$61,644 net from a rehashed liens list
Closed a $60K deal from a lead everyone else would have thrown away. Follow-up is the cheat code.
About
Joshua runs a lean direct to seller wholesaling operation in New Jersey, marketing by SMS to lien-stacked records. A year into DataSift, rehashing his own tracked data replaced constant new list pulls.
Operating market
Joshua works New Jersey, where lien records run township by township. He emails each municipality for the exact payoff, sewer, water, taxes, and code violation fees included.
Favorite features
The Challenge
Joshua runs direct to seller SMS marketing in New Jersey as a solo operator. Go High Level handles his conversations and PropStream supplied the data. The old way was volume: pull a 10,000-record list, blast it, then buy more when the replies dried up. Leads that never answered got left behind. One liens-list prospect first received his texts in February 2024 and went silent for the rest of the year.
The waste stayed invisible because nothing was tracked. Wrong numbers went unlabeled, files got mislabeled, and the same records were skip traced twice. "You're not tracking your data. Really just burning through your marketing spend," is how he puts it now. Liens themselves cut both ways too. He has watched surprise backend payoffs kill whole deals, so guessing at a payoff amount was never an option he trusted.
What They Built
Filtering the account for the people never reached
Joshua uploaded his Go High Level history into DataSift in May 2024 to create one base of record. His rehash filter is simple: records with a mobile number, no status or no response, stacked with a lien tag. That list is who gets the next campaign, not a fresh data purchase.
Adding the follow-up text that does the heavy lifting
He changed his settings so every unanswered initial text triggers a follow-up the next day. The same message that failed in February landed in December because of the second touch.
We sent out that message on December 12th. No response. And then the follow up ensued on December 13th at the same time. And then he responded letting me know that he was interested.
Getting the exact lien payoff before the offer
Instead of guessing at debt, he emails the township for the exact payoff: sewer, water, taxes, board-ups, and code violation fees. He positions it the way a title company would, as a buyer under contract who needs the number to close. That figure sets the seller's walk-away expectation before terms are agreed.
Tracking wrong numbers so rehashes stay cheap
Every attempt, wrong number, and tag gets logged. He says that single habit is the difference between spending about $500 on skip tracing and spending $2,000, and it is why his spend stays small relative to what the business produces.
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
Joshua markets direct to seller over SMS, working liens lists in New Jersey. When a list goes quiet he does not buy replacement data. He filters his account for records with a mobile number, no response, and a lien tag, then reruns them with a follow-up text added.
One record sat silent from February 2024 until a rehash text on December 12 and a follow-up on December 13 drew a reply. The stack ran deep: 15 year ownership, liens, code violations, tenant occupied, a senior owner with health issues. Joshua locked it up at $100,000 on the first call, wholesaled it, and netted $61,644.24, his biggest deal at the time.
I know a lot of people would just say, okay, they didn't respond. Let's get some more data. Let's just run, run back the race, but I feel like doing that rehash combined with sending that follow-up text really helped.
The Results
The deal posted at $61,644.24 net profit on a liens-list rehash, contracted at $100K. The record carried the full stack: 15-year ownership, liens, code violations, tenant occupied, a senior owner with health issues. It entered his account on May 24 and closed on January 22, eight months of tracked follow-up, with the reply arriving one day after the December 12th text.
The contrast is the point. Under the old model that lead was garbage, marked unresponsive and buried under the next 10,000-record purchase. Under the rehash model it became the best January in company history. He is honest about the other side too: the months since have been rocky, and he paused heavy marketing to build AI infrastructure before scaling back up.
There's so many deals already sitting in your account from people that you haven't contacted.
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