GREGORY A. BENNETT
This case study explores how a series of customer site visits to two international service centers drove design recommendations for a chatbot building platform that could encourage positive agent-chatbot collaboration. The first part of the case focuses on the research undertaken by a team of user experience practitioners at the enterprise software company Salesforce. The team used contextual inquiry and group interviews to better understand the daily experience of customer service agents and service teams in search of ways to responsibly implement automation tools like chatbots within a service center environment. The second part of the case study highlights how the UX team applied these learnings into specific product recommendations and developed a set of principles that could drive the product forward while remaining empathetic and supportive of customer service agents....
This paper draws on a discovery research project focused on the customer experience of Intrepid Travel's automated booking system. The Data Analytics team initially investigated customer behaviour when booking and found problems with high exit rates on the first and second steps of the 3-step booking process. A paradox was also found between the numeric NPS and CES scores for booking, and comments which revealed high volumes of customers requiring assistance from customer service to complete their online booking. The Product Manager for this project prioritised an extended discovery research phase to provide a more holistic understanding of the customer experience of online booking and answer some questions that arose from customer behaviours highlighted by the Data Analytics team. The UX Researcher's task was to design a research project that would analyse why customers were struggling to complete Intrepid Travel's automated booking process and provide recommendations to improve this system for a...
IDEO Chicago and DePaul University
Case Study—This case study provides an inside look at what occurs when methods from the data science and ethnographic fields are mixed to solve perennial customer service problems within the call center and cruise industries. The paper details this particular blend of ethnographic practitioners with a data scientist resulted in changes to design approaches, debunking myths about qualitative and quantitative research methods being at odds and altering team member perspectives about the value of both. The project also led to the creation of innovative blended design research and data science methods to discover and leverage the right customer data to the benefit of both the customer and the call center agents who serve them. This paper offers insight into the untold value design teams can unlock when data scientists and ethnographers work together to solve a problem. The result was a design solution that gives a top-performing company an edge to grow even better by leveraging the millions...
Nissan Research Center – Silicon Valley; Massachusetts Institute of Technology
Nissan Research Center – Silicon Valley
In this paper we explore the idea of a system of care through a city transit system. We argue that a systematic orientation to care is central to what makes a transit system work for people. Further, we suggest that this care orientation is recognized as such, even though it is not apparent in typical modes of systems management. Care is what knowing in this system is for. We examine how participants in the system navigate different epistemic bases of their work, focusing on how care work and information work intertwine. How is this work practiced and known? And how could we, as design researchers, use these practices to design systems of care? In service of these goals, we expand the notion of care work toward care of non-human actors as well as that of people. We focus particularly on the roles of automation and the risks automation presents for care. In a moment of increased...