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Pixalate Releases Q3 2024 Malformed & Fraudulent CTV Bundle IDs Risk Report: $174 Million in Estimated Connected TV (CTV) Open Programmatic Ad Spend Went to Malformed, Unidentified, and/or Fraudulent Bundle IDs

Pixalate’s data science team analyzed over 2.2 billion open programmatic advertising impressions across 12k+ CTV Bundle IDs mapped to 5k+ unique CTV apps in September 2024 on Amazon Fire TV, Roku, Samsung Smart TV, and Apple TV to compile the research in this series 

London, Oct. 31, 2024 (GLOBE NEWSWIRE) --  Pixalate, the global market-leading ad fraud protection, privacy, and compliance analytics platform, today released the Q3 2024 Connected TV (CTV) Malformed and Fraudulent Bundle IDs Risk Reports for Amazon Fire TV, Roku, Apple TV, and Samsung Smart TV CTV apps.

The reports include a detailed analysis of the global state of non-standard and malformed Bundle IDs in the open programmatic advertising supply chain as of Q3 2024. “Malformed” Bundle ID represents an app identifier used in the ad bid 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, and open the door to ad fraud.

Pixalate’s data science team analyzed over 2.2 billion open programmatic advertising impressions across over 12k CTV Bundle IDs mapped to over 5k unique CTV apps in September 2024 on Amazon Fire TV, Roku, Samsung Smart TV, and Apple TV to compile the research in this series. 
Key Findings:

  • Roku: 8% of Bundle IDs were malformed, unidentified, and/or fraudulent (~350 out of 4.5k)
    • 44% of Bundle IDs utilized across Roku traffic used App Store IDs, which is the recommended method for app identification according to the IAB Tech Lab
  • Amazon Fire TV: 62% of Bundle IDs were malformed, unidentified, and/or fraudulent (3.0k out of 4.9k)
    • 22% of Bundle IDs utilized across Amazon Fire TV traffic used App Store IDs, which is the recommended method for app identification according to the IAB Tech Lab 

  • Apple TV: 41% of Bundle IDs were malformed, unidentified, and/or fraudulent (~550 out of 1.4k)
    • 41% of Bundle IDs utilized across Apple TV traffic used App Store IDs, which is the recommended method for app identification according to the IAB Tech Lab 

  • Samsung Smart TV: 52% of Bundle IDs were malformed, unidentified, and/or fraudulent (~600 out of 1.2k)
    • 27% of Bundle IDs utilized across Samsung Smart TV traffic used 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 3202204027073 5232783
2 onefox tempbundleid18jcc5al86 g3201511006428 3794814
3 [replace_me] b00hcp9zdy eyeq eyeq
4 75419 tempbundleid18jcc5bei2 g3202305030895 8389520
5 84f1d9c6673633a8b6bdbead8759b7bf onefox onefox 3735519


Download the full report to receive a list of the top 50 malformed Bundle IDs - ranked by impression volume and by CTV platform - as measured by Pixalate in September 2024.
Download the Malformed and Fraudulent CTV Bundle IDs Reports

About Pixalate
Pixalate is a global market-leading ad fraud protection, privacy, and compliance analytics platform. Pixalate works 24/7 to guard your reputation and grow your media value by offering the only system of coordinated solutions across display, app, video, and CTV for the detection and elimination of ad fraud. Pixalate is an MRC-accredited service for the detection and filtration of sophisticated invalid traffic (SIVT) across desktop and mobile web, mobile in-app, and CTV advertising. www.pixalate.com
Disclaimer

The content of this press release, and the Malformed Bundle IDs Reports (the “Report”), 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.



Nina Talcott
ntalcott@pixalate.com

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