Automated WhatsApp Lead Nurturing with Postgres & Gallabox

This n8n workflow automates lead nurturing for Marketing Qualified Leads (MQLs) by querying Postgres for unqualified leads based on retry counts (0-3) and time delays (3-8 minutes). It processes each lead individually, selects tailored message content depending on the lead's model (e.g., nexus, magnus) and count, then sends interactive WhatsApp template messages via the Gallabox API with dynamic fields like name, phone, and quick reply buttons (Show Brochure, Get Showroom Location, Not Interested). Finally, it logs all interactions in a Postgres table for tracking.

Benefits include hands-free, personalized follow-ups that boost conversion rates, reduce manual sales efforts, and ensure compliance with retry logic to avoid spamming. The workflow scales effortlessly for high-volume leads, integrates seamlessly with existing CRM data in Postgres, and provides full audit trails via logs, saving hours of repetitive outreach.

Ideal use cases: Sales teams nurturing real estate or product leads via WhatsApp, e-commerce follow-ups, or any business using Gallabox for messaging. Deploy in CRM pipelines to qualify MQLs into SQLs, enhancing pipeline velocity without additional tools.