Property Leads Pipeline
Qualify and manage buyer, renter, and site-visit inquiries captured by your WhatsApp real estate agent. Track deal pipelines, timeline preferences, and automated lead scores.
The Property Leads Pipeline
A real estate lead is generated automatically when a customer inquires about a property or states their purchasing preferences via WhatsApp. The AI parsing engine extracts budget thresholds, localities, BHK structures, and financing status.
The Leads Pipeline dashboard aggregates these parsed inquiries, allowing agents to oversee progress, update stages, adjust lead scores, add manual entries, and trigger live handoffs or site visits.
1. Core Pipeline Metrics
The dashboard tracks client engagement distributions across four operational KPIs:
Total Inquiries
Sum total of all property inquiries captured.
Score ≥ 75%
Highly qualified buyers showing strong intent.
Scheduled Tours
Leads with an active site visit booked.
Deals Concluded
Successful transactions marked as won.
2. Lead Data Schema
The properties matching engine processes client profiles using structured columns. The database fields include:
| Lead Property | Database Column | Type | Description & Values |
|---|---|---|---|
| Linked Property | property_id | UUID | Null | Reference ID of the specific listing the client originally inquired about. |
| Customer Phone | customer_phone | Text (Required) | Primary international contact number used for dispatching WhatsApp templates. |
| Customer Name | customer_name | Text | Null | Contact name extracted from profile payload or entered by agent. |
| Intent Type | intent_type | Text | Client's core goal: buy, rent, site_visit, or general inquiry. |
| Budget Boundaries | budget_min / budget_max | Numeric | Minimum and maximum budget ranges matching pricing parameters. |
| Preferences | preferred_citypreferred_localitypreferred_bhk | Text / Integer | Target geographic city, locality segment, and preferred layout size (BHK). |
| Financing & Timeline | financing_statustimeline | Text | Null | Payment state (e.g. loan approved, cash buyer) and purchase horizon (e.g. immediate, 30 days). |
| Lead Score | lead_score | Integer (0-100) | AI assessment score representing contact value and completeness. |
3. Pipeline Status & AI Scoring Automation
Leads are processed using lifecycle transitions and automated value calculations:
AI Lead Scoring Engine
As user parameters populate, the AI scoring script runs automatically to set lead_score:
- Base Weight (30%): Verification of correct WhatsApp contact number.
- Preference Completeness (40%): Having budget, BHK, and locality values extracted.
- Intent & Timeline (30%): Actionable parameters (e.g. cash buyer, immediate purchase timeline).
- Leads scoring above 75% are flagged as Hot Leads on the dashboard.
Lifecycle Stages
Leads follow a standardized progression tracked in the database:
new: Capture state.qualified: Criteria parsed successfully.contacted: Agent has engaged.visit_booked: Physical tour has been set.closed: Client closed deal successfully.lost: Dead lead.
Quick Pipeline Actions
Agents can fast-track leads through two direct action triggers in the leads table:
- Quick Qualify: Updates status column from
newtoqualified. - Quick Close: Updates status column to
closed, signifying deal conclusion. - Both actions prompt instant updates via Supabase clients.
Source & Channel Attributions
Understanding how inquiries enter the pipeline
Leads entering the Supabase database are automatically tagged with source parameters depending on their creation mechanism. The pipeline supports three channels:
WhatsApp Chatbot
Inquiries created through conversational parsing have source_channel set to whatsapp.
Website Widget
If submitted through the embeddable web chat, source_channel reads website_widget and registers the referral domain path in source_url.
Offline Uploads
Manual additions inside the dashboard populate the channel with a null marker, which fallbacks to displaying WhatsApp by default in lists.