Pixalate’s Q4 2024 Report Finds 31% of CTV Bundle IDs Were Malformed, Unidentified, and/or Fraudulent Across Roku, Amazon Fire TV, Apple TV, & Samsung TV

London, Jan. 24, 2025 (GLOBE NEWSWIRE) — Pixalate, the global market-leading ad fraud protection, privacy, and compliance analytics platform, today released the Q4 2024 Connected TV (CTV) Malformed and Fraudulent Bundle IDs Risk Reports for the Amazon Fire TV, Roku, Apple TV, and Samsung Smart TV CTV apps.

The series of reports provide a detailed analysis of the global status of non-standard and malformed Bundle IDs in the open programmatic advertising supply chain as of Q4 2024. A “malformed” Bundle ID refers to an app identifier used in the ad bid that is either uncorrelated or unmapped to any known app, according to Pixalate’s Bundle ID mapping technology. These “malformed” Bundle IDs disrupt ad targeting and campaign measurement while paving the way for ad fraud.

Key Findings:

Roku: 3% of Bundle IDs were malformed, unidentified, and/or fraudulent (~150 out of 4.7k)

• 52% of Bundle IDs across Roku traffic used actual App Store IDs, which is the recommended method for app identification according to the IAB Tech Lab

Amazon Fire TV: 48% of Bundle IDs were malformed, unidentified, and/or fraudulent (2k out of 4.2k)

• 36% of Bundle IDs across Amazon Fire TV traffic used actual App Store IDs, which is the recommended method for app identification according to the IAB Tech Lab

Apple TV: 52% of Bundle IDs were malformed, unidentified, and/or fraudulent (~850 out of 1.6k)

• 36% of Bundle IDs across Apple TV traffic used actual App Store IDs, which is the recommended method for app identification according to the IAB Tech Lab

Samsung Smart TV: 46% of Bundle IDs were malformed, unidentified, and/or fraudulent (~500 out of 1.1k)

• 31% of Bundle IDs across Samsung Smart TV traffic used actual App Store IDs, which is the recommended method for app identification according to the IAB Tech Lab

Top Malformed, Unidentified and/or Fraudulent Bundle IDs (by impression volume) as determined by Pixalate

Malformed and/or Fraudulent Bundle ID
Rank (by Impression SOV)	Roku	Amazon Fire TV	Samsung Smart TV	Apple TV
1	eyeq	eyeq	eyeq	eyeq
2	onefox	onefox	com.cmgdigital.whiohybrid	com.spectrumreach.tv
3	scripps	scripps	scripps	onefox
4	7405534	soap2dayhq.to	onefox	20006184
5	com.spectrumreach.tv	com.spectrumreach.tv	com.spectrumreach.tv	replace_me

For this report, Pixalate’s data science and analyst team analyzed over 2 billion open programmatic advertising transactions across more than 20,000 CTV Bundle IDs linked to over 6,000 unique CTV apps on Roku, Amazon Fire TV, Samsung Smart TV, and Apple TV traffic in December 2024.

Download the complete reports:

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 Malformed Bundle IDs Reports (the “Reports”), reflect Pixalate’s opinions with respect to factors that Pixalate believes can be useful to the digital media industry. 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 programmatic advertising activity across CTV in the time period studied. 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. Also per the 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.”.

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