Addressing identified issues will enhance users’ interaction with MYA.Ĭhatbots have become an important part of the financial services ecosystem.
A good and diversified user experience promotes prolonged chatbot use.
However, some technical issues were identified. Generally, MYA was considered to be welcoming, very easy to use, realistic, engaging, and informative. The lowest mean CUQ score was 40.6 for participants aged between 50 and 69 years. The highest mean CUQ score was 64.5 for participants who thought MYA could help increase their physical activity behavior. The mean CUQ score was below 68, the benchmark for average usability. Participants in a usability study answered a survey with the Chatbot Usability Questionnaire (CUQ), which is comparable to the Systems Usability Scale. MYA’s design includes behavior change techniques effective in increasing physical activity through digital interventions. The concept and the prototype development of the social media chatbot MYA were realized in three steps: requirement analysis, concept development, and implementation. The study’s objective is to explore users’ experiences with a social media chatbot. Chatbots, also known as conversational agents, have emerged in healthcare in relation to digital interventions and have proven effective in promoting physical activity among adults. Usability test outcomes confirm what is already known about chatbots - that they are highly usable (due to their simple interface and conversation-driven functionality) but conventional methods for assessing usability and user experience may not be as accurate when applied to chatbots.ĭigital interventions for increasing physical activity behavior have shown great potential, especially those with social media. Chatbot users reached optimum proficiency in tasks after just one repetition. The optimum number of users for identifying chatbot usability errors was 26, which challenges previous research. WeightMentor usability scores were generally high, and correlation between questionnaires was strong. WeightMentor was tested using a pre-determined usability testing protocol, evaluating ease of task completion, unique usability errors and participant opinions on the chatbot (collected using usability questionnaires). efficiency based on task completion times)? This paper describes the procedure for testing the WeightMentor chatbot, assesses correlation between typical usability testing metrics, and suggests that conventional wisdom on participant numbers for identifying usability issues may not apply to chatbots. This study addresses the following four research questions: How usable is the WeightMentor chatbot, according to conventional usability methods? To what extend will different conventional usability questionnaires correlate when evaluating chatbot usability? And how do they correlate to a tailored chatbot usability survey score? What is the optimum number of users required to identify chatbot usability issues? How many task repetitions are required for a first-time chatbot users to reach optimum task performance (i.e. WeightMentor is a bespoke self-help motivational tool for weight loss maintenance. The traditional best practices normally applied to User Experience (UX) design cannot easily be applied to chatbots, nor can conventional usability testing techniques guarantee accuracy. Chatbots are becoming increasingly popular as a human-computer interface.
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