Not every distressed-looking property has a motivated seller behind it, and not every motivated seller looks distressed on the surface. Offr AI's seller intelligence pulls together multiple public data signals so you can judge motivation before you ever make contact — instead of guessing from curb appeal or a listing photo.
What seller intelligence outputs, field by field
Every property that has at least one motivation signal detected carries:
- Signal tags — one or more of: pre-foreclosure/lis pendens, probate, vacancy, code violation, tax delinquency, absentee ownership, FSBO, or stale MLS listing.
- Signal source — the record type each tag was pulled from (e.g., a county lis pendens filing, a tax assessor delinquency list, a code-enforcement citation).
- Signal count — how many distinct motivation signals apply to a single property; more overlapping signals typically move a lead higher in your priority list.
- Timestamp context — an indication of when the underlying record was last available, so you can judge how current a signal likely is.
- Downstream weighting — signal count and type feed directly into the Offr Score, so you'll see this reflected in ranking, not just as a raw tag.
Inputs required
Seller intelligence runs automatically on top of a buy box search — you don't request it separately. What you control is which motivation types you filter for: describe them in your buy box (e.g., "vacant or tax-delinquent only") to narrow results, or leave motivation unspecified to see every signal type across a broader list. No manual data entry is needed beyond the buy box itself; the underlying lookups happen against county and public records tied to each property's address.
How the signal detection works
- Your buy box search returns a batch of off-market properties from public and county data sources across all 50 states.
- For each property, Offr AI checks multiple record types: recorder's office filings (lis pendens for pre-foreclosure), probate court records, utility/postal vacancy indicators, code-enforcement citations, tax assessor delinquency lists, mailing-vs-property address mismatches (absentee ownership), FSBO listing sources, and MLS days-on-market data (stale listings).
- Any record type with a positive match gets attached to the property as a tag.
- Properties with multiple tags are not automatically ranked higher by a fixed multiplier — signal count and type are one input among several (alongside ARV, rehab, and MAO) that combine into the Offr Score.
- You review the tagged list, sorted or filtered by score, and decide which signals matter most to your calling strategy that week.
Worked example
A search for "single-family homes, Wayne County, MI, under $120,000" returns 40 properties. Seller intelligence tags them as follows:
- 14 properties: no motivation signal detected (matched only on price/location/type)
- 11 properties: single signal — either absentee-owner (7) or stale MLS (4)
- 9 properties: two signals — most commonly tax-delinquent + absentee-owner
- 6 properties: three or more signals — for example, one property carries pre-foreclosure + vacancy + tax delinquency
That six-property group with three-plus overlapping signals is the natural starting point for calls that day, since each additional independent signal generally correlates with a seller more likely to need a fast, as-is sale. The remaining 34 properties still get worked, just lower in the call queue.
Where it's uncertain, and how to verify by hand
- Recording lag: county recorder and tax offices update on different schedules — some counties post lis pendens filings within days, others take weeks. A "pre-foreclosure" tag could reflect a filing that's already been cured.
- False negatives: a genuinely motivated seller (recent divorce, job relocation, inherited property not yet in probate) may show zero signals simply because there's no public record trail yet. Don't treat an untagged property as automatically low-priority if it otherwise fits your buy box well.
- Vacancy and absentee-owner tags are inferred (e.g., mismatched mailing address, utility signals) rather than confirmed by a physical inspection — a quick drive-by or neighbor conversation is the fastest way to confirm before investing skip-trace credits.
- Multiple signals ≠ guaranteed sale — treat signal count as a prioritization tool for your calling list, not a prediction of deal probability.
How it fits the rest of the workflow
Seller intelligence is the layer that turns a plain property list into a prioritized one: it feeds directly into lead scoring, which combines signals with ARV, rehab, and MAO into the sortable Offr Score. Once you've picked which signals matter most for a given batch, skip tracing gets you a verified number to call, and the CRM tracks the outreach and outcome. See pricing for details.