In a previous post, we discussed why the customer experience is driving investments in the contact center. More specifically, the customer experience is driving the need for contact center analyticsas organizations rely on customer feedback to guide business decision-making. Traditional means for collecting feedback, such as surveys and interaction monitoring, are still valuable tools. However, advanced analytics are required to overcome the complexity of the modern contact center, automate quality management processes across multiple channels, and better understand customer interactions.
There are a number of different types of contact center analytics, including:
- Speech Analytics. Voice calls are monitored in real time to identify ways to increase efficiency and improve the customer experience by improving processes, updating call scripts or deploying tools that allow agents to resolve issues more quickly.
- Text Analytics. More and more customer interactions are happening via email, chat, instant message, text and social media. Text analytics can monitor and review these interactions to identify and address problems from the customer’s perspective.
- Predictive Analytics. By analyzing historic data across channels, predictive analytics can forecast patterns and trends. This allows you to optimize staff levels, predict the impact of certain events on contact center activity, and improve metrics such as call volume, service level, handle time and customer satisfaction.
- Self-Service Analytics. Organizations can reduce costs, call volume and errors by enabling customers to complete certain tasks online themselves rather than contacting an agent. Self-service analytics can help you improve the quality of these offerings and overcome barriers to adoption.
- Desktop Analytics. By capturing an agent’s desktop activity and monitoring how the agent uses contact center tools, you can monitor and optimize everything from agent performance to contact center security and efficiency.
- Cross-Channel Analytics. By understanding what channels customers are using, how often and for what purpose, and how well agents are performing in each channel, organizations can tailor their services at the channel level to ensure customer expectations are met.
One of the primary challenges faced in the contact center is the reliance on large volumes of data from multiple systems that cannot or do not communicate. Customers demand a seamless experience across channels and may even use a new channel before you’ve integrated it into your contact center environment. For example, your organization may not promote customer service through social media, but if a customer contacts you through Facebook or Twitter about an issue, are you going to ignore that inquiry?
Contact center analytics is capable of integrating data from disparate sources so you can understand both individual customer preferences and larger customer service trends. The more you measure, the more effectively you can manage the environment. Instead of operating in a reactive mode that waits to fix problems after the fact, analytics enables you to shift to a proactive model that monitors interactions, predicts potential issues and prevents them from happening. This not only keeps customers happy but allows you to reduce contact center costs. Preventing problems is a lot less expensive and resource-intensive than trying to solve them.
IPC can help you expand and integrate your contact center channels and deploy an analytics solution that allows you to take full advantage of your contact center data. Let us help you make sure your contact center is capable of delivering the kind of experience your customers demand.