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 still struggle with complex, brittle and largely unintegrated contact center technology ecosystem that make it difficult to deliver on the promise of great service. On a tactical level, customer service leaders struggle to:

  • Empower customers and agents with exactly the right knowledge. Customer service leaders know that the right knowledge, right answers, delivered at the right time is critical to a successful interaction. When done correctly, knowledge- curated or tribal – can be used to personalize an interaction, reduce handle time,  increase customer satisfaction, operational efficiency, customer engagement, and ultimately drive conversion and revenue.
  • Make their workforce more productive. Customer service agents use dozens of disconnected applications when working on a single customer issue, often duplicating data from application to application, or performing repetitive manual tasks. Customer service leaders can’t enforce standardized processes which reduces agent consistency, productivity, increases agent training times, and leads to high turnover rates due to frustration with their toolset.
  • Do the right thing for the customer. Customers expect service interactions tailored to their persona, to their transaction and interaction history, and to their current state. Yet customer service leaders can do little more than deliver service interactions tailored to broad customer segments. They cannot optimize process flows and decisions – or next best actions – for more personal – and successful business outcomes that foster relationship, 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 a service process. Some key intelligence technologies to keep an eye on are:

  • 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 content. And chatbots  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 emails and chats to quickly surface trends in issues, and customer sentiment that may 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 to more effectively service customers. Machine learning makes decisioning – as well as other intelligence technologies – smarter by detecting patterns and correlations to for example, create customer segments, and make predictions about behavior.