Real Estate · RE/MAX brokerage team (US)

Agent Contact Data from a Gated MLS Platform

A two-stage extraction pipeline for the MLSPIN platform: bulk-parse the agent directory, then scrape emails and phone numbers from hundreds of authenticated profile pages into a clean CSV.

100sProfile pages
2Pipeline stages
5★Client review

How it works

The system, end to end.

extraction pipeline 04 steps
  1. 01 Parse directory names · IDs
  2. 02 Authenticated scrape saved login
  3. 03 Multi-strategy extract links · xpath · regex
  4. 04 Clean CSV CRM-ready

The problem

An independent US brokerage needed structured contact data — names, emails, phone numbers — from the MLSPIN agent directory for their outreach and CRM. The platform is gated behind authentication, offers no export, and collecting hundreds of agent profiles by hand wasn’t realistic.

The build

Stage one parses the agent directory into a CSV of names, offices, and agent IDs. Stage two drives an authenticated browser session through each agent’s profile page using a saved login state, so the scraper signs in once and runs for hours.

Contact details appear inconsistently across profiles, so extraction is multi-strategy: semantic links first, then targeted selectors, then pattern matching as a fallback — maximising coverage without false positives. Pacing is configurable with per-request delays and batch cooldowns to stay polite, and resume support tracks processed IDs so an interrupted run continues where it left off instead of starting over.

The result

The client received both the tooling and the fully scraped dataset — a CRM-ready CSV covering hundreds of agent profiles — with a five-star review on delivery.

Services used

How we built it.

Web Scraping & MonitoringPython Scripting & Bots

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