AI-powered Symptom Checker for EyecareLive
Life SciencesBusiness Impacts
4.3/5
Average Customer Satisfaction Score
Real time Tracking of Unhandled Cases
24/7
Available Lead Generation Tool
Customer Key Facts
- Location : North America
- Industry : Healthcare and Life Sciences
Problem Context
EyecareLive provides a digital vision care platform that brings technology to the eye care providers, patients, pharmaceutical companies and industry partners. EyecareLive wanted to enhance their customer experience by offering a 24/7 available virtual assistant which could triage eye symptoms along with acting as a lead generation tool.
Challenges
- Training the virtual assistant to triage eye symptoms accurately, given that multiple symptoms are often common across complex eye conditions.
- Identifying returning users to enable the virtual agent skip repetitive questions and provide a customized experience.
Technologies Used
Dialogflow
Google Cloud Platform
Python
NODE.JS
Google Data Studio
Solution
Quantiphi developed an all-in-one chat enabled virtual assistant (VA) capable of triaging complex eye symptoms, assist patients to take eye tests and schedule appointments with the doctors. The smart assistant can also identify returning users and skip repetitive questions, thereby providing a seamless customer experience. The symptom checker-cum-lead generation assistant can also flag emergency cases and help the patients with the immediate next steps. A powerful Data Studio analytics dashboard has also been set up that helps business users gauge the VA performance and make impactful decisions to further enhance the VA's capabilities.
The virtual assistant is integrated with EyecareLive's back-end APIs for scheduling appointments and identifying returning users.
Result
- 24/7 available symptom checker as well as lead generation tool
- Availability of critical data points like eye symptoms and demographics data prior to connecting with patients saves precious time and efforts on Doctors' end
- Reporting & metrics that empower data-driven decision making
