Shiny TechnologiesShiny TechnologiesWork with us

Field Note

Building an ElevenLabs voice assistant for insurance lead qualification

How we architect an AI voice agent that screens inbound calls, qualifies insurance leads, and routes warm prospects to sales without losing the human touch.

Published

Dec 15, 2024

Reading Time

8 min read

Topics

Voice AIElevenLabsLead qualificationInsurance

Key Takeaway

Voice assistants excel at top-of-funnel screening when you define qualification criteria upfront, instrument every handoff, and keep humans in the loop for complex cases.

Map the qualification workflow before writing prompts

Insurance lead qualification follows a predictable pattern: verify contact info, assess needs, check eligibility, and score intent. We document the exact questions top-performing agents ask and the decision tree they follow before we touch the ElevenLabs API.

This means sitting with sales ops to map BANT (Budget, Authority, Need, Timeline) criteria, compliance requirements for each product line, and the routing rules that determine when a lead gets flagged as "hot" versus "nurture."

  • Record and transcribe ten to fifteen top-performing qualification calls to extract the actual dialogue patterns.
  • Document the minimum viable data points required to create a qualified lead record in your CRM.
  • Define escalation triggers: when the caller asks about claims, disputes, or complex coverage needs, route immediately to a human.

Structure the conversation flow with guardrails

ElevenLabs Conversational AI works best when you give it clear instructions and structured outputs. We build the agent with a system prompt that defines the qualification script, tone boundaries, and data extraction requirements.

The conversation flow follows a three-part structure: greeting and consent, needs assessment, and next steps. Each section has fallback responses if the caller goes off-script or asks questions outside the agent’s scope.

  • Start every call with explicit consent: "This call may be recorded for quality and training purposes. Is that okay with you?"
  • Use structured data extraction to capture name, phone, email, product interest, and qualification score in real time.
  • Set conversation timeouts: if the call exceeds five minutes or the agent detects confusion, offer a callback from a human specialist.

Integrate with telephony and CRM in real time

The voice assistant becomes useful when it updates your systems of record during the call, not after. We wire webhooks from ElevenLabs to our middleware layer that parses conversation events and pushes structured data to the CRM and telephony platform.

This means when the agent confirms a lead is qualified, a lead record appears in Salesforce or HubSpot with the qualification score, product interest, and a transcript snippet before the call ends. Sales can see the lead light up in their queue and call back within minutes.

  • Use webhook events to capture conversation milestones: call started, qualification complete, escalation triggered, call ended.
  • Parse the transcript in real time to extract structured fields (name, email, product interest) using simple regex or an LLM extraction step.
  • Route qualified leads to the appropriate sales queue based on product line, geography, or lead score.

Instrument quality and compliance from day one

Insurance calls are regulated, so every conversation needs audit trails. We log full transcripts, consent recordings, qualification scores, and handoff reasons to a compliance-friendly data store.

We also set up a quality dashboard that tracks qualification rate, average call duration, escalation frequency, and post-call satisfaction scores. This data feeds back into prompt tuning and helps identify when the agent is struggling with specific question types.

  • Store all transcripts and metadata in a HIPAA-compliant data warehouse with retention policies that match your compliance requirements.
  • Flag calls that mention specific keywords (claims, disputes, complaints) for immediate human review, even if the agent handled them successfully.
  • Run weekly quality reviews where sales ops spot-checks five to ten calls and rates them against the same criteria used for human agents.

Tune the agent with real conversation data

The first version of the voice assistant will handle maybe sixty percent of calls well. The other forty percent reveal edge cases: callers who speak quickly, have heavy accents, ask unexpected questions, or need emotional support.

We review every escalated call and every low-scoring interaction to identify patterns. Those patterns become prompt updates, new fallback responses, or triggers for human handoff. After a month of tuning, most agents hit eighty to ninety percent automation rates.

  • Create a feedback loop where sales agents can flag problematic calls directly in the CRM with notes on what went wrong.
  • Use transcript analysis to identify common phrases or questions that trigger escalations and add them to the agent’s knowledge base.
  • A/B test different greeting scripts, qualification questions, and tone settings to see which combinations yield the highest qualification rates.

Next Steps

Move fast without breaking trust

Start with one product line

Launch the voice assistant for a single insurance product (e.g., auto insurance) to validate the workflow before expanding to other lines.

Build the integration layer

Create a lightweight middleware service that handles webhook events from ElevenLabs, extracts structured data, and updates your CRM and telephony systems.

Set up the quality board

Stand up a weekly review process where sales ops, compliance, and product review call transcripts, qualification rates, and escalation reasons to identify tuning priorities.

Ready to turn this into a scoped engagement?

We help teams implement these approaches with hands-on execution, not slide decks.