PROBLEM
Asurion's experts engage with millions of customers annually through the Asurion Hub messaging platform, providing essential tech support. A significant portion of these customers, approximately 20%, have multiple chat sessions over time. To ensure efficient problem resolution, experts need a streamlined process for reviewing past sessions, regardless of when they occurred.
SOLUTION
By utilizing this capabilities of generative AI, we can provide Asurion's experts with the relevant information they need, when they need it. This will significantly improve the workflow for the experts and enhance the overall user experience for Asurion's customers.
OPPORTUNITY
Introducing a contextual session summary reduces Average Handle Time (AHT), saving costs for the business. Experts can handle more sessions with efficiency, boosting productivity. This enhancement not only benefits the experts' earnings, as they are compensated per session and based on their CXP ratings, but also boosts overall customer satisfaction.
In the previous messaging platform, experts faced challenges while reviewing a customer's previous conversations. My initial research and discovery revealed that past messages were not effectively utilized by experts. The absence of clear session distinctions and the need to scroll through an endless timeline resulted in repetitive questioning, negatively affecting the customer experience. When the team and I began discussing the possibility of incorporating a session history feature in the new messaging platform, I was excited about the opportunity to explore and revamp the approach. Our aim was to provide a more efficient solution that would significantly enhance the customer and expert experience.
I analyzed and mapped out the user flow for both customers and experts, establishing a foundation for the design process. To foster collaboration, I facilitated a brainstorming session with key stakeholders from product, engineering, and UX content. Together, we addressed the major issues seen in the old messaging platform and generated innovative ideas for improvement. This cross-functional collaboration greatly contributed to team alignment as we progressed through the design and development stages. Key outcomes from the session included leveraging generative AI, eliminating the endless scroll, implementing a search functionality, providing additional context, limiting the history window, and introducing follow-up messages for experts.
I partnered closely with the UX content team to evaluate the capabilities of generative AI in producing the necessary information for experts based on various prompts. To gain stronger buy-in from the team, I conducted an initial experiment by inputting an old chat transcript into ChatGPT. I prompted the model to generate both a summary and a follow-up message for the next expert, as required. This experiment served as a quick and effective way to demonstrate the potential of generative AI and gather support from the team.
Before diving into explorations and wireframes in Figma, I started by sketching out initial ideas. These concepts were guided by the major capabilities the team and I had identified through collaborative brainstorming, considering both the team's insights and the capabilities of the model. Building upon these ideas, I further refined the designs and concepts, ultimately creating a prototype to gather valuable user feedback from the experts.
Experts responded overwhelmingly positively to the session summary feature, expressing excitement about its potential to save time during their workflow. Through conversations with the experts, I gathered valuable input and addressed their questions, particularly regarding the most beneficial type of context. Incorporating this feedback, the initial prototype was adjusted to better cater to the experts' needs and leverage the AI-generated information effectively.
After gathering insights from the experts, I met with my cross-functional team to review the designs and address any concerns, red flags, or questions. As a team, we discussed the iterative nature of this feature and made the decision to remove the end session modal from the flow.
The team diligently built and launched the first iteration of this feature with great sucess. The experts highly anticipated its implementation, and they have shared their positive experiences with this feature noting a boost in productivity and numbers of sessions handled daily.
MALLORY MICHAEL
(205)914-8889