Intelligence Becomes Pervasive In Customer Service Applications

In the age of the customer, consumers have more information, more choices, more access, and more power. But they don't have more time. That's why the companies that attract, win, and retain customers focus on delivering the tenets of great experiences: make it easy, make it effective, and build an emotional connection.

But, customer service organizations are hampered by a complex, brittle, and largely unintegrated contact center technology ecosystem that makes it difficult to deliver on the promise of great service.

As well, organizations that own the various customer service touchpoints historically have not shared the same objectives, funding, business processes, data management strategies, technology, or culture. On a tactical level, customer service leaders struggle to do the following:

  • Empower customers and agents with exactly the right knowledge. Customer service leaders know that the right knowledge delivered at the right time is critical to a successful interaction. When done correctly, knowledge, either curated or tribal, can be used to personalize an interaction, increase customer satisfaction, reduce call handle time, lead to operational efficiencies, increase customer engagement, and ultimately drive conversion and revenue.
  • Make their workforces more productive. Customer service agents use dozens of disconnected applications in the course of resolving a single customer issue, often duplicating data from application to application, or performing repetitive manual tasks. Customer service leaders cannot enforce standardized processes that reduce agent consistency or productivity, increase agent training times, or lead to high turnover rates due to frustration with their toolsets.
  • Do the right thing for the customer. Customers expect service interactions tailored to their personas, to their transactions and interaction histories, and to their current states. Yet customer service leaders can do little more than deliver service interactions tailored to broad customer segments. They cannot optimize process flows, decisions, or next-best actions for more personal and successful business outcomes that foster relationships, trust, and loyalty.

Customer service technologies are evolving to include intelligence. They make agents and customers smarter. They recommend answers and advice. They unburden repetitive, manual tasks. They prescribe the right actions or next steps to take within service processes. Some key intelligence technologies to keep an eye on are the following:

  • Contextual Knowledge Solutions. Knowledge management technologies amplify agent and customer intelligence by empowering them with curated content that is automatically refined over time based on use. Yet, no organization can keep up with the volume of content needed to address every product, service, or application variation that customers use. Peer-generated community content extends the reach of curated content. Search technologies extend discovery beyond the walls of a knowledge base and help understand customer intent and context, helping arm agents with exactly the right answers . And virtual agents also automate dialogs and knowledge discovery.
  • Agent Productivity Solutions. Robotic process automation helps customer service organizations automate repetitive, onerous tasks that kill agent productivity and incur errors because of the nature of the work. Text analytics and natural language processing can automate issue categorization. They can extract useful information from email and chats to quickly surface trends in issues and customer sentiment that could affect customer retention and loyalty.
  • Prescriptive Advice. Customer service organizations use decisioning—automatically deciding a customer's or system's next action—to route interactions to the right resource or recommend answers to customer questions, to present personalized cross-sell and upsell offers to customers, and to prescribe the right next set of steps for customers and agents. Machine learning makes decisioning and other intelligence technologies smarter by detecting patterns and correlations to create customer segments and make predictions about behavior.

Kate Leggett is vice president and principal analyst covering CRM and customer service at Forrester Research.