Optimizing Self-service Channels with Customer Interaction Analytics
Understanding why your customers are contacting you and what customer service channels will best meet those needs is pivotal to build an effective customer self-support system. Customer Interaction Analytics can help not only develop a robust self-service system, but also optimize the existing one for greater results.
By analyzing vast volumes of customer conversations, particular topics and issues can be detected, which are being discussed in every call. This will help identify call drivers and devise action plans to address those call drivers through an optimized self-help system. Website, IVR System, and SMS/Text Messaging are some of the widely used self-help options by customers. By evaluating customer interactions, customer interactions analytics reveals not only the issues impacting the performance of self-service channels, but also the opportunities for improvements.
For instance, if an agent receives a call that can be easily self-solved by customers using any self-service channels, it means that the existing system is inadequate and needs improvements. Similarly, if customers come to the support website, but finding themselves unable to self-solve their issues, they try reach to a live agent. It also clearly indicates that the support website needs to be enhanced. Therefore, assessing the effectiveness of the self-help system is vital to optimize it.
Performing the root cause analysis, Customer Interaction Analytics provides insights on how to improve the efficiency of self-help channels, including:
1:- Customer Support Website: Analysis of customer interactions can help identify key call drivers, customer needs, behavior patterns and the prevailing issues in the existing support portal. Using these insights, Website FAQs, knowledgebase, etc., can be tailored and improved for a better customer support and experience.
2:- Interactive Voice Response (IVR) System:Using Customer Interaction Analytics, insights can be gleaned from the customer journey before, during, and after the IVR contact. Leveraging the insights on revealed behavior patterns, IVR experience can be optimized by providing customized menu options pertinent to the particular journey. Besides, customer interaction analytics helps determine the inefficiencies of the existing IVR system, root causes of the call transfer, and the ways to improve it.
3:- Mobile SMS/Text Messaging:Based on the insights on customer needs, issues, and behavior patterns, SMS/text messaging can be optimized to enable customer self-help for updation, specific information, and confirmations. Moreover, agents can be trained on how to quickly re-route the incoming calls back to the self-help channels, which can be easily self-solved. For instance, if a customer calls a live agent to know about the monthly bill amount, he/she can be guided to use sms/text messaging to get this information easily.
Following are some of the key benefits of a well-designed Self-help System:
By building an effective self-help system and its continuous optimization, organizations can save millions of dollars yearly. Besides, following are some other important benefits of building a self-help system:
  • Faster Response Time
  • Improved Customer Experience
  • Reduced Call Volume
  • Better Handling of Customers’ Inquiries
  • Improved Agent Productivity
A well-optimized self-help system not only reduces the call volume, but also improves customer satisfaction and quickly connects customers with a customer service representative if required.
About Sheetal Kumari
Sheetal is an MBA with 6.5 years of experience in the publishing and the IT industry. She is currently working as an Assistant Manager in the RSI Marcom department.

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