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Industries · Real Estate · Residential · Commercial · Mortgage · Property management

Real estate, from likely sellers on one street to a farm the whole brokerage runs on.

An agent wants the twelve households on her farm most likely to list this year. A national brokerage wants every agent's farm scored, mailed and measured on one person key. The property, household, mover and intent fields on 240M adults do both, and the ladder between them is short.

Book a free demo Start at rung one

Fair housing first: audiences are built on property, tenure and research intent, never on protected classes.

  • Home value, mortgage presence, years in home, dwelling type and a recent-mover flag on roughly every US household.
  • Daily intent on listing agents, home values, mortgage pre-approval, moving companies and new-construction searches.
  • Direct mail from the graph or your own farm list, in home within a week, matched back to listings and closings by address.
US Consumer Data · Likely sellers · 3 zip codes · 2,140 households
SegmentHomeownerYears in home: 7+Home value: $400K to $900KNo recent refinance
SignalsHome value estimateListing agents near meMoving companies
AlsoValidated phone · do-not-call checkedEmail validatedMailing address
PushedDirect Mail · 2,140Meta · 57% matchedGoHighLevel
Mail the listPush to MetaSend to the CRM
240M+US adults in the graph
120Mbusinesses, with the people in them
2Tintent signals read a day
400+attributes on a person

What the graph holds for real estate

The property and household fields an agent's farm is made of.

Four of the sixteen bundles, picked for this industry. See everything in the graph →

Household & propertyAbout 250 fields on where they liveOwner or renter, home value, mortgage presence, years in home, dwelling type, carrier route and the recent-mover flag: the farm, as fields.Open this table in the data dictionary → Intent & linkagesWhat they research, and how the keys joinDaily scores for home value estimates, listing agents, pre-approval, moving companies and new construction, joined to the household.Open this table in the data dictionary → FinanceModeled, not a credit reportModeled income and net worth bands to size a buyer audience or a luxury farm; never used to qualify a mortgage.Open this table in the data dictionary → PhonesChecked before you see themLine type, carrier, do-not-call status and a quality score on every number, so the follow-up call is to a number you may dial.Open this table in the data dictionary →

The ladder · simplest to largest

Five rungs, from one farm to the brokerage's warehouse.

Most of real estate lives happily on rungs one to three. Rungs four and five are for brokerages, iBuyers, builders and lenders with the volume to model and the systems to feed.

Rung 1 · Day one

An agent, a small team, a property manager, a mortgage broker

Pull the likely sellers on your farm, and see who is on your site.

Build one US Consumer Data segment: homeowners on your farm, years in home above a threshold, home value in your band, researching home values or listing agents this week. Download the records with validated phones, do-not-call flags and mailing addresses. Put the Website ID tag on the site and see which households read the listings and the home-value pages.

  1. Build the farm as a US Consumer Data segment; count it, sample it, download it.
  2. Install the Website ID tag; by tomorrow the households on the listings pages are in the app.
  3. Call the do-not-call-clear numbers, mail the rest.
US Consumer DataWebsite ID
Rung 2 · First month

A brokerage office, a team with a media budget, a builder selling a community

Advertise to the farm, keep clients out of it, and mail the top tier weekly.

Ad Audiences turns the farm into hashed audiences on Meta, Google and CTV, refreshed as intent moves. Smart Exclusion keeps past clients and current listings' owners out of the spend. Direct Mail runs the weekly drop from the graph or your own list and matches responders back by address.

  1. Build seller and buyer audiences in Ad Audiences; housing ads run under the platforms' special ad category rules, which the rep walks through.
  2. Load past clients into Smart Exclusion; they are excluded everywhere, refreshed as closings happen.
  3. Run the drop in Direct Mail; match back by address to listings and closings.
Ad AudiencesSmart ExclusionDirect Mail
Rung 3 · First quarter

A brokerage with a CRM, a lender with loan officers, a property management company

Enrich every contact, and watch the database for people about to move.

Enrich appends property, tenure, mover and finance fields to every contact in the CRM, written back through Integrations. Pulse watches the sphere, the past-client list and the lead database for the week someone starts researching home values, listing agents or mortgage rates, and routes the alert to the agent who owns them.

  1. Enrich the CRM with Enrich: home value, years in home, mortgage presence, mover flag.
  2. Put the sphere and past clients on Pulse; weekly, who is about to list, buy or refinance.
  3. Route alerts to agents through Integrations; score leads by equity and intent heat.
EnrichPulseB2B Data
Rung 4 · First year

An iBuyer, a national lender, a brokerage network, a proptech with an analyst

Model who lists, score every farm, and feed the competitors' shoppers.

Join enriched household fields and intent recency to past listings and closings, fit a listing-propensity model, and score every household in the market monthly by API. Seed Ad Audiences with the top decile; mail it with Direct Mail. Scope a Custom Intent Feeds feed on your brand, your listings, the competing brokerages and the lenders you lose to.

  1. Train on outcomes: years in home, equity band, mover signals and topic recency predict listings; distance and income band predict buyers.
  2. Score monthly by API or let an agent run it through the MCP server; refresh audiences, mail and suppression together.
  3. Build the Custom Intent Feeds feed to a written scope; it lands in the app, by API, in S3 or as a hashed audience.
Custom Intent FeedsEnrichAd AudiencesDirect Mail
Rung 5 · At scale

A national brokerage, a mortgage lender, a title company, an MLS-adjacent data business

License the graph into the warehouse and run every farm, channel and agent on one key.

Enterprise delivers the graph on a schedule to your warehouse, resolves every agent's contacts to one person, runs matching in the Clean Room, and streams audiences to The Trade Desk integration for CTV. Listings, mail, digital and closings are measured on the same household. White-label delivery puts the whole stack under your brand for agents or partners.

  1. Proof of concept on your transaction file: match rate and coverage, reported.
  2. Scheduled warehouse delivery; one household key across agents, offices and brands.
  3. Clean-room matching with lenders and title partners; CTV and programmatic through the DSP integrations.
EnterpriseCustom Intent FeedsAd AudiencesAgency DaaS

What real estate teams use it for

What agents, brokerages, lenders and builders run on the graph.

Buyer audiences for a community

Renters and owners in the value band within commuting distance, researching new construction and pre-approval.

Ad AudiencesDirect Mail

Sphere monitoring

Past clients and the database watched weekly for listing, buying and refinancing intent.

PulseEnrich

Who viewed the listings

Households on the site last night with their property fields, routed to the agent who owns the listing.

Website ID

Investor prospecting

Owners of multiple properties and non-owner-occupied homes, with validated phones and do-not-call flags.

US Consumer DataEnrich

Relocation and new-mover campaigns

Households that just moved into the market, in the mail by carrier route the week they arrive.

US Consumer DataDirect Mail

Mortgage and refinance

Homeowners with a mortgage on file, modeled equity and refinance research this week, suppressed against current borrowers.

Ad AudiencesSmart Exclusion

Commercial tenant and owner outreach

Businesses by size, industry and location with the owners and facilities leads inside, phones checked.

B2B DataChrome extension

Listing-propensity modeling

A model trained on past listings, scored monthly across the market by API.

EnrichAd Audiences

Competitor-brokerage feeds

Households researching the competing brokerage or lender by name, delivered daily.

Custom Intent Feeds

Franchise-wide identity resolution

Every office's contacts resolved to one household in your warehouse.

Enterprise

Agencies serving real estate

Every product under your brand, one sub-account per brokerage or builder.

Agency DaaS

Use it right

Fair housing, do-not-call, and nothing that qualifies a loan.

What applies when the buyer sells, finances or manages homes. Your counsel decides; this is how the data behaves.

  • Fair housing. Audiences are built on property, tenure, geography and research intent. Protected characteristics are never selection criteria, and housing ads on Meta and Google run under their special ad category rules, which the rep walks through.
  • Non-FCRA. Finance fields are modeled marketing data. They size an audience; they never decide a mortgage. Underwriting uses a credit report.
  • Calling and texting. Every phone carries a do-not-call flag and a line type. TCPA consent for texts and autodialed calls is yours to obtain; many brokerages call only the numbers that clear the flag.
  • Your clients' data. Past-client files for suppression or enrichment are hashed and matched; they stay yours.
  • Opt-outs honored. People who opt out through datamoon.com are removed from every product and from pulled records on the next refresh.

Questions

Questions an agent or a brokerage asks first.

How accurate are the property fields?

Household and property fields come from public records and deed data joined to the person. Home value, mortgage presence and years in home are the fields agents check first, and the sample shows them before you pull.

Can I call the people on the list?

The list carries a validated phone with line type and a do-not-call flag. Call the numbers that clear the flag and keep your own consent records for texts and autodialed calls.

Does this replace my farm list?

It scores it. Load your farm for enrichment and monitoring, or build the farm from the graph with the same fields. Either way the households researching a move this week float to the top.

Can I keep past clients out of my ads?

Yes. Load them into Smart Exclusion, hashed. Each one expands to every identifier the graph knows and is excluded on every platform and from every mail drop.

What does an enterprise engagement look like?

A proof of concept on your transaction file first, then scheduled delivery of the graph to your warehouse, identity resolution across offices, and clean-room matching with lenders or title partners, on an annual contract.

Other industries

The same graph, a different ladder.

Home ServicesFinancial ServicesInsuranceMarketing AgenciesAll industries

Book a free demo

Bring three zip codes. We count the likely sellers on the call.

Thirty minutes: your farm as a segment with the fields that matter, the match rate per platform, a sample of the records, and the next rung written down.

Book a free demoSee how it works

Thirty minutes, live on your own data. A person who knows the products and this industry runs the call. By continuing you accept the DataMoon terms.