Much has been written about the importance of Customer Experience (“CX”) and it has never been more important with record call volumes at contact centers during COVID-19 that is placing tremendous strain on contact center agents.
Discover what 80% of Americans are citing as the most important features of a positive CX experience.

Much has been written about the importance of Customer Experience (“CX”) and it has never been more important with record call volumes at contact centers during COVID-19 that is placing tremendous strain on contact center agents. These elevated levels are providing challenges to improving an organization’s CX as nearly 80 percent of Americans have cited speed and convenience, knowledgeable help, and friendly service as the most important elements of a positive CX.

The use of Artificial Intelligence (“AI”) in customer service is currently utilized in just under one-quarter of companies today, although, 56 percent of service decision makers say their organizations are actively looking for ways to use AI and AI adoption (forecasted to surge by 143 percent by 2021). AI, if implemented correctly, has the potential to improve both the internal contact center and employee-agent experiences by reducing time spent on routine tasks.  This increase in time will not only create a superior CX by increased first contact resolution rates and CSAT and/or NPS scores, but it will allow representatives more time to focus on solving complex issues.

  1. Intelligent Chatbots:  AI technology that simulates voice or text-based conversations with humans and Chatbots are very prevalent in today’s contact centers. The most common use case includes gathering initial case information and enabling self-service in simple scenarios to reduce manual workloads for agents.
  2. Automated Case Attributes:  Using information gathered by Chatbots or customer provided information to a contact center agent, coupled with historical case data, case AI automates the population of case attributes in new cases as they are being created. Case accuracy is improved by removing the agent guesswork involved in completing case fields; based upon these automated case attributes, the case can be automatically routed to an appropriate contact center employee who has the necessary skills, product expertise, etc. to increase first contact resolution rates.
  3. Recommended Actions:  This AI capability analyzes case data gathered during the case creation process coupled with historical case data to suggest the next steps or actions to agents. Those actions may involve selling activities (e.g., recommend providing an extended warranty quote for a product coming off initial warranty) or service activities (e.g., performs steps A, B & C to remotely triage the issue or immediately create a field service work order) and are intended to enrich the agent-customer experience by equipping the agent with more robust information and allowing them to deliver it to the customer.
  4. Predictive Analysis:  AI predictions based on historical data have the power to automatically present data to enable contact center agents to take proactive steps and make more intelligent decisions to improve the CX. For example, a case type with a certain set of attributes may have a high likelihood of not meeting a customer Service Level Agreements are automatically surfaced and proactive steps can be taken or those same case attributes determine that a field technician should be immediately dispatched to the customer’s location.

The term Artificial Intelligence can seem puzzling or futuristic, however, within contact centers, AI has tremendous potential to dramatically improve both the experience of the customer and the contact center agent. At their core, AI top use cases are helping companies to scale their support operations and to solve issues faster and more accurately the first time, freeing up agents to work on more valuable interactions with customers.

Citation

PwC, The Future of Customer Experience, 2018

Salesforce, State of Service, 3rd Edition, 2019

Ivan Moore

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