Chatbot Quality Assurance Using RPA

Abstract

Chatbots are becoming mainstream consumer engagement tools, and well-developed chatbots are already transforming user experience and personalization. Chatbot Quality Assurance (QA) is an essential part of the development and deployment process, regardless of whether it’s conducted by one entity (business) or two (developers and business), to ensure ideal results. Robotic Process Automation (RPA) can be explored as a potential facilitator to improve, augment, streamline, or optimize chatbot QA. RPA is ideally suited for tasks that can be clearly defined (rule-based) and are repeating in nature. This limits its ability to become an all-encompassing technology for chatbot QA testing, but it can still be useful in replacing part of the manual QA testing of chatbots. Chatbot QA is a complex domain in its own right and has its own challenges, including the lack of streamlined/standardized testing protocols and quality measures, though traits like intent recognition, responsiveness, conversational flow, etc., are usually tested, especially at the end-user testing phase. RPA can be useful in certain areas of chatbot QA, including its ability to increase the sample size for training and testing datasets, generating input variations, splitting testing/conversation data sets, testing for typo resiliency, etc. The general rule is that the easier a testing process is to clearly define and set rules for, the better it's a candidate for RPA-based testing. This naturally increases the lean towards technical testing and makes it moderately unfeasible as an end-user testing alternative. It has the potential to optimize chatbot QA in conjunction with AI and ML testing tools.