Latest innovation leverages AI to uncover low-quality sites at scale and minimize wasted ad spend
MFA sites are web pages featuring low quality content (e.g. spam sites, or ad farms) created solely to serve ads, and are optimized to perform well against traditional verification metrics, such as viewability. However, advertising spend on these sites does not drive meaningful outcomes, such as conversions or brand lift.
IAS's new product leverages AI to uncover MFA sites at scale, allowing advertisers to take back control of their media quality and cut down on wasted spend. During Alpha testing, IAS delivered comprehensive campaign analysis demonstrating superior MFA site identification for some of the world's largest advertisers and agencies.
IAS's product supports the
"Our MFA product was built to deliver unprecedented transparency to advertisers and provide them with the ability to both detect and avoid MFA sites in order to redirect their ad spend to publishers that drive a return," said
Advertisers and their agencies need confidence that the industry is converging on agreement about the specific websites that compose the MFA category. By training its model against Jounce Media's widely adopted list of MFA domains and incorporating signals from Sincera, IAS has developed the industry's first pressure tested solution for detecting and blocking MFA at scale.
"Advertisers should recognize that MFA websites can account for a significant portion of their overall campaign and should determine, independently, if MFA sites fit with their brand suitability standards for content and user experience. We applaud IAS for taking action after we released the findings from our programmatic transparency report and for supporting our definition of MFA," said
The IAS MFA product completed alpha testing in early
For more information on how IAS is identifying and combating MFA sites, visit: How Marketers Can Detect and Avoid Made for Advertising Sites
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