Signify Health
Dialer Insights
Role
Senior UX Designer
Tools
Figma
Dialer Insights is an enterprise web application that enables our operation team to control the flow of membership that is being called. This is based on client needs, campaigns, and pilots that are being conducted. This helps Signify Health reach their annual in-home and virtual health assessment goals by targeting and calling particular members at a given time.
Objective
Signify has goals of completing millions of health assessments a year, and to accomplish this our operations team adjusts Dialer Insights to push members through the call system, Five9. As our call volume increases, we have an increased risk of being flagged as spam which then impacts our member reach rates.
To mitigate being blocked and marked as spam, we wanted to implement an automatic round robin approach where fresh numbers will cycle and at-risk phone numbers have time to cool off. We also needed a new interface to add new numbers, map phone numbers to client membership, and add and adjust any associated voicemails.
KPIs:
Pick-up rates increase
Scheduling rates increase
Semi-structured Interviews
Before diving into designs, I drafted guiding questions to talk through flow and process with the operation analysts who will be handling this phone number control process.
I met with the group over Google Meets to discuss general flow of handling phone numbers, way that we determine fresh phone numbers, where we receive new phone numbers, and reasons to deactivate phone numbers.
Phone Number Pools Designs
Based on the discussions, I found that a new pool of phone numbers is usually received from Five9 after being “warmed up” via a CSV file. I wanted to easily allow the operations team to quickly upload the list to Dialer Insights by simple drag and drop, but also enable the flexibility to add or change individually.
I also wanted to provide visualized outreach rates to the user to monitor phone number pools and its impact on the members. Since the users are internal and the tool specific, I was able to gauge sentiment quickly around designs as I was wireframing.
Results
After establishing the UI and incorporating data pulled from Snowflake, we’ve been able to easily identify phone numbers marked as spam and have the system automatically cycle through the phone numbers. If outreach limits are being met by the phone number pool, the operation analysts have the ability to add new numbers and maintain control over at-risk numbers.
Although we’re still monitoring the results of our KPI measurements: pick-up rates and scheduling rates, we’re seeing an increase in pick-up rates across a few states.