How I Built a Programmatic SEO Engine to Find "Broken" Local Businesses (React & Vite)

Nifemi Jacob — Wed, 13 May 2026 20:56:35 +0000

How I Built a Programmatic SEO Engine to Find "Broken" Local Businesses (React & Vite)

When building B2B SaaS, the standard playbook for lead generation is basically just scraping Google Maps and handing users a massive CSV of business names and phone numbers.

But raw data is useless if there's no intent. Agency owners don't need more phone numbers to cold call; they need to know which specific businesses are actively failing technical checks so they have a real pain point to pitch.

I recently launched SignalQub, an AI lead generation engine that doesn't just scrape contact info, but actively scans local businesses for broken websites, missing SEO schemas, and terrible page speed.

Here is a breakdown of the architecture, the tech stack, and how I handled the programmatic SEO to scale the inbound traffic.

The Tech Stack

Frontend: React.js via Vite
Styling: Tailwind CSS
Deployment & Hosting: Vercel

The Architecture: Programmatic SEO at Scale

To drive organic traffic to a lead generation tool, you can't just rely on a homepage. Agency owners are searching for highly specific intent queries, like "Plumber leads in Texas" or "Best alternative to LeadSwift."

Instead of manually creating hundreds of landing pages, I built a programmatic SEO architecture.
I created a master template component in React that dynamically injects data based on the URL route. By passing a JSON dataset containing cities, niches, and competitor comparisons, the router dynamically generates hundreds of highly targeted, indexable pages.

Because it's a Single Page Application (SPA), I utilized react-helmet-async to ensure that every dynamically generated page outputs a strict, unique canonical tag and properly formatted Meta/Title tags. This prevents Google from flagging duplicate content and ensures maximum search visibility.

The Scraping Challenge: Bypassing Anti-Bot Systems

The hardest part of building an engine that scans thousands of local businesses is not the parsing logic—it's staying unblocked.

If you try to run concurrent scans using standard datacenter IPs (like AWS or DigitalOcean), you get rate-limited or shadowbanned almost instantly by modern firewalls.

To bypass this, the data extraction layer has to rely on CGNAT (Carrier-Grade NAT) via mobile proxies. By routing requests through rotating 4G/5G mobile IPs, the engine perfectly mimics real human mobile traffic. A firewall cannot ban a mobile proxy IP without accidentally blocking hundreds of real users on the same cell tower.

The Takeaway

Building this engine taught me that the value of data isn't in the volume; it's in the qualification. By combining a fast React frontend with a programmatic SEO routing structure and stealth proxy infrastructure, you can build a highly scalable lead engine that basically runs itself.

If you are an agency owner tired of cold calling dead leads, or just a fellow dev who wants to see the frontend architecture in action, check out SignalQub.

I’d love to hear how other devs are handling programmatic SEO routing in Vite—drop your strategies in the comments!

DEV Community: Nifemi Jacob

How I Built a Programmatic SEO Engine to Find "Broken" Local Businesses (React & Vite)

How I Built a Programmatic SEO Engine to Find "Broken" Local Businesses (React & Vite)

The Tech Stack

The Architecture: Programmatic SEO at Scale

The Scraping Challenge: Bypassing Anti-Bot Systems

The Takeaway