Pixalate’s research into open programmatic advertising finds that over 4,100 Apple TV, Roku, Samsung Smart TV, and Amazon Fire TV apps were subjected to “App Spoofing” as a form of invalid traffic (IVT) in September 2024, as measured by Pixalate; On Samsung Smart TV apps, “Proxy IVT” accounted for 52% of all IVT in September 2024, as measured by Pixalate
LONDON, October 16, 2024 -- Pixalate, the market-leading fraud protection, privacy, and compliance analytics platform for Connected TV (CTV) and Mobile Advertising, today released the Top 10 Connected TV (CTV) Ad Fraud Types in September 2024 for Amazon Fire TV, Roku, Apple TV, and Samsung Smart TV.
The reports cover invalid traffic (IVT) and ad fraud measured across CTV app stores, including the number of distinct apps impacted and the share of voice of each IVT type. The reports also reveal the top 10 apps in each respective app store with the highest IVT rates in September 2024, according to Pixalate’s data.
To compile the research in this series, Pixalate’s data science team analyzed over 1.9 million open programmatic advertising impressions and over 5,500 mapped CTV apps across Roku, Amazon Fire TV, Apple TV, and Samsung TV in September 2024. IVT types are rated ‘most common’ according to the share of invalid traffic within each CTV app store, as per Pixalate’s methodology.
For the purposes of this report, “Bundle ID (App) Spoofing'' indicates impressions in which the app identifier reported to the exchange does not match the characteristics of the app detected by Pixalate. “Proxy” is defined as impressions from an intermediary proxy device that exists to manipulate traffic counts, pass non-human or invalid traffic, or fails to comply with the protocol. For more information on IVT types, visit Pixalate’s IVT knowledge base.
Pixalate is MRC-accredited for the detection and filtration of Sophisticated Invalid Traffic (SIVT) across desktop and mobile web, mobile in-app, and Connected TV (CTV). All of Pixalate’s MRC accredited measurement areas can be found here.
For more information on IVT types, visit Pixalate’s IVT knowledge base.
About Pixalate
Pixalate is a global platform specializing in privacy compliance, ad fraud prevention, and digital ad supply chain data intelligence. Founded in 2012, Pixalate is trusted by regulators, data researchers, advertisers, publishers, ad tech platforms, and financial analysts across the Connected TV (CTV), mobile app, and website ecosystems. Pixalate is accredited by the MRC for the detection and filtration of Sophisticated Invalid Traffic (SIVT). pixalate.com
Disclaimer
The content of this press release, and the CTV’s Most Common Ad Fraud and IVT Types Report, reflects Pixalate’s opinions with respect to the factors that Pixalate believes can be useful to the digital media industry. Any data shared is grounded in Pixalate’s proprietary technology and analytics, which Pixalate is continuously evaluating and updating. Any references to outside sources should not be construed as endorsements. Pixalate’s opinions are just that, opinions, which means that they are neither facts nor guarantees. Pixalate is sharing this data not to impugn the standing or reputation of any entity, person or app, but, instead, to report findings and trends pertaining to the time period studied. Per the Media Rating Council (MRC), “‘Invalid Traffic’ is defined generally as traffic that does not meet certain ad serving quality or completeness criteria, or otherwise does not represent legitimate ad traffic that should be included in measurement counts. Among the reasons why ad traffic may be deemed invalid is it is a result of non-human traffic (spiders, bots, etc.), or activity designed to produce fraudulent traffic.” Where the traffic characteristics are suggestive of deliberate intent to mislead, such IVT is often referred to as “ad fraud.” Also per the MRC, “'Fraud' is not intended to represent fraud as defined in various laws, statutes and ordinances or as conventionally used in U.S. Court or other legal proceedings, but rather a custom definition strictly for advertising measurement purposes.”
