No deal was posted or sold this week. Instead, the team asked the audience directly whether they wanted more live comping or more buyer calls - 62% voted for more comping. So this session became a teaching clinic: reviewing three deals wholesalers submitted (a Philadelphia rowhouse, a Detroit 3-bed, and a Dallas flip), correcting each seller's optimistic ARV guess with real comps, and stress-testing Investorlift's AI ARV tool against manual analysis.
What we covered:
Why off-market sales should never be used as comps - they weren't tested by the retail market, so they typically sell for less than a property would fetch through the MLS
How basements, garage conversions, and lot differences can swing ARV by tens of thousands of dollars, even between properties that look nearly identical from the street
Why major roads, train lines, or even which side of the street a house sits on can mark a hard line between two completely different subdivisions - crossing one cost a past deal $75K off its expected ARV
How to comp deals in non-disclosure states like Texas, where sold prices aren't public: track active and pending listings, price-drop history, and days on market instead of relying on Zillow or Redfin's sold data
How Investorlift's AI ARV tool (built on P70 pricing logic) held up against manual comping across three very different deals - matching closely on two, and flagging why non-disclosure states can skew its estimate higher
The big lesson this week: sellers often anchor to an optimistic ARV, and a few minutes of real comping - checking actives, pendings, basements, and neighborhood dividing lines - can move that number by six figures before you ever price a deal to sell. The team is back to live buyer calls on a fresh deal next week.
🎬 Watch the replay and see the entire process in action:
Watch the recording