Audience targeting

Audience targeting use cases let advertisers and publishers activate first-party and third-party data without exposing raw, user-level information to the other side of the collaboration. 

Explore use cases
A swirling ocean whirlpool with frothy white waves and deep blue-green water spiraling toward a dark center.

Explore audience targeting use cases

In a Decentriq data clean room, the matching and modeling logic runs inside a confidential computing environment, so audience targeting can happen without either party sharing the underlying data. This differs from targeting through a conventional platform, where one party typically has to hand over a customer list and accept a black-box match rate they cannot verify. 

The use cases on this page span the full range of privacy-safe audience targeting, from building a remarketing pool to onboarding an identity graph for matching. Each runs on the same underlying principle: computation happens without data exposure.

Lookalikes

Extend reach to similar audiences using matched signals, without exposing the seed audience itself.

explore lookalike audiences ->
Two mountain goats with curved horns standing on a snowy rocky ledge overlooking a fog-covered valley at sunset with snow-capped peaks in the background.

ID graph onboarding

Bring an identity graph into the clean room for matching and activation without sharing PII with the identity provider

explore ID graph onboarding ->
Cluster of vibrant orange-yellow mushrooms growing densely on a dark, textured piece of wood.

Affinity segments targeting

Match first-party signals to uncover top affinity segments to target

explore Affinity segments targeting ->
A close-up of a bee gathering nectar on an orange and yellow daisy-like flower surrounded by similar flowers.

Remarketing

Build retargeting pools from matched audiences without sharing full raw customer data with the other party

explore Remarketing ->
Large flock of birds flying and standing in shallow water at sunset with orange and purple sky and distant vegetation.

Exclusion targeting

Suppress existing customers from a campaign without handing over the full customer list

explore exclusion targeting ->
Aerial view of a small lake surrounded by dense forest with a tree-covered island in the center and several small docks or platforms on the water edges.

Why audience targeting matters

Most audience targeting workflows depend on one party trusting another with sensitive data, whether that is a customer list for exclusion, a seed audience for lookalike modeling, or an identity graph for onboarding. Confidential computing removes that dependency. Data stays encrypted throughout the process, and only the agreed output, such as an activation-ready audience segment, leaves the environment.

This matters most for organizations working with data clean room providers that also compete in the advertising ecosystem. When the platform running the computation has no commercial stake in the campaign outcome, the targeting logic itself becomes something the buyer can verify rather than take on faith.

Get in touch
A telescope on a tripod set up on rocky terrain with dry grass at dusk, pointing towards a clear starry sky with scattered clouds and distant mountain ridges.

Frequently asked questions

What is audience targeting in a data clean room?

It refers to building, refining, or suppressing advertising audiences using matched or combined data, without either party exposing the underlying raw data to the other.

How does exclusion targeting work without sharing customer data?

The matching happens inside the data collaboration environment. The publisher only receives the resulting suppression list applied to the campaign, not the advertiser's underlying full customer records.

Can lookalike audiences be built without exposing the seed audience?

Yes. The seed audience is used inside the secure environment to find matching signals elsewhere, and only the resulting lookalike segment is returned as output.

What is ID graph onboarding used for?

It brings an identity graph into the clean room so the advertiser can translate their CRM PII into activable identifiers across channels without disclosing any PII to the identity provider.

Talk to us about audience targeting

‍

get in touch