Discussing the status of Lab Results
Brief
A medical company provides cholesterol lab testing. It needs to update its in-app chatbot to cater to users asking for updates on their cholesterol lab results. These lab studies are outsourced.
We assume the chatbot is designed for visual and touch-only experiences, with no near-term plans to voice-enable it, nor integrate it with Siri, Google Assistant, or IVR support systems. The chatbot is also assumed to be used by users, no more than once a week. The app is also assumed to have legal approval to access, parse, and display lab results.
Duration: This Design jam lasted just over 2 hours. (1½ hours for brainstorming scope and content, and 45 minutes for documentation)
Solution
A key user pain point was the uncertainty of when results would arrive. This is alleviated by:
Providing estimated delivery times of results
Explaining why recent results may be missing
Providing the option to be proactively notified of results
Additionally, contextual greetings, the display of results, and the explanation of results were other important avenues. Improving these avenues of inquiry would help match users’ mental models of a chatbot that can handle the delivery status of their results.
* Portions of these Conversational Designs, that impacts other teams, are explicitly marked for team discussions.
Process
Initially, the brief was scoped and light secondary research was conducted. This research informs an understanding of customer journeys and mental models. Afterwards, brainstorming was done to scope out content.
1. Potential User Inquiries are noted and clustered into groups. (These groups can be shifted and sub-divided in future, based on passive user feedback)
2. Potential ways of responding to clusters of user questions were then formulated. These are structured as modular components of responses. Conversational logic is also considered, for ambiguous questions and variables.
3. Finally portions that require input from external teams are documented (e.g. new visual timeline widget, backend systems for delivery notifications).
Next Steps
This process shows how Conversational Designs can been created. The process assumes a good understanding of relevant customer journeys. After a Conversational Design is drafted, scopes and timelines can be verified with relevant teams (e.g. Visual, Research, Backend Systems). Finally, pilot releases can facilitate rapid iteration of these architectures prior to a full release.