Analyzing a wholesale lead by hand means pulling comps, guessing at rehab costs, and doing MAO math on a calculator — for every single property. Offr AI's deal analysis feature runs that process automatically for every lead your search generates, so a list of 25+ properties comes back with numbers attached instead of just addresses.
What deal analysis outputs, field by field
Every property card in a search result carries the same set of fields, so you can compare deals apples-to-apples:
- Property address and basic details — bed/bath count, square footage, lot size, and year built, pulled from public records.
- ARV (After Repair Value) — a dollar estimate of what the property would sell for once fully renovated, based on nearby sold comps.
- Estimated rehab range (low/high) — a total repair cost band generated from available photos, broken into categories like roof, kitchen, bath, flooring, and systems.
- MAO (Maximum Allowable Offer) — the ceiling price you could pay and still hit your target margin, calculated from ARV and the rehab estimate.
- Motivation signals — tags like pre-foreclosure, vacant, probate, tax-delinquent, absentee-owner, code-violation, FSBO, or stale-MLS, when detected.
- Offr Score — a single ranking number that combines all of the above so you can sort a list from most to least promising.
Inputs required
To get a full analysis, the platform needs: a buy box description (location, property type, price range, and any motivation filters you care about), and — once a property is identified — its address so it can pull comps and county data. Photos (from the listing, MLS, or your own upload) are what drive the rehab estimate; a property with no available photos will still get an ARV and motivation tags, but the rehab range will be less precise or unavailable.
How the scoring math works
- You enter a buy box in plain English (e.g., "single-family, 3+ bed, under $180k, pre-foreclosure or vacant, in Maricopa County").
- Offr AI queries public and county records for properties matching that criteria across all 50 states and returns 25+ candidates.
- For each property, the ARV engine pulls the most similar recent sold comps nearby and adjusts for size, bed/bath count, and location to produce an ARV.
- Available photos are analyzed room by room to flag visible condition issues, producing a low/high rehab total.
- MAO is computed using the standard wholesaling formula: MAO = (ARV × target percentage) − estimated rehab − your assignment fee/margin.
- Motivation signals detected in county and public records are layered on top as tags.
- ARV, rehab, MAO, and motivation signals are combined into the Offr Score, which you can sort and filter the list by.
Worked example
Say a search returns a 3-bed/2-bath single-family home flagged as pre-foreclosure and absentee-owned:
- Sold comps nearby average $215,000 for similar homes in good condition → ARV = $215,000
- Photos show a dated kitchen, worn flooring, and an aging roof → rehab estimate = $28,000–$36,000 (use $32,000 as your working number)
- Using a common wholesaling target of 70% of ARV minus rehab: MAO = ($215,000 × 0.70) − $32,000 = $150,500 − $32,000 = $118,500
- Subtract a $10,000 assignment fee if you want your actual offer ceiling to the seller: offer ceiling ≈ $108,500
- With two motivation signals present (pre-foreclosure + absentee owner) and a healthy ARV-to-rehab ratio, this lead lands near the top of the Offr Score ranking for that search.
Where it can be wrong, and how to check by hand
- ARV can be off in areas with few recent comps, or when a property has unique features (a view, an oversized lot, a nonstandard layout) the comp-matching logic doesn't fully capture. Pull your own 3-5 comp list from a local agent or MLS access before finalizing a price.
- Rehab estimates only reflect what's visible in photos — plumbing, electrical, foundation, and roof-decking issues can be invisible in pictures. Add a contingency (many investors use 10-20% on top of the AI estimate) and get a contractor walkthrough before writing a contract.
- MAO is only as good as the ARV and rehab numbers feeding it, and it assumes you know your target percentage and margin — adjust the formula's inputs to match your own buying criteria rather than accepting the default assumptions blindly.
- Motivation signals reflect the county record's last update, which can lag actual status by weeks or months in some counties.
How it fits the rest of the workflow
Deal analysis is the hub that the other features feed into: AI ARV estimation and the rehab cost estimator generate the numbers, seller intelligence supplies the motivation tags, and lead scoring turns it all into the sortable Offr Score. Once you've picked a promising lead, skip tracing gets you the owner's phone number, and the CRM carries the deal through outreach and contract. Everything lives inside the same app — see pricing to get started.