Property Sourcers
How the company tripled their deal volume without adding a single hire
Three hours every morning, manually scanning Rightmove. A deal pipeline that filled overnight changed everything.
The challenge
Tom Blackwell started the company with a simple value proposition: find better deals faster than investors could find themselves, and charge a packaging fee for the privilege. Six people, a clear process, and an intimate knowledge of a handful of postcodes. It worked well enough to build a client base and a reputation.
The problem was that the deal identification process hadn't scaled with the team. Every morning, Tom and two colleagues would spend the first three hours of the day manually filtering Rightmove: searching by price reduction, scanning long-days-on-market listings, cross-referencing against their own criteria. It was exhausting, inconsistent, and entirely dependent on who happened to be online first.
Opportunities were being missed. A property that had been reduced by 8% overnight in a target postcode might sit undiscovered until mid-morning. By then, a faster competitor might already have made contact. In a business where time-sensitive information is the entire product, relying on a manual morning scan was leaving deals on the table every week.
The volume cap was also becoming a problem. Client expectations were growing: investors wanted more deals, more consistently. But there was no obvious way to increase throughput without hiring more people to stare at Rightmove.
"We were manually scrolling Rightmove every morning. Now our deal pipeline fills overnight. We're finding opportunities our competitors don't even know exist."
The solution
Automated nightly deal scanning across all target postcodes, with instant qualification using live comparables, and the Explore tool for visual opportunity mapping.
the company started with Homedata's Explore tool, the visual deal-finding interface, using a first top-up (matched 100%) to map price reductions and long-DOM properties across their target postcodes. The visual interface immediately identified several opportunities the manual Rightmove process had been missing entirely, and the team was convinced within the first session.
The automation layer came next. A nightly cron job calls the live listings search (/live-listings/search/, arranged per customer), filtered to reductions, across all 12 of their target postcodes. Properties that meet their criteria (reduction percentage, days on market, property type) are logged to a deal pipeline dashboard. Tom and the team arrive each morning to a pre-filtered shortlist rather than a blank search box.
When a property reaches the qualification stage, the comparables endpoint (/comparables/{'{uprn}'}/, arranged per customer) runs in seconds, giving an instant comparable evidence set that would previously have taken 20 minutes to assemble manually. The address retrieve endpoint provides verified Royal Mail contact data for direct approaches.
The result: deal identification time fell from three hours to under 20 minutes. Monthly qualifying deals sourced went from 15–20 to 45–55. Every investor client renewed their retainer within three months of the new process going live.
/live-listings/search/
Long DOM and reduced properties by postcode, the nightly deal feed. Runs across all target areas automatically.
/live-listings/search/
Current on-market properties, status, price, listing date, full inventory view across target postcodes.
/comparables/{'{uprn}'}/
Instant deal qualification, bedroom-matched comps within 0.5mi. Replaces 20 minutes of manual research per deal.
/api/public/address/retrieve/
Verified Royal Mail formatted address for direct vendor contact.
homedata.co.uk/explore
Visual deal-finding across target areas. Search free; reveal a full address for 20 tokens.
The results
Integration
The nightly pipeline calls the live listings search across 12 target postcodes: 12 API calls per run, scheduled at 2am. That feed is arranged per customer rather than sold self-serve, so it does not draw on a token balance. Before the standalone comparables endpoint moved to enterprise pricing, deal-level qualification added 10 tokens for comparables plus 5 for address retrieve per qualifying property, run as a background job when a team member flagged a lead. Comparables are now arranged per customer; address retrieve remains 5 tokens, and comparable data remains in the complete property profile. The company built the automation layer as a Python script with a simple Airtable front-end, the initial build took one freelance developer three days.
"We were manually scrolling Rightmove every morning. Now our deal pipeline fills overnight. We're finding opportunities our competitors don't even know exist."
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