3 Contact Center Metrics Improved by Predictive Analytics

Predictive analytics predict future events by combining various techniques that analyze historical and current patterns. Predictive voice analytics can have a major positive affect on integral contact center metrics, including customer retention, follow-up call success and quality assurance.

Customer Retention

One of the customer service industry’s main goals is customer retention, and experts believe that it costs more to acquire a brand new customer than to keep an existing customer. Predictive voice analytics, which analyze the customer’s voice during customer-agent interactions, can determine if the customer is at high risk for ending their relationship with the company altogether. It can then inform the agent that they need to put more focus on retaining the customer. On the flip side, predictive voice analytics can also tell which agents aren’t doing enough to keep the customer coming back. This is more effective than random checking for quality assurance, which can take a long time to identify poor-performing agents.

Follow-up Call Success

Often, the first contact with a customer isn’t the one that has a positive outcome (i.e. a sale); it’s the follow-up call that proves to be more advantageous. However, it’s difficult to know which customers are a priority for follow-up contact. Instead of leaving it up to your agents to determine which customers are worth a follow-up call, predictive analytics can analyze past interactions and study voice features to determine if the customer’s tone and behavior predicts a favorable outcome during the next interaction (like making a payment or finalizing a sale). Predictive analytics can create a ranked list of customers, organized by their likelihood to say “yes.”

Quality Assurance

Predictive analytics are a richer way of assessing quality assurance than traditional methods. Routine QA testing often ignores customer patterns, and it is also unable to learn in real-time. Predictive analytics, however, can analyze all types of data, both structured and unstructured, to give a well-rounded view of agent behavior and how it impacts the customer. All customer-agent communication is assessed in-the-moment, allowing the contact center to get an accurate view of agent performance immediately instead of having to wait several weeks.

Contact centers can’t just gather metrics to assess their current performance and then call it a day. They must also use what they’ve learned from the past to create goals for the future. Predictive analytics can help shape those goals realistically.

 

 

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