Real estate investor spending 20+ hours monthly screening Zillow manually across Milwaukee, Waukesha, and Racine. Solution: n8n + Apify Zillow scraper + RentCast API + dual-scenario ROI filter. Results: 300+ properties weekly, 30x coverage, $1,356/month saved, $144/month cost.
Dane invests in single-family and small multifamily properties across Milwaukee, Waukesha, and Racine. With hundreds of new Zillow listings hitting every week, manually running cash-on-cash calculations on each one was consuming entire afternoons. Deals that penciled out sat unreviewed because there was no bandwidth to evaluate them in time. In real estate, being the third person to call a motivated seller is rarely a winning position.
Before: Dane spent 20+ hours monthly scrolling Zillow, manually pulling comps, estimating rents, and calculating returns on individual properties. Coverage was limited to what one person could physically review in a day.
After: A daily n8n workflow screens every new listing in three target markets, runs dual-scenario ROI calculations against real RentCast rent data, deduplicates against previously alerted properties, and delivers a formatted Gmail report of qualified deals each morning before he opens his laptop.
Dane needed a way to evaluate every qualifying Milwaukee-area listing against a 12% cash-on-cash threshold, in both all-cash and financed scenarios, without spending his days buried in spreadsheets. The goal was deal flow coverage at scale, not optimization of a manual process.
We built a daily n8n workflow that pulls fresh Zillow listings from three Milwaukee-area markets, filters them against Dane's investment criteria, fetches real market rent estimates from RentCast, runs both all-cash and financed ROI scenarios against those numbers, deduplicates against a Google Sheets tracker, and emails formatted alerts only for properties that hit 12% or higher. The system handles the research layer entirely. Dane's job is to decide, not to screen.
Self-hosted workflow orchestration: daily schedule triggers, filtering logic, ROI calculations, and multi-step routing without platform fees
Zillow scraper actor pulling fresh listing data across three markets daily: address, price, tax estimates, insurance, and unit count
Real-time market rent API returning address-level comparable data: the foundation of an accurate ROI calculation rather than an estimated one
Deduplication tracker that logs every alerted property by address, preventing repeat notifications when listings sit on market unchanged
Daily delivery channel for qualified deal alerts: formatted with Zillow link, full financial breakdown, and RentCast comp data for instant decision-making
If you are a real estate investor manually screening listings that could be filtered in seconds, we should talk. We will map out exactly how this system would work for your criteria and target markets.
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Head of Sales
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Founder of JB Consulting
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Founder of Opia Intimates
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CEO at Contrago Digital LTD
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Data Analyst at Amundi
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Account Executive at Odoo
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Founder of GhostCopEU
As a Business Analyst at Deloitte, working with King of Automation made a huge difference. Their AI solution helped us quickly analyze research papers in PDF format, saving us hours of manual work. It was accurate, fast, and tailored to our needs. Andrea and his team were responsive and easy to work with. Highly recommended if you deal with heavy document analysis.
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Business Analyst at Deloitte
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