AdTheorent Launches Industry's First Privacy-Forward Solution for Audiences
AdTheorent Predictive Audience Builder Delivers Customizable Machine Learning Tools to Enhance Audience Reach, Composition and Quality
AdTheorent Predictive Audience Builder leverages customizable and primary-sourced seed data sets to mimic the audience profile of an advertiser's desired target. In a major departure from industry-standard audience segments, that seed data set is not used for direct targeting. Instead
AdTheorent Predictive Audience Builder's use of primary-sourced, highly-customized audience profile parameters is boundlessly flexible and customizable to each advertiser's marketing strategy.
- Examples include completely customizable vertical-based audiences such as: auto intender in-market for a specific make or model; frequent fast-food diner with high probability of switching to a new chain, or frequent family meal or online orderer; big box and family shopper with high household income; or high spender on luxury travel in market for or researching a trip.
How It Works:
- Primary-Sourced Data: AdTheorent Predictive Audience Builder leverages primary-sourced datasets (provided by either
AdTheorentor an agency or brand) to identify audience quality statistics relevant to the specific brand campaign. Examples of data types include:
- Consumer Data: Thousands of consumer data attributes such as demographics, purchasing habits, lifestyles, interests, and attitudes.
- Location Data: Precise location data sourced directly from in-app SDKs and server-to-server integrations with publishers and mobile application developers.
- Verticalized Data: Vertical-specific data across automotive, B2B, CPG, dining, finance, retail, travel and more.
- Machine Learning Expansion:
AdTheorentidentifies commonalities in the data using machine learning and identifies other important attributes to grow the addressable ML-informed audience in real time.
- ML-Based Audience Optimization: As per
AdTheorent'sstandard Predictive Targeting processes, AdTheorent Predictive Audience models define the data parameters within which AdTheorentads are served, with the primary goal being optimizing ad delivery towards data attributes and combinations which cause KPI conversion lift.
- Campaign Performance: Using
AdTheorent'sPredictive Targeting, the campaign is optimized toward the advertiser-specified KPI to drive performance. AdTheorentdelivers an ad to an impression opportunity only when AdTheorent'spredictive models indicate a sufficiently high probability that a given ad opportunity will do each of the following: (1) be served within the customized Predictive Audience and (2) lead to completion of an advertiser-specified campaign action. Each AdTheorent Predictive Audience model evaluates millions of impressions per second to drive performance, considering 1000+ data variables in its models. Models self-optimize throughout each campaign, allowing AdTheorentto drive industry-leading performance for advertisers.
"AdTheorent Predictive Audience Builder represents a more modern way for brands to reach relevant individuals without reliance on targetable user IDs, delivering data-driven audience quality and further driving KPI optimization," said
For more information about
AdTheorent (Nasdaq: ADTH) uses advanced machine learning technology and privacy-forward solutions to deliver impactful advertising campaigns for marketers.
View original content to download multimedia:https://www.prnewswire.com/news-releases/adtheorent-launches-industrys-first-privacy-forward-solution-for-audiences-301724667.html
Melanie Berger, AdTheorent, firstname.lastname@example.org, 850-567-0082