Lead qualification
Outbound AI Lead Qualification Agent
An outbound voice agent that calls a real-estate lead, introduces the service, qualifies them on budget, timeline and property preferences, and writes every answer to a sheet.
01 / THE PROBLEM
Why this matters.
Real-estate leads go cold fast, and the first call is always the same handful of qualifying questions. Doing them by hand means slow follow-up, and answers that live in someone’s notes instead of a shared record.
02 / THE DIRECTION
The solution.
A Retell voice agent driven by n8n. It places the call, introduces the service, asks the qualifying questions — budget, timeline, property preferences — and writes the answers into Google Sheets. Conditional follow-up and callback flags are wired end to end, so a lead who asks to be called back is marked for it.
My role.
Designed and built the agent and its n8n workflows. Personal prototype, validated with live test calls only — not a client or production deployment.
03 / ARCHITECTURE
How the pieces connect.
System flow
- 01Lead list
- 02Outbound call
- 03Introduce the service
- 04Qualify: budget · timeline · preferences
- 05Answers to Google Sheets
- 06Follow-up / callback flag
04 / ENGINEERING DECISIONS
Designed with intent.
- Ask one qualifying question at a time, the way a human ISA would, rather than reading a script.
- Write structured answers to a sheet as the call happens, so qualification is a record and not a recollection.
- Flag callbacks and follow-ups explicitly instead of leaving them to whoever reads the notes.
05 / EVALUATION APPROACH
What needs to hold true.
- Validated with live test calls end to end: call placed, questions asked, answers written, callback flags set.
- Never run against real leads.