5 Capabilities to Make Case Deflection a Reality
Enabling customers to find the answers to their questions via self-service can improve your case deflection rate, minimizing the amount of time your customer support agents are dealing with customer issues and improving the overall customer experience. Following best practices for case deflection will make your self-service experience a success.
Case deflection depends on the effectiveness of your knowledge management system. If you have self-service content located in multiple places across different platforms, it’s important to ensure there’s a way to bring all of the content together and make it searchable. You can make case deflection and self-service success a reality by following these best practices:
#1: Identify your self-service content across all enterprise sources and channels, then unify search across all of it
#2: Make self-search prominent and mobile-ready
#3: Offer proactive insights
#4: Identify and resolve self-service gaps with usage analytics
#5: Use machine learning to continually improve search results and predict relevant content
Successful case deflection has multiple benefits. First, it reduces ticket case creation and therefore, the load on customer support teams, freeing up their time to deal with more complex or urgent issues rather than ones that should be able to be solved with self-service content. This can help decrease customer service costs as self-service channels are typically cheaper to maintain than support channels that require personnel. It can also improve customer satisfaction by providing instant access to information and reducing wait times and friction in the customer experience. Lastly, case deflection can provide valuable insights into customer behavior and preferences by capturing more data via self-service channels, and these insights can be used to optimize self-service channels and improve overall customer experience over time.
Case deflection will never fully remove the need for customer support agents, but a good case deflection rate will certainly mean that a large portion of customers are finding their answers through self-service. Depending on the type of business and the complexity of its products or services, the ideal case deflection rate will vary. For example, the average case deflection rate in the technology industry is 23%, and the average rate in the eCommerce industry is 24.4% (meaning 24.4% of customers are finding what they need through self-service rather than contacting support). A higher deflection rate would mean that more customers are able to find the information they need quickly and easily through self-service channels. A lower deflection rate would mean that self-service channels are not optimized, and customers are struggling to find the information they need. This can hurt your customers’ satisfaction and increase the need to contact a live agent.
AI can significantly improve case deflection strategy and success by providing personalized and relevant content to customers through self-service channels. With AI-powered chatbots, customers can receive instant responses to their questions rather than searching through content or contacting a live agent, increasing the chances of successful self-resolution. AI algorithms can also predict what content would be most relevant to the customer based on customer data like their past interactions, preferences, and online behaviors. This ensures that customers are directed to the most relevant content, reducing the need for human support. AI can also continually improve search results by using machine learning to analyze customer interactions and feedback, allowing for better search suggestions and results over time. Ultimately, AI improves case deflection rates by providing a seamless and personalized customer experience that results in successful self-resolution and minimized friction in the customer journey.
