Household Consumer Marketing Profiles

Stop Mailing Blind. Start Targeting with Precision.

The Household Consumer Marketing Profiles dataset delivers household-level demographics, hundreds of behavioral flags, propensity scores, and match confidence metadata so your direct mail and omnichannel campaigns reach the right door, not just the right zip code. For the first time, you can build, score, and activate a verified audience segment without a single data append request to an outside vendor.

Isometric white geographic platform with blue household markers, routes, audience overlays, floating data cards, and spatial partitions representing precise household marketing targeting.
At a Glance

The Data Behind the Decision

Hundreds
Interest and purchase flags per record
Census block to DMA
Geographic precision range
Multi-point
Contact signals per household
Buy by Geography

Stop buying the whole country. Buy just your markets.

Most data vendors sell you a national license to millions of records you will never contact. BigGeo works differently.You tell us where you sell, and we cut you exactly that geographic slice of the dataset. A single city.

A cluster of ZIP codes. A metro area. A county. Whatever matches your territory. The result is a lean, CRM-ready file containing only the companies in the markets you actually work, delivered at a fraction of the cost of a full national license.

Book a Meeting

See the Data Against Your Use Case

The Problem

Why Most Campaign Lists Underdeliver

Direct marketers know their offer is good. The list is where campaigns die. Fragmented data sources, stale contact records, and audience segments built on guesswork produce low match rates and lower ROI — and no one in the room can explain exactly why the last campaign missed. You are not running a bad campaign. You are running it on bad data.

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Segment Building Takes Too Long
Every audience segment requires pulling from multiple sources, reconciling fields, and waiting on data engineering. By the time the list is ready, the campaign window has narrowed and the segment logic has already been compromised.
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No Confidence in Match Quality
When you cannot see the confidence score behind a record linkage, you are mailing to assumptions. Low match quality inflates suppression failures and drives up cost per acquisition without any signal telling you where the leak is.
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Behavioral Signals Arrive Too Thin
Most lists give you age and income and call it enrichment. Without interest flags, purchase behavior, and lifestyle scores, your personalization is a demographic guess dressed up as targeting — and your audience can tell.
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Geographic Targeting Stops at the Zip Code
Zip-code-level targeting wastes budget on households outside your true trade area. Without census block and coordinate-level precision, you cannot suppress, refine, or weight your list to match actual market opportunity.
What Is In The Dataset

Every Signal You Need to Win the Mailbox

Verified Household Contact Signals

Multiple phone lines, email addresses, and do-not-call flags per record mean you can suppress, prioritize, and route each household to the right channel before a single piece goes to print or deployment.

Hundreds of Behavioral and Interest Flags

Interest flags covering hobbies, travel, purchase patterns, and lifestyle give you the signal depth to build personalization that reflects what a household actually does, not just how old they are or what they earn.

Propensity Scores and Confidence Metadata

Built-in match confidence scores let you tier your list by reliability, prioritize high-confidence records for premium spend, and flag low-confidence records for suppression or verification before campaign launch.

Sub-Zip Geographic and Census Identifiers

Coordinates, census block, and DMA identifiers let you define true trade areas, weight spend by geographic market potential, and join household records directly to property and parcel data for deeper context.

Let's talk
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The world's spatial data is more accessible than you think. Let's show you how close you already are.
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You already have the questions. We have the data. Let's see what happens when they meet.
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The where in your business is more important than you think. Let's find it together.
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Most spatial data conversations start with a problem nobody thought was solvable. What is yours?
BigGeo AI

Ask Every Audience Question in Plain Language, Get Governed Answers Instantly

BigGeo AI is live in ChatGPT today and shipping in Claude, giving your team direct access to governed, real-data answers grounded in the Household Consumer Marketing Profiles dataset, no GIS analyst required and no data pull ticket to file. Ask which census blocks in your target DMA contain the highest concentration of households matching your propensity threshold, then layer in income band and interest flags, all in one plain-language conversation. What used to take a data scientist two days now takes two minutes.

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Which zip codes in the Atlanta DMA have the highest density of households with a home value above $400k and a travel interest flag?
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Show me census blocks in my target trade area where median estimated income exceeds $90k and credit score band is prime or above.
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Which households in my suppression list have a do-not-call flag active and what channel should I route them to instead?
FAQ

Frequently asked questions

How fresh is this data and how often is it updated?
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We already have a CRM. Why do we need this instead of appending to what we have?
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How do I know the household records are accurate enough to trust for a paid campaign?
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How does this data get into our systems and how long does it take?
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What is the fastest way to see if this data works for our specific audience model?
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