Future-proof cookieless
retargeting campaigns
Reach your customers without compromising their privacy
Innovative solutions
Privacy Sandbox solutions:
Protected Audience API with
PLTD and OBTD
Proven technology
Proprietary Deep
Learning algorithms
Personalized creatives
Best-in-class banners leveraging
the most advanced recommendation mechanisms
Personalized retargeting campaigns
that don’t need third-party cookies
…enables cookieless retargeting with no compromise on privacy. It takes an advertiser’s website data and places users in interest groups specifically defined for that advertiser. This allows people to see tailored ads, with no infringement on their privacy.
Protected Audience API aims to preserve current functionalities and the look and feel of classic retargeting, while introducing more robust privacy protection mechanisms. RTB House uses Deep Learning algorithms to create an advanced bidding logic to ensure that advertisers optimize their ad spend.
Protected Audience API
Product-level Turtledove (PLTD)
and Outcome-based Turtledove (OBTD)
…improve on Protected Audience API retargeting personalization.
PLTD stores data on the products a user interacts with within that user’s browser. This means we can display personalized product recommendations without knowing who that user is.
OBTD applies this same approach to gain user Signals. This piece of data can include variables specific to a given individual, such as the value of the products in a basket. This is used by the adtech’s bidding logic to better evaluate the bid price for an on-device, perfectly private ad auction.
PLTD
OBTD
RTB House Deep Learning understands patterns in behavior in real time
Raw first-party
data input
Patterns identified
by Deep Learning
Deep Learning defines interest group criteria
and adds users
It also defines relevant variables and products for bidding and ad personalization
Category
Product
Find
in-store
On a
wishlist
In a cart
Size
On sale
New model
Prices
of viewed
products
Sequence
of visited
products
Time
between
visits
Time spend
on each
subpage
List
of browsed
categories
Advanced self-teaching algorithms able to handle vast amounts of rich, even unstructured data, in real-time
Highly precise predictions of user behavior and estimations of buying potential with more efficient budget allocation
Currently delivers up to 50% more efficient personalized retargeting
Case study:
personalized creatives with the highest
privacy protection standards
The user visited an electronic e-shop and clicked on three products: smartphones, TVs, and laptops. What do they see in the cookieless future?
Competitor solutions
RTB House
The user will only see previously visited products and pre-defined, most popular products from a given category
The user will see visited products and personalized recommendations spanning a wide variety of categories
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