$300K in spreads in 90 days on niche county data
$300K in 100 days operating a remote Egypt-to-US wholesale operation with a 7-person team.
About
Alex, based in Egypt, spent three years building cold callers and systems for 14 to 16 US investors. He sold the agency, went 50-50 with a US acquisitions partner, and now runs the data, dispositions, and calling side.
Operating market
Indiana and Ohio. The team spread into Texas, Florida, and North Carolina, made less profit, and pulled focus back to those two states.
Favorite features
The Challenge
Alex is a software engineer from Egypt who spent three years in US wholesaling without owning any of it. He worked agency-side as a client success and data department head, then ran his own agency. He staffed cold callers, acquisition managers, and disposition managers for 14 to 16 American investors, big and small. Every system he built made someone else the money. The last investor he partnered with finally asked why he was not doing this for himself. He sold the agency and went principal, splitting 50-50 with a young US acquisitions manager.
The first months proved how thin a new operation can spread. They started in Indiana, then added Texas, Florida, Ohio, and North Carolina, pulling PropStream lists alongside county records. They were not losing money, but profit shrank as the map grew. The fix was the opposite of expansion: cut back to Indiana and Ohio and go deep on fewer records.
What They Built
Pulling fewer records and dialing them until they answer
Instead of 50,000-record vacant lists, the team pulls around 10,000 tightly filtered county records: evictions, probates, foreclosures, first to market. Monthly filtering inside DataSift keeps the data clean, and an API connection to ReadyMode feeds the dialer without manual exports.
Instead of pulling a list of 50,000 vacants, we'd only pull 10,000, but we would literally dial them over and over and over again, using REISift to basically monthly filter out the data, keep track of everything.
Running a US deal team from Egypt
Two cold callers, one acquisition rep, one disposition manager, and two VAs work remotely from Egypt. His American partner handles acquisitions and contracts on the ground, and everything splits 50-50. On the morning of the call, agents dialing for two hours had already produced six qualified leads.
Qualifying hard so the funnel math holds
Bad leads do not pass into the pipeline, and the ratios stay stable because of it. Roughly 12 to 13 qualified leads produce a contract. On first to market records, about one in five qualified probates becomes a deal.
Out of every 12 to 13 qualified leads, we get the contract and with FTM records out of every five probates, we got a deal.
Targeting the owner who shows up on ten lists
A DataSift case study from another investor, Kara, reframed his approach: stop counting records, start counting motivation signals stacked on a single owner. The owner on ten lists gets the heavy targeting, not the 300,000-record pile.
Before and After
Before DataSift
- Achieved Data Clarity
- Consistent Deal Flow
- Inconsistent Deal Flow
- Poor Marketing Flow
- Little Data Clarity
- Relied On Google Sheets
- Consistent Deal Flow
- Data Clarity / Organization
- Wholesales, Flips And Does Retail
- Strong Marketing Flow
- Didn't Understand Data Management
- Strong Real Estate Agent
- Wanted To Break Into Wholesaling But Didn't Know How
- Healthy Scale
- Data Driven Decisions
- Consistent Deals
- Strong Marketing Flow
- Inconsistent
- Little Data Insight
- Unorganized Bulk Marketing
- Strategic Focus on Niches
- Enhanced Lead Flow and Certainty
- Streamlined Marketing Process
- Efficient Use of Data
- Direct Mail & Deep Prospecting
- Broad, Unfocused Strategy
- Inconsistency in Results
- Dependency on Luck
- Marketing Clarity
- 6 Figure Months
- High Deal Volume
- Strong Marketing Flow
- Proper Data Management
- Weak Marketing Flow
- Poor Data Management
- Lack of Focus
- Manual Efforts
- Successful Scale
- Total Data Clarity
- Clear Marketing Approach
- Large Deal Spreads
- Improper Data Management
- Poor Marketing Method
- Inconsistent Deal Flow
- Strong Marketing Flow
- Clear Data Management
- Clear Data Management
- Successful Scale
- Many ways to close deals
- Large deal spreads
- Poor data management
- Unable to scale properly
- Poor marketing flow
- Smaller Deal Spreads
- Increased Deal Volume
- Platform Utilization
- Realtor Collaboration
- Funding Efforts
- Lots Of Deals
- Data Driven Decisions
- Strong Marketing Flow
- Sales And Marketing Clarity
- Poor Data Management
- Poor Marketing Flow
- Relied On Bulk Marketing
- Lack of Clarity
- Automated Acquisition
- Strong Marketing Flow
- Data Driven Decisions
- Structured Follow-ups
- Increased Lead Generation
- Achieved Sales And Marketing Clarity
- Manual Acquisition Processes
- Ineffective Marketing Flow
- Minimal Lead Insights
- Poor Follow Up Flow
- Inconsistent Lead Generation
- Lacked Sales And Marketing Clarity
After DataSift
- Achieved Data Clarity
- Consistent Deal Flow
- Inconsistent Deal Flow
- Poor Marketing Flow
- Little Data Clarity
- Relied On Google Sheets
- Consistent Deal Flow
- Data Clarity / Organization
- Wholesales, Flips And Does Retail
- Strong Marketing Flow
- Didn't Understand Data Management
- Strong Real Estate Agent
- Wanted To Break Into Wholesaling But Didn't Know How
- Healthy Scale
- Data Driven Decisions
- Consistent Deals
- Strong Marketing Flow
- Inconsistent
- Little Data Insight
- Unorganized Bulk Marketing
- Strategic Focus on Niches
- Enhanced Lead Flow and Certainty
- Streamlined Marketing Process
- Efficient Use of Data
- Direct Mail & Deep Prospecting
- Broad, Unfocused Strategy
- Inconsistency in Results
- Dependency on Luck
- Marketing Clarity
- 6 Figure Months
- High Deal Volume
- Strong Marketing Flow
- Proper Data Management
- Weak Marketing Flow
- Poor Data Management
- Lack of Focus
- Manual Efforts
- Successful Scale
- Total Data Clarity
- Clear Marketing Approach
- Large Deal Spreads
- Improper Data Management
- Poor Marketing Method
- Inconsistent Deal Flow
- Strong Marketing Flow
- Clear Data Management
- Clear Data Management
- Successful Scale
- Many ways to close deals
- Large deal spreads
- Poor data management
- Unable to scale properly
- Poor marketing flow
- Smaller Deal Spreads
- Increased Deal Volume
- Platform Utilization
- Realtor Collaboration
- Funding Efforts
- Lots Of Deals
- Data Driven Decisions
- Strong Marketing Flow
- Sales And Marketing Clarity
- Poor Data Management
- Poor Marketing Flow
- Relied On Bulk Marketing
- Lack of Clarity
- Automated Acquisition
- Strong Marketing Flow
- Data Driven Decisions
- Structured Follow-ups
- Increased Lead Generation
- Achieved Sales And Marketing Clarity
- Manual Acquisition Processes
- Ineffective Marketing Flow
- Minimal Lead Insights
- Poor Follow Up Flow
- Inconsistent Lead Generation
- Lacked Sales And Marketing Clarity
What changed
Alex niches down instead of scaling list size. He works first to market county records, evictions, probates, and foreclosures, plus small PropStream lists. Instead of 50,000 vacants he pulls 10,000 and dials them on repeat through the ReadyMode integration. He refilters the data in DataSift every month so the team only dials current records.
The team made $300K in wholesale spreads in 90 days, with almost $600K more in contracts that ghosted or backed out. A contract lands from every 12 to 13 qualified leads, and about one of every five qualified probates turns into a deal. The operation started with two cold callers, one acquisitions manager, and one dispositions manager.
Instead of pulling a list of 50,000 vacants, we'd only pull 10,000, but we would literally dial them over and over and over again, using REISIF to basically monthly filter out the data, keep track of everything, and with the API key going with ready mode, it's been like an absolute blast, honestly.
The Results
In roughly 100 days the operation made $300K in wholesale spreads. Over the same stretch another $600K in contracted spreads died: sellers ghosted, backed out, or deals fell through. Alex's own accounting is blunt. Follow the complete DataSift system from day one and the total lands at $600K or more. The miss is part of the math, and he says it out loud.
The before and after is ownership. Three years of agency work meant fees while 14 to 16 clients kept the spreads. Six to seven months after going principal, his own 50-50 operation banked $300K in about 100 days. The funnel behind it is countable. Two hours of dialing brought six qualified leads. Roughly 12 to 13 qualified leads bring a contract, and about one in five qualified probates becomes a deal.
It's honestly not that big of a deal as everyone thinks. I think it's just a data game and you have to plan it out right.
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