Two different models, two different bets. Here's what each one really delivers, with numbers we can back up.
How does PropScored compare to Offrs? Offrs runs AI predictions on which homeowners might list in the next 12 months, then buys ads to catch their info. PropScored doesn't predict anything. I pull leads straight from public-record filings, liens, pre-foreclosure, bankruptcy, that prove a homeowner is already distressed or motivated, and every customer gets the full county-verified dataset.
Both companies chase the same truth: in real estate, being first in the door wins listings. The split is in how each company picks who to knock on, and how stale that pick is by the time it reaches you.
Give them their due. Offrs built a real business on predictive modeling, they claim over 250 data points per homeowner and say their algorithm predicts more than 70% of listings in a market. They lean on a documented NAR stat that 3 out of 4 homeowners list with the first agent they talk to, a legitimate, well-cited industry finding.1 Their Lead Guaranty, a promised lead volume per tier, with automatic territory expansion if they miss it, is a clean, agent-friendly commitment. And their three-stage funnel (predictive sellers → seller signal leads → in-market leads via email nurture) is a real system, not a data dump. If you want broad-market prediction with ad infrastructure and nurture built in, Offrs has clearly put the work in.
Not everywhere. Not for everyone. I'll say that upfront. PropScored doesn't guess who might sell, it sources leads from homeowners who've already filed something in the public record that proves real motivation: a lien, a pre-foreclosure notice, a bankruptcy. I scrape every source daily. Across 1,142 timestamped filings, the median gap between a filing hitting the record and it becoming a sourced lead is 2 days, bankruptcy in 1 day, pre-foreclosure in 3, liens in 7 (county lien lists land as periodic bulk loads, the lone exception to daily refresh). Most batch platforms in this space, like PropStream, refresh on 30-90 day cycles. Read more on why freshness compounds over a filing's lifecycle.
Across 5,265 sourced prospects, 84% carry a verified phone or email (69% a phone, 64% an email, many with both), and the number moves by signal type: FSBO sits at 96%, liens at 97%, pre-foreclosure at 95%, expired listings at 82%, tax delinquent at 81%. Offrs doesn't publish a comparable contactability figure anywhere on their site, so I can't put the two side by side, only note that PropScored's number is measured and disclosed, not a marketing line.
Every customer gets the full metro-Atlanta dataset, county-verified, no zip limits, for one flat price. Coverage runs 11 distress signal types across metro Atlanta counties in Georgia (DeKalb, Gwinnett, Cobb, Fulton, Cherokee, Forsyth, Hall, Henry, Clayton), with distressed-seller leads as a core category. Offrs runs national with a broader territory model. If your farm sits outside those Georgia counties, that fact alone might settle it for you.
| Dimension | Offrs | PropScored |
|---|---|---|
| Data source | AI prediction + ad capture | Public-record filings |
| Refresh cycle | Not disclosed | Daily (median 2 days) |
| Dataset access | Territory-based | Full dataset, no zip limits |
| Contactability | Not disclosed | 84% verified phone/email |
| Motivation signal | Predicted (12-mo model) | Confirmed (county record) |
| Best for | Broad-market farming, national reach | Georgia distress niches, verified data |
Predictive models guess at motivation; PropScored confirms it. Every lead traces back to a real public-record filing, bankruptcy, pre-foreclosure, liens, not a propensity score. Harvard Business Review found the winning move is reacting fast to customer-driven signs of interest. A court filing or tax delinquency is exactly that: a recorded event, not a probability. That's why freshness and verified distress beat algorithmic guessing.
If you want a national predictive-lead engine with ad campaigns and email nurture baked in, and you're fine with a looser definition of