You don’t have to be a magician to be able to identify problems before they happen. Nor do you need a fortune teller to help you understand the things your customer is not saying aloud (and may not even be thinking yet). With the amount of data available today in customer interactions and transactions, organizations can proactively detect and predict customer issues.
In each customer journey, there are many events that are strongly correlated with certain subsequent actions. When a customer calls with a specific question, purchases a certain item, or performs a transaction, there is usually an ensuing question that can be predicted and addressed during the first interaction with the customer.
For example, when customers get their first mobile phone bill, they often call the contact center to clarify the information within. When they upgrade to a smartphone, many will call within 10 hours asking how to synchronize their work email to the device. Customers who call to cancel one of their cable TV packages may not realize that they will also losing one channel they really like. Or, customers calling to change their address may be unaware of additional changes that will automatically ensue.
This kind of ‘chain reaction’ happens all the time. It may seem obvious in retrospect—looking at an isolated case—but with tens of thousands of calls a week about hundreds of issues, it’s much harder to identify these trends. Organizations are struggling to see through the chaos of this big data.
Advanced tools for predictive analytics offer the ability to provide proactive customer service, enabling organizations to reduce call volume and deliver better customer service. This is done by preventing the next/first customer call by predicting and fulfilling the next customer need. No magic is needed.
The Next Call Prevention proactive customer service approach provides very tangible benefits to both customers and organizations, manifested through better customer experience, a stronger bond between the customer and the organization, and reduced operational costs.