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AdTheorent Launches “Cost Per Incremental Visit” Ad-Pricing Model

AdTheorent Launches “Cost Per Incremental Visit” Ad-Pricing Model

Leveraging Industry Leading Machine Learning and Predictive Capabilities, Advertisers Pay Only for Ads That Yield Incremental Visits to Stores and other Advertiser Destinations

NEW YORK – AdTheorent, Inc., an advertising technology company using data, predictive analytics and machine learning to provide competitive advantages to marketers as measured by real-world business outcomes, announced the launch of a new Cost Per Incremental Visit (“CPIV”) ad-pricing model. The goal of AdTheorent’s CPIV model is to optimize and drive incremental visits to physical locations such as retail stores, dealerships, theme parks, movie theaters and other attractions – i.e., visits that would not have occurred absent a given ad campaign. Under this model AdTheorent’s advertisers derive measurable value from each campaign because they pay only for ads that yield an incremental physical visit. AdTheorent’s CPIV ad pricing model is third-party measured with Placed Attribution, the leader in ad to in-store attribution.

New CPIV ad model launched by @adtheorent enables advertisers to pay only for ads that yield incremental visits

Unlike a handful of other recently launched solutions that offer advertisers the option of a “Cost Per Visit” (CPV) pricing model, AdTheorent’s CPIV model is designed to identify location visits that are truly incremental and representative of “lift” caused by exposure to the ad campaign — not counting visits that likely would have occurred regardless of the ad campaign. Just like “mis-clicks” that can obscure the real value of ad “clicks” to an advertiser, CPV pricing uncorrelated to in-store or location “lift” (i.e., visits that were incremental because of the ad campaign) may over-state an advertiser’s campaign ROI.

“AdTheorent’s machine learning platform combines billions of data attributes into custom models used to identify and engage optimal audiences based on a given advertiser’s desired goals,” said Josh Walsh, AdTheorent’s President, Media. “Our high-performing predictive models afford us the luxury of developing a pricing model that guarantees ROI for AdTheorent advertisers – whether that be a lift in in-store, movie theater or dealership visits or some other real-world business outcome.”

Consistently outperforming Placed lift benchmarks by 2.6X, AdTheorent uses its highly advanced predictive advertising platform to create custom models designed to identify and engage users most likely to be driven to location visitation engagement as the result of engagement with a given ad. AdTheorent’s custom models are optimized to generate visitation “lift” (new visits), which is different than serving ads to consumers who likely would have appeared in the store or location regardless of the ad.

This is an evergreen pricing model, but is especially timely for retailers now due to the impending holiday shopping season. With 81% of consumers planning on doing half or more of their holiday shopping in stores1 and with estimated sales rising 3.5-4.4% this year2, retailers are looking to capture shopper attention and drive store visits. In a complicated and fragmented advertising ecosystem in which it is easy to make bold claims but much harder to back them up with measurable business achievements, AdTheorent’s CPIV ad-pricing model puts advertiser value first.

“Campaign measurement has moved far beyond the early days of optimizing to clicks, and at this stage, marketers have reached a point where they demand online to offline attribution to demonstrate campaign success,” said David Shim, CEO of Placed. “We have partnered with AdTheorent successfully for years to measure their high-performing campaigns with Placed Attribution, and we look forward to continuing this across an innovative set of advertiser-focused solutions.”

About AdTheorent®

AdTheorent is a machine learning-powered predictive advertising company, utilizing machine learning and predictive analytics to connect advertisers with their optimal audiences, at scale. AdTheorent’s Data Science team leverages an award winning machine learning platform connected to a Cross-Environment Map consisting of 600MM devices across 90MM US households. AdTheorent’s platform combines millions of data attributes into custom models to drive campaign results, far outperforming industry standards, to predict and identify users most likely to engage with an advertiser’s message. AdTheorent’s Studio A\T creative organization helps advertisers develop the most effective creative assets, content and technology solutions to engage with audiences. AdTheorent’s award winning attribution division – MRC-accredited Barometric – provides attribution solutions based on real-world outcomes. For more information, please visit adtheorent.com.

1. AlixPartners US Retail Holiday-Outlook Survey, https://www.alixpartners.com/insights-impact/despite-closures-nearly-three-quarters-of-consumers-plan-to-do-most-of-their-holiday-shopping-in-stores-according-to-alixpartners-survey/#sm.00012mbiwq22oejux5r2czrmdkba5

2. Deloitte, 2017 Holiday Sales Forecast: https://www2.deloitte.com/us/en/pages/about-deloitte/articles/press-releases/deloitte-retail-holiday-forecast.html.