From cold spreadsheets to 300+ qualified seller leads a month
A 12-agent realty team was burning 40 hours a week scraping listings, cross-checking ownership data, and sending follow-ups by hand. We replaced the whole chain with an automated engine: scraping, enrichment, verification, and a personalized outreach sequence that hands agents warm conversations — not raw lists.
- 0
- qualified leads / month
- 0
- manual work removed weekly
- 0
- ROI inside 90 days
The challenge
Where it started
The team's pipeline ran on elbow grease: agents pulled expired listings and FSBO data from portals by hand, cross-checked ownership in county records, pasted everything into a shared spreadsheet, and sent follow-ups whenever they remembered. Across 12 agents that added up to roughly 40 hours a week of research — done inconsistently, duplicated between agents, and abandoned entirely during busy closing weeks.
The cost wasn't just time. Follow-up speed decided who won the listing, and they were routinely days behind investors running automated outreach. Their CRM was half-empty because data entry competed with actual selling — so management had no reliable picture of the pipeline at all.
The approach
What we built
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1
Define the target, precisely
We workshopped their ideal seller profile into hard criteria: expired listings, FSBOs, and high-equity owners in five farm ZIP codes — turning "good leads" from a gut feeling into a query.
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2
Automate sourcing and enrichment
Apify scrapers pull matching listings nightly; n8n routes them through Clay for ownership and contact enrichment, then triple-verifies phone numbers and emails. Duplicates across agents became impossible by design.
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3
Personalize outreach at scale
OpenAI generates a first line referencing the specific property and situation — days on market, neighborhood, listing history — feeding a multi-touch email and SMS sequence with reply detection.
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4
Hand off warm, not raw
Interested replies land in HubSpot as scored deals, round-robined to agents with an instant mobile alert. Every workflow reports failures to a monitored Slack channel.
The stack
- n8n
- Apify
- OpenAI
- Clay
- HubSpot
The results
What changed
Ninety days in, the engine sources and works more prospects in a night than the team previously managed in a week. Agents start their morning with warm conversations instead of research tabs, management finally trusts the pipeline numbers, and the system's running cost is a fraction of one part-time assistant.
“We went from arguing about who builds the lead list to arguing about who takes the next warm seller call. I'll take the second argument every time.”
Your operation has a story like this waiting to happen
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