One of the greatest opportunities for applying customer data and data analysis capabilities is in the contact center. That’s where contact center leaders and other decision makers can gain valuable insights about customer sentiment, customer behavior, indicators of customer churn, opportunities for upsell/cross-sell, etc.
Data analysis and data discovery can also be used in the contact center to identify opportunities for agent coaching and training as well as agent utilization and capacity planning, which can be used to drive higher agent productivity and customer satisfaction.
Moreover, contact center analytics can be used to identify peaks and valleys in call volumes and other types of digital customer interactions (chat, email, etc.).
Contact center managers can use data discovery to assist with agent scheduling based on anticipated surges in call volumes and to ensure that the agents with the right skills are available and can be matched with the right customers.
In a recent post, Ventana Research vice president and research director Tony Cosentino notes that 75% of call center managers and executives who have participated in one of Ventana’s benchmark surveys consider increasing agent utilization to be “very important” to them.
Cosentino describes how the use of data analysis and data discovery in the contact center is able to benefit companies. He points to one organization that has struggled with forecast variations across locations with respect to both hours and customer satisfaction. This struggle has resulted in sizable cost overruns in overtime hours as well as significant hits to overall customer satisfaction and loyalty scores.
By implementing supporting technologies and analytic capabilities across its call centers, the company has generated a 10% reduction in operating expenses, more than a 5% increase in customer satisfaction scores, and a positive increase in return on investment – all within a matter of months.
Data analysis tools can also help contact center leaders better evaluate the rising tide of unstructured data coming into the organization. As Ovum principal analyst Keith Dawson notes in a blog post, contact centers amass a lot of big data without considering it “big data.”
For instance, many contact centers record phone interactions between customers and agents for regulatory and quality assurance purposes. Customers share a great deal of information about aspects of a company’s products, services, and business processes that either frustrate or delight them.
Contact center leaders can use data discovery and data visualization tools to identify the things that matter most to customers and then take actions that can improve upon them and make it easier for customers to do business with their companies.
Speech analytics can also be used to help drive additional business for companies, according to an article in SearchCRM. Sales and contact center leaders can use speech analytics to identify cross-sell and upsell opportunities during certain types of customer interactions.
They can also use speech analytics tools to determine the most effective techniques used by agents to drive conversion. Such insights can be used to help coach and train agents on the most effective sales techniques that have been shown to drive successful outcomes.
