4 Ways to Leverage Artificial Intelligence in Customer Service

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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% 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% of service decision makers say their organizations are actively looking for ways to use AI and AI adoption (forecasted to surge by 143% 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 with the goal of reducing 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 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.

Conclusion

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, 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
Ivan is Chief Operating Officer of Jolt Consulting Group, a company exclusively focused on assisting companies improve their customer experience and accelerate growth. Ivan and his team deliver success business outcomes for their clients across the entire customer journey by assessments of their sales and service delivery, optimization of business processes, operating metrics, and deployment of enabling technologies. As a consultant, Ivan has worked with clients across 10 industry verticals to transform their operations. Contact Ivan at [email protected].

1 COMMENT

  1. By leveraging AI to understand the customer better, taking advantage of real-time decisioning and predictive analysis, providing a hyper-personalized experience, and using AI chatbots to engage the customer, the customer journey can be improved through all touchpoints and across all channels.

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