Automation and artificial intelligence (AI) increasingly handle routine tasks. Customer service agents already focus on escalations and exceptions. They need a powerful workspace to empower them to understand their customer, their journey, and their context.
They also need to be armed with the right knowledge and data to help solve hard problems. They need to be focused on work that matters. They need to connect with other resources. They need just-in-time training. They need tools to better connect emotionally with their customer.
No single-vendor customer service solution offers all of these capabilities today. This means that technology-powered customer service organizations must assemble these workspaces themselves.
Getting Started
I think of it as a four-step process:
1. Build a solid customer service agent desktop foundation. Start with a modern agent desktop solution from a customer service vendor. These solutions allow for basic customer identification such as phone numbers; emails; social handles; transaction-system-based customer IDs; and basic customer understanding. These solutions also allow inquiry capture, workflow, and resolution.
2. Maximize agent productivity with efficiency. Layer on process guidance to standardize agent actions through all the disconnected applications that they use. Options include scripts that guide agents through conversations and actions; tip balloons that break down processes into step-by-step instructions for agents to follow; unified agent desktops that present agents with a single pane of glass for all of their applications; and robotic process automation, in which software robots mimic human actions.
3. Improve agent effectiveness with better content and coaching. Curated content from within a knowledge base can only take you so far. Organizations should add on cognitive search solutions to extract information from data that resides in file systems, bug databases, streams, APIs, and other applications. Explore agent-facing chatbots to help understand an agent’s intent and surface the right content or data in line with the process. Look for ways to make training more bite-sized and available within the agent desktop, with content directly tied to quality results.
4. Leverage data insights to improve customer intimacy and predict next best actions. Use customer success solutions to surface a health score to help agents better understand their customers. Use customer analytics to extend profile data with demographic and relationship data for better matching. Use predictive analytics to provide next best actions for agents to take. Use real-time speech and text analytics to surface a customer’s emotions. Together, these tools improve outcomes by helping agents understand the value of the customer and their journey — for example, is this the first time they’ve called in or the fifth time?
There’s lots more to say about the changing nature of work in the contact center. Read my thoughts about the agent desktop here.
Kate Leggett is VP and principal analyst at Forrester Research. Read more Forrester blogs here.
