$141K+ from niche county data and returned mail
$141K+ net from niche marketing. 29 calls and 20 texts on biggest deal before closing.
About
From accidental landlord in Northwest Florida to real estate innovator, Peyton's journey is a tale of transformation powered by the First to Market Challenge, a bunch of strategic insights and the right tools.
Operating market
Northwest Florida
Favorite features
The Challenge
Peyton stumbled into real estate through an accidental rental in Panama City, FL. He bought a house, moved, could not sell it, and rented it out instead. Then Hurricane Michael wiped the city out and deals got easy. Bandit signs alone pulled in two or three qualified leads a day while he cut his teeth on active income.
A year or two later the easy market dried up and the bandit sign leads slowed with it. He had rental properties, a DealMachine driving for dollars habit, and no system behind any of it. He had met Tyler, who was marketing in Panama City, saw the software, and figured he would give it a shot. That was about three years ago, back when the platform ran on the old cloud. Today his whole operation runs inside it.
What They Built
50 county records a day across six counties
Everything Peyton markets to is county data. His team pulls six Florida counties, first to market, and calls through 50 records a day on a Sensei flow. The goal, in his words, is to get in front of everybody.
Three calls, then up to six pieces of mail
Each record gets three call attempts. If nobody answers, or every number is dead, it kicks instantly into a mail cycle of up to six attempts. No record exits the system between channels.
The main goal is to get in front of everybody. If we don't reach them, then we put them in a mail cycle.
Returned mail becomes a deal source
Mail that bounces back does not get tossed. Returned pieces drop into a deep prospect bucket for research, then kick back to the caller. The team has closed deals that started as mail failures.
Filter presets instead of boards
Peyton skips SiftLine boards for everything except active deals. His three virtual VAs run data intake, cold calling, and lead management from daily filter presets. Management is one Tuesday huddle: each VA brings their three hardest calls for review plus a KPI report.
I have filter presets that are like daily stuff that people need to do and it makes it kind of foolproof. They just log in, click the filter and they know what they're supposed to be doing.
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
- Tens of Thousands Spent on Masterminds That Never Fit
- Got Crushed Wholesaling Cleveland Virtually From New York
- Career-biggest payoff under agreement after a year of deep prospecting
- A 1,300-lead vacant property gold mine in two counties
- One shared database with his agent wife for three years
- Guru models demanded VAs and a big company he never wanted
- His investing and her listing business never connected
- Ten years flipping houses with no shared system
- One Call and One Text Found His Last Buyer
- A Deal About Every Three Weeks, Pushing for Two
- Eight Deals Working in the Middle of the Slowdown
- A $7,000 Mail Campaign Went Out at 56 Percent of Value
- Three to Five Active Listings in Every Subdivision He Underwrites
- Colorado Prices Down 9 to 11 Percent by May
- Callers Hunt Correct Numbers, Closers Take Over
- Returned Mail Tagged And Worked As Its Own Bucket
- 6 Deals In One Month From Year-Old Data
- Eight Months In Before Working The Data Right
- Bulk Dials On Call Tools Produced Nothing
- 100K Records Added, Team Spinning Its Wheels
- Mail, three call attempts, then the rehash pool
- 150 records a month, skip traced twice before dialing
- Full authority probates only, five Southern California counties
- 15 to 20 grand across seven months of last year
- Calling agents and MLS, never direct to seller
- No CRM, just a phone, a computer, and email
- $56K Largest Single Assignment
- A VA Pulls County Probate Data Daily
- $5,300 Total Expenses, About $441 A Month
- $210K In Fees From 7 Deals In A Year
- Every Conversation Started Cold
- No Pipeline, No Aged Database, No Team
- Random Calling On Whatever Records He Found
- Started September 2023 With No Probate Experience
- $95K Spread Closed In 21 Days
- All Four Questions Answered On Every Lead
- 120 Qualified Sellers In The Pipeline
- $1M+ Company With SMS As The Core Channel
- Tracking It All In Podio, Then Another CRM
- Doing What Everybody Else Was Doing
- Downloading Every Record Providers Would Give Him
- Churn And Burn Message Blasts
- One Contract For Every 10 Leads
- 100% Of Deals Sourced Inside The System
- $1M+ In Assignment Fees In 2023
- Almost All Deal Flow From Driving For Dollars
- Bouncing Between Tools Looking For One That Stuck
- Leads Tracked In Excel Sheets, Antiquated And Scattered
- First Flip Finished And Live On Market
- Partner Funding Instead Of 18-22% Hard Money
- Probate Cleared In A Week And A Half
- About One Deal Per 15 To 20 Doors
- Door Knocks The Foreclosure List Top To Bottom
- Severely In Debt, Couldn't Keep Up
- A Couple Of Years To Get In Gear
- Worked Hard For Two Weeks, Then Stopped
- 12 Years In Oil And Gas, Then Nothing Left
- $10K Deal From A Q3 Not Interested Lead
- Follow Up Brought The Seller Down $40,000
- Two First To Market Contracts In One Week
- Dedicated Caller Works The First To Market Flow
- Eviction Records Pulled Straight From Two Counties
- Outbound Marketing Completely Phased Out
- Credit Card Debt From Bad Marketing Advice
- Two Years Of Shiny Object Crash And Burn
- Absurd Data Subscription Costs Draining The Business
- $61,644 Net From A Lien List Rehash
- Tracks Wrong Numbers, Cuts Skip Trace Spend
- Emails The Township For Exact Lien Payoffs
- Rehash Filters: Mobile Numbers, No Response, Liens
- Next Day Follow Up Text Gets The Reply
- Lien Lead Silent Since February 2024
- No Follow Up Text After A Silent First Message
- Unknowingly Recycling The Same Data
- Pulling 10,000 Record Lists The Old Way
- 15 Heirs Signed, $37,500 In One Month
- Skip Trace, Upload To Sift, Call Fast
- Small Problem Lists Over Huge Data Sets
- Targets Deeds Of Trust 12 Years Or Older
- Checks County Foreclosure Postings Every Morning
- Bulk Absentee And Owner Marketing Dried Up
- 150 Mile Days Driving Project To Project
- Six Renovations Running At One Time
- Full Time Rehabbing Since 2015
- Sellers Now Calling In From Her Mail
- One Hot Lead Plus Tons Of Correct Numbers
- Mails Only The 54 Absentee Petitioners First
- Google Form Auto Formats Data For Upload
- Pulls Probate Filings Daily Across Three Counties
- Left A Company, Unsure She Could Pull It Off
- Tedious Copy And Paste List Formatting
- Struggled To Pull Data From Her County
- Years In California Trying To Figure It Out
- 135,000 Records Organized Into Buckets
- A Lead Every 10-15 Calls
- Pre-probate Inherited Niche, 60% Sell Within Two Years
- New Process Closed Its First Deal In 30 Days
- Thursday Deep Research, Offer Accepted By Monday
- PropStream Lists And Bought Probate Data
- Return Mail Dead-ended, Records Sat Dormant For Years
What changed
Meeting Tyler and discovering DataSift revolutionized Peyton's approach, shifting from ad-hoc efforts to a structured, data-driven strategy that supercharged his real estate business.
The Results
The niche system has produced $141K+ in net revenue. The deal he walks through on camera is his favorite: a hurricane damaged house he found driving for dollars with DealMachine. His VA left a voicemail. The owner called back a year later, still asking for that VA by name. By closing, the record log showed 29 call attempts and 20 SMS attempts, 49 touches on one deal.
The seller had roughly $130K to $140K in the property after five years of contractor runaround. The contractor offered $140K, so Peyton offered $141K in good faith and won the deal. Renovation ran about $70K to $80K, call it $211K to $221K all in. The property went under contract to sell at $385K with a $10K seller concession. He is honest about the gap in the machine too. His three biggest deals ever came from driving for dollars, and he has not been back in the car lately.
You can look at any record in my account and see anything that's ever happened to it, which I think that's huge because you can reverse engineer successes and failures.
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