Upcoming Changes



branding campaigns

tailored to your needs

The best cookieless targeting methods available from a single provider

Group targeting

Context targeting

Individual targeting

Privacy Sandbox-based:


Our proprietary contextual targeting: ContextAI

Directly reach

publisher audiences

Targeting solutions

for the future without cookies


Identity Providers

(Origin Trials Pending)


…reaches users where they browse by using predefined, recommended taxonomies, and custom categories on demand. It works at scale to reach them in the right environment with ads that they will actually want to see. The technology takes contextual marketing to a new level by using Deep Learning to define when ads should be shown, what format they should use, and which content to display to minimize ad fatigue.







for labels

Targeting example:

specific contextual signals up to a keyword or phrase level, e.g. sport cars. better target users. Publishers utilize onsite behavior to create user groups and build direct relationships with readers.

Publisher 1

Publisher 2

Access publisher audiences

RTB House’s network of publishers, coupled with leading-edge Deep Learning technology, enables advertisers to reach their audiences.

Mustang 1969 fan

Camaro 1979 fan

Belgium football team fan

Austrian football team fan

User 1

User 2

Targeting example:

people interested in cars, but currently browsing unrelated content within publisher sites.

… take user-identifiable data, such as emails, IP addresses, and phone numbers, and attach it to a universal identifier. This can be used to leverage a wide variety of user information, such as behavioral or demographic data, and functions cross-site and cross-device. The solution is only used when the user provides consent, and is compliant with all relevant privacy laws.

Identity providers

Targeting example:

people with emails associated with a purchase of a ticket to a car expo within the last 180 days and have seen the ad on their CTV device.

User Identifier

…in which our Deep Learning algorithms improve on Chrome’s Topics API, enabling privacy-friendly, interest-based advertising. It delivers all the functionalities of the API, but is enriched with proprietary data.










Targeting example:

people interested in cars currently browsing an electronics review for smartwatches.

(Origin Trials Pending)

…creates lookalike audiences by surveying users. The resulting zero-party data enables us to create groups of users tailored to your campaign goals, a step beyond the typical taxonomies used in advertising.


Targeting example:

people who are interested in buying an electric car.

Featured by

Combining multiple cookieless solutions to maximize the number of insights

Tools can be combined

to target specific user groups, e.g., runners interested in wearable electronics, or travelers interested in winter sports

AI helps to improve scale, while still ensuring ad relevance and brand visibility

Future-proof tools in line with emerging privacy regulations and people's expectations

Build your future with us

Fill out this form and our team will help you to future-proof your campaigns

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can prepare for the cookieless future?

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