Call center ai · Production

MyPlanAdvocate makes Medicare enrollment twice as efficient with ElevenLabs Agents

The problem

During the seven-week Medicare Annual Enrollment Period, MyPlanAdvocate received thousands of inbound calls per day. Human-led pre-qualification created three systemic problems: capacity risk from hiring temporary staff, incentive-driven bias routing ineligible callers to licensed agents, and licensed-agent burnout from time spent on non-starters.

Workflow diagram · grounded in source
1
Inbound call received
trigger
“During this period, MyPlanAdvocate experiences thousands of inbound calls per day.”
2
AI verifies Medicare eligibility
ai_action
“The agent verifies Medicare eligibility conversationally, in real time, before routing qualified callers to licensed representatives.”
3
Route qualified callers
routing
“route only qualified callers to licensed agents”
4
Licensed rep handles call
human_review
“Calls that reached licensed agents after AI pre-qualification converted at 2× the historical baseline”
Reported outcome

The ElevenLabs AI voice agent handled approximately 210,000 inbound calls per month during AEP, and calls reaching licensed agents after AI pre-qualification converted at 2× the historical baseline, materially increasing revenue per licensed representative.

Reported metrics
inbound calls handled per month by AI~210,000
conversion on AI-qualified calls vs. baseline2×
Revenue per licensed representativematerially increasing revenue per licensed representative
Licensed-agent utilization and earningsImproved licensed-agent utilization and earnings
Show all 5 reported metrics
inbound calls handled per month by AI~210,000
conversion on AI-qualified calls vs. baseline2×
revenue per licensed representativematerially increasing revenue per licensed representative
licensed-agent utilization and earningsImproved licensed-agent utilization and earnings
wasted handle time during peak demandReduced wasted handle time during peak demand
Reported stack
ElevenLabs Agents
Source
https://elevenlabs.io/blog/myplanadvocate
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

The ElevenLabs AI voice agent handled approximately 210,000 inbound calls per month during AEP, and calls reaching licensed agents after AI pre-qualification converted at 2× the historical baseline, materially increas…

What tools did this team use?

ElevenLabs Agents.

What results were reported?

inbound calls handled per month by AI: ~210,000; conversion on AI-qualified calls vs. baseline: 2×; Revenue per licensed representative: materially increasing revenue per licensed representative; Licensed-agent utilization and earnings: Improved licensed-agent utilization and earnings (source-reported, not independently verified).

How is this call center ai AI workflow structured?

Inbound call received → AI verifies Medicare eligibility → Route qualified callers → Licensed rep handles call.

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