Platform / Filter

Build the audience around the campaign.

Filter real estate and mortgage behavioral audiences by intent category, geography, recency, and contact requirements.

The short answer

The audience builder turns a broad signal category into a campaign-ready segment. Teams can define the behavior, market, recency window, and profile requirements, then preview the available audience before creating an export.

What audience building changes

A national category is too broad for most real estate and mortgage campaigns. Operators need a repeatable way to align the audience with a territory, offer, channel, and available follow-up capacity.

The public walkthrough shows category and subcategory selection, state/city/ZIP geography, recency windows up to 30 days, profile-completeness filters, and audience-count previews.

  • Available geographies and coverage thresholds
  • Preview counts versus exported records
  • Duplicate and repeat-signal handling
  • Saved-search, seat, and export governance

From signal to a usable audience

A defined segment becomes a documented campaign input. Saving the criteria alongside the export makes testing, suppression, routing, and later performance comparison easier.

  1. DefineChoose the behavioral category, geography, recency window, and contact requirements that match the campaign.
  2. PreviewReview the available audience count before creating an export or downstream activation.
  3. ActivateMove the resulting audience into an approved CSV, advertising, CRM, or webhook workflow.

What a serious buyer should verify

Intent-data procurement should be evidence-led. Ask vendors to define every freshness claim, show the delivered fields, document suppression and permitted-use controls, and explain what the signal does—and does not—prove.

  • Available geographies and coverage thresholds
  • Preview counts versus exported records
  • Duplicate and repeat-signal handling
  • Saved-search, seat, and export governance

Decision support

Frequently asked questions

Can an audience be filtered by geography?

The public product walkthrough describes state, city, and ZIP filtering. Teams should confirm coverage and minimum counts for their exact markets.

Why does recency matter?

Research context changes quickly. Recency allows a campaign team to test how results differ as a signal ages rather than treating a 48-hour and 30-day-old record as identical.

Should every filter be as narrow as possible?

No. Excessive filtering can create small or unstable cohorts. Start with the campaign hypothesis, required fields, and available follow-up capacity.

From research to audience

See the signal before you scale the spend.