performance to be assessed properly through spot-check call monitoring. And if there’s an issue with an agent’s technique, that’s simply too long to let it continue.
Thanks to predictive analytics software, that’s no longer an issue. The system provides a full set of data from every calls, allowing evaluation time to be cut from weeks to days.
The more quickly a supervisor or trainer can address an issue that an agent is having, the more quickly it can be corrected, which can then improve customer satisfaction almost immediately. By replacing the old manual assessment system with predictive analytics, a call center can make itself stronger than ever before.
Predictive analytics can give your contact center greater insight into what’s coming down the pipeline, and allow you to see trends that you’d have otherwise missed. For more on how analytics can help you meet KPIs, read “How Monitoring Your Contact Center KPIs Can Lead You to Better Customer Service.”