50 deals a year recycling one Philadelphia database
50+ deals/year across 2 companies. Text-first strategy reduces caller workload by segmenting lists via SMS before calling.
About
Adam Garner runs two wholesale companies out of Philadelphia, one residential and one commercial, alongside rentals, land, and multifamily rehabs. He bought his first two duplexes in college, then built the wholesaling side on DataSift over the past five years.
Operating market
Adam markets across most of southeastern Pennsylvania, Delaware, and New Jersey from his Philadelphia base. Philadelphia alone has 550,000 properties, so he stays in the better zip codes that still hold some distress.
Favorite features
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The Challenge
Adam Garner bought his first two duplexes in college with a partner, one seller financed on a five-year balloon. Six or seven years later he had rentals, wholesaling, and land deals running out of Philadelphia. When rates and construction costs killed the new-construction math, he shifted toward rehabs and multifamily. The deal engine had a harder problem. After five years of marketing, his database already covered the Philadelphia metro, 550,000 properties deep, plus southeastern Pennsylvania, Delaware, and New Jersey.
Fresh lists were mostly gone, so everything became a recycled campaign, and recycled data behaves differently. A pile of no-answers converts nothing like a fresh list, so lead flow got harder to predict and caller productivity swung with it. He had been deep prospecting by hand before he even knew tooling for it existed. The pinch point was capacity: two callers per company could not keep pace with the volume the database could feed them.
What They Built
Splitting the operation into two companies
One company works residential wholesale, with a closer Adam promoted up from lead manager. The other, run with a partner who came up as an appraiser, hunts commercial assets: fewer deals, bigger spreads. Each company carries its own transaction coordinator, so contracts never bottleneck on one desk.
Texting big lists first so callers only dial what matters
Standard data gets an SMS blast before anyone dials. Responses update statuses in the system: sold, not interested, still talking. What remains is a smaller, cleaner call list, which matters when texting scales faster than callers ever can.
Then the list is smaller for the callers because it takes more time to call than text.
Prioritizing the records that actually fall
Campaigns run in a strict order: probate and share sale first, then cold leads in good zip codes, then bulk no-answer passes. First to market probate rarely closes in month one, an honest zero most months. The filings fall later, if the follow-up lands on schedule.
What we found from the probate first to market was it's not a lot that we're taking down that first month right away, but they do start to fall down if you follow up with them every three months or so.
Recycling good zip codes instead of chasing the whole metro
Philadelphia alone holds 550,000 properties. Adam stays where values hold and distress still shows, skips the $6,000 land parcels, and lets the rest of the metro sit.
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
After five years on the platform, Adam holds the entire Philadelphia metro in his database, so almost everything he runs is a rehash campaign. Probate gets priority, and first to market probate leads rarely close in month one; follow up every three months brings them in. Text blasts go out before any dialing: texting is cheaper and faster, statuses get updated, and callers work a smaller list.
Each of his two wholesale companies runs two callers, one texter, and one salesperson. Last year they closed 48 or 49 deals; this year the two companies will do over 50. His residential closer started as a lead manager and now closes more than 20 percent of his offers.
I couldn't imagine like not having REI, seriously. I've built the wholesaling around it and it can do so much more than like what other CRMs or data management platforms can do.
The Results
The two companies closed roughly 48 to 49 deals in 2023 and project past 50 this year, mapped out in the profit and loss. That is about one contract a week across both companies. His residential closer, promoted from lead manager, now closes more than 20 percent of his offers. Offers only go to qualified sellers, which is why the ratio holds.
The before and after is a strategy inversion. Five years ago growth meant buying more data. Now first to market pulls add only incremental records, mostly probate filings with the personal representative attached. Everything else is recycled data that his own text-first sequencing re-segments into callable lists. To go past 50 deals, the plan is not more records. It is more salespeople, then more lead generators behind them.
I couldn't imagine not having REI, seriously. I've built the wholesaling around it and it can do so much more than what other CRMs or data management platforms can do.
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