Integral Ad Science, a leading global media measurement and optimization platform, has launched a new AI-powered Made for Advertising (MFA) site detection and avoidance offering. The MFA site technology developed by the company intends to improve transparency into advertiser campaign quality, identify where expenditure is being spent, and inform optimizations to reduce waste on MFA sites.
MFA sites are web pages with low-quality content (e.g., spam sites or ad farms) that are designed to perform well against traditional verification criteria like as viewability. However, advertising on these sites does not result in important outcomes like conversions or brand lift.
IAS’s new product uses AI to detect MFA sites at scale, allowing advertisers to regain control of their media quality and reduce waste. IAS produced a detailed campaign analysis demonstrating superior MFA site identification for some of the world’s major advertisers and agencies during Alpha testing.
The Association of National Advertisers (ANA) latest definition of MFA sites is supported by IAS’s product, which incorporates factors such as ad-to-content ratio, ad refresh rate, and the source of visitors flowing to the site to categorize a site as MFA. According to the ANA’s Programmatic Media Supply Chain Transparency Study, MFA sites served 21% of the advertisement impressions measured.
“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,” stated Yannis Dosios, Chief Commercial Officer, Integral Ad Science. “MFA sites pose a significant challenge to the industry.” We’ve built a scalable method for identifying low-quality inventory sources and improving overall campaign performance by applying AI.”
Advertisers and their agencies require assurance that the industry is coming to terms on the specific websites that comprise the MFA category. IAS has developed the industry’s first pressure tested solution for detecting and blocking MFA at scale by training its model using Jounce Media’s widely adopted list of MFA domains and combining signals from Sincera.
“Advertisers should recognize that MFA websites can account for a sizable portion of their overall campaign and should independently determine if MFA sites meet their brand suitability standards for content and user experience.” “We applaud IAS for acting in response to our programmatic transparency report findings and for supporting our definition of MFA,” stated Bill Duggan, ANA group executive vice president. “We discovered that awareness of MFA sites is low among the ANA community of media professionals, which is surprising.” We anticipate future advances from IAS in the areas of MFA site recognition and ad spend optimization to better educate and inform purchasers.”