v2.5 · 2024
Pest Leads Pro
End-to-end lead generation SaaS: traffic from SEO pages, backlinks, paid ads, and digital PR; Lead Wizard + AI Pest Advisor chat widget; gatekeeper pipeline (normalization, quality score, pricing); n8n Router Agent for vendor match, credits, and notifications. Digital PR automation detects incident spikes, generates press pages with embeddable trend charts, and runs outreach (Hunter.io) for earned backlinks. Background n8n agents for SEO content, performance, audits, and reporting. Stack includes PostgreSQL, vendor portal, SMS/email, and production-hardened frontend (FAQ/geo widgets, embed API, email templates).
Next.js
PostgreSQL
n8n
OpenAI
TypeScript
SEO
Context
Pest Leads Pro is a lead-generation SaaS aimed at pest-control operators: inbound traffic from SEO, backlinks, paid acquisition, and digital PR, with a guided Lead Wizard and an AI-assisted chat (Pest Advisor). Behind the scenes, leads pass through normalization, quality scoring, pricing, and routing to vendors—with credit handling and notifications orchestrated through n8n.
What we were solving
Operators need predictable lead flow and trust that routed jobs match their capacity and geography. The product had to combine marketing surfaces (landing pages, PR-led spikes), a conversational intake, and automation that doesn’t drop edge cases—while staying observable and changeable without redeploying the core app for every workflow tweak.
Approach
Next.js on the front for fast marketing and app surfaces; PostgreSQL as the system of record; n8n for Router Agent behavior, credits, notifications, and background agents (SEO content, performance, audits). Digital PR automation watches for incident spikes, generates press-ready pages with embeddable trend charts, and plugs into outreach (e.g. Hunter.io) for earned links. Vendor portal, SMS/email, and hardened UI components (FAQ, geo widgets, embed API, email templates) sit in the same product mindset: production first.
My role
End-to-end product engineering across frontend surfaces, integration points with automation, and operational hardening—so marketing, intake, and routing stay coherent as the product evolves.
Outcomes & notes
The stack is built for iteration: workflows can move in n8n while the core domain stays in PostgreSQL and typed APIs. That split keeps ship cadence high for growth experiments without sacrificing data integrity.