Real Estate & Roofing Glossary

A property owner who does not live at the property they own. Absentee-owned properties are a high-priority target list because owners managing property remotely are statistically more likely to sell, especially when combined with other distress signals.

The estimated market value of a property after all repairs and renovations are complete. Used by wholesalers and flippers to calculate maximum allowable offer (MAO) and determine deal viability.

The transfer of a purchase contract from the original buyer (wholesaler) to an end buyer. The assignment fee is the wholesaler’s profit margin. Speed of assignment depends on buyer network depth and property acquisition cost.

Your specific acquisition criteria for a deal. Defined by property type, location, price range, condition, equity position, and other filters. A precise BuyBox allows predictive data platforms to surface only the properties matching your ideal deal profile.

An investor who purchases properties without financing. Cash buyer lists are used by wholesalers to quickly assign contracts. Match rate between your motivated seller lists and local cash buyer networks directly impacts assignment speed.

Historical data on which property profiles convert from lead to signed contract. The Feedback Engine tracks close rate signals to refine which homeowner types are most likely to approve a roof replacement proposal.

Direct outreach by phone to property owners on a targeted list. Effectiveness is determined by data quality, dial volume, contact rate, and script. Predictive-scored lists significantly improve conversation rate compared to generic county records.

Total marketing spend divided by the number of deals closed from that channel. The single most important metric for evaluating lead source ROI. Predictive-scored lists typically reduce cost per deal materially compared to generic lists.

Physical mailers sent to property owners to generate inbound seller leads. ROI depends on list quality, mail piece design, offer, and follow-up cadence. Operators using predictive-scored lists typically see 3-5x higher response rates than broad direct mail.

Any data point indicating a property owner may be motivated to sell. Examples include tax delinquency, pre-foreclosure filing, code violations, divorce filings, probate, vacancy, or high equity combined with absentee ownership. Stacking multiple distress signals on one property creates higher-probability leads.

Physically driving through neighborhoods to identify distressed or vacant properties. Combining physical observation with predictive data creates a powerful acquisition channel. 8020REI provides scored routes optimized for door-knocking efficiency.

The difference between a property's current market value and what the owner owes on it. High equity properties are primary targets because sellers have room to accept below-market offers and still net a meaningful payout.

A data refinement system that learns from closed deals to improve future list scoring. When you close a deal from a list, that data point trains the model to surface similar properties more accurately in future deliveries.

The legal process by which a lender reclaims a property after a borrower defaults on their mortgage. Foreclosure filings are a high-signal distress indicator, often used in combination with equity data to identify motivated sellers before the property hits auction.

The difference between a property’s market value and outstanding mortgage balance. High-equity homeowners are more likely to approve roof replacement projects because they have financial capacity and incentive to protect their investment.

Any channel that generates potential acquisition opportunities. Common lead sources include direct mail, cold calling, SMS, driving for dollars, PPC advertising, and referral networks. Data quality is the primary differentiator between high-performing and low-performing lead sources.

An arrangement where only a limited number of clients receive the same territorial data. 8020REI caps clients per county so that the data advantage stays with the operator who locks the territory first.

The practice of overlapping multiple motivated seller lists to identify properties appearing on two or more. A property on the absentee owner list AND the tax delinquent list AND the pre-foreclosure list is statistically far more likely to sell than one appearing on a single list.

The roofing material installed on a property, asphalt shingle, tile, metal, slate, flat/TPO, etc. Material type affects expected lifespan and replacement cost, and is a key input in predictive scoring models.

The highest price an investor can pay for a property while maintaining target profit margins. Calculated as ARV minus repair costs minus desired profit minus holding and closing costs.

A property owner with a pressing reason to sell quickly, often at below-market value. Motivation can be financial (tax delinquency, foreclosure), situational (divorce, probate, relocation), or physical (property condition). Data platforms identify motivated sellers by stacking distress signals.

A cluster-level signal showing multiple properties in a geographic area with similar roof characteristics. When several roofs in a neighborhood are the same age and material, replacement tends to happen in waves, one job leads to referrals from neighbors.

Public records of building permits filed for a property, including prior roof replacements, additions, and repairs. Permit history reveals maintenance patterns and helps predict when the next replacement cycle is due.

The period between when a lender files a default notice and when the property goes to auction. Pre-foreclosure is one of the highest-conversion lead types because sellers have a finite window to resolve the default and are often open to investor offers.

A machine-learning model that assigns a probability score to each property indicating likelihood of sale. Scores are calculated from hundreds of data points including ownership tenure, equity, distress signals, neighborhood trends, and historical transaction data.

The legal process of settling a deceased person's estate. Probate properties are a strong motivated seller signal because heirs often prefer a fast, clean sale over managing inherited property. Probate lists require timely access to county court filings.

A predictive score indicating the likelihood that a property will need a roof replacement within a defined time window. Calculated from roof age, material type, storm exposure, permit history, and neighborhood patterns.

The percentage of contacted property owners who respond to outreach. Direct mail response rates typically range from 0.5% (generic lists) to 2-3% (predictive-scored lists). Higher response rates directly reduce cost per deal.

Revenue generated divided by total investment cost, expressed as a percentage. For data platforms, ROI is calculated by comparing deal revenue from platform-sourced leads against subscription and marketing costs.

The number of years since a roof was last replaced or installed. Roof age is a primary input in predictive scoring models, properties with roofs older than 15-20 years are significantly more likely to need replacement, especially after storm events.

The process of locating current contact information (phone numbers, email addresses) for a property owner using identity and address data. Skip trace match rate and contact quality directly affect the reach of direct mail, SMS, and cold calling campaigns.

Text message campaigns sent to motivated seller lists. Higher open rates than email but requires compliant opt-in and messaging practices. Predictive-scored lists dramatically reduce waste by targeting only highest-probability sellers.

See List Stacking. The practice of layering multiple data filters or distress signals to identify the highest-probability motivated sellers.

A predictive metric that measures a property’s cumulative exposure to hail, wind, and severe weather events. Higher storm exposure combined with aging roofs creates the highest-probability replacement targets.

A property owner who has failed to pay property taxes. Tax delinquency is a top-tier distress signal because continued non-payment can result in a tax lien sale, creating strong motivation to sell. Stacking tax delinquency with equity data surfaces the best deal candidates.

Limited Market Exclusivity caps each roofing market at 2 to 5 contractors, scaled by market size. Members receive predictive replacement scoring and BuyBox-filtered lists for their territory.

A strict cap of 2 to 5 roofing contractors per market, scaled by market size. Once those seats are claimed, the broader roofing market never receives 8020Roof’s scored data for that territory. First-come, first-served.

A property that shows indicators of non-occupancy such as utility disconnection, mail forwarding, or lack of activity. Vacancy combined with other distress signals creates a strong motivated seller profile.

Conducting wholesale transactions in markets where the investor is not physically located. Requires high-quality remote data, skip tracing, and virtual deal management. Predictive scoring and territory exclusivity are critical for virtual operators who cannot drive for dollars.

A real estate investment strategy where an investor contracts to purchase a property and then assigns that contract to an end buyer for a fee, without ever taking title. Profit depends entirely on acquisition cost and buyer network depth. Data quality is the primary competitive advantage.