Pixalate Releases Global September 2024 Most Common Mobile In-App Invalid Traffic (IVT) Types Across North America, EMEA, LATAM & APAC

London, Oct. 23, 2024 (GLOBE NEWSWIRE) —  Pixalate, the market-leading fraud protection, privacy, and compliance analytics platform for Connected TV (CTV) and Mobile Advertising, today released the September 2024 Most Common Mobile Invalid Traffic (IVT) Types Report. The report examines the most common types of mobile invalid traffic across North America, Europe, Middle-East, and Africa (EMEA), Asia-Pacific (APAC), and Latin America (LATAM) on the Google Play and Apple App Stores.

Pixalate’s data science team analyzed over 33 billion open programmatic advertising impressions across over 700k mapped mobile apps in September 2024. IVT types are rated most common by Pixalate according to the share of invalid traffic found within each mobile app store.

Most Common Mobile IVT Types Key Findings by Region:

North America

• Google Apps:
  • Display Impression Fraud: 21% share of voice of invalid traffic (IVT)
  • Device ID Stuffing Traffic: 19% share of voice of IVT
• Apple Apps:
  • Display Impression Fraud: 18% share of voice of IVT
  • Device ID Stuffing Traffic: 14% share of voice of IVT

LATAM

• Google Apps:
  • Display Impression Fraud: 33% share of voice of IVT
  • Masked IP: 20% share of voice of IVT
• Apple Apps:
  • Display Impression Fraud: 42% share of voice of IVT
  • Masked IP: 19% share of voice of IVT

EMEA

• Google Apps:
  • Display Impression Fraud: 31% share of voice of IVT
  • Device ID Stuffing Traffic: 14% share of voice of IVT
• Apple Apps:
  • Display Impression Fraud: 35% share of voice of IVT
  • Masked IP: 31% share of voice of IVT

APAC

• Google Apps:
  • App Spoofing: 19% share of voice of IVT
  • Display Impression Fraud: 18% share of voice of IVT
• Apple Apps:
  • Masked IP: 29% share of voice of IVT
  • Display Impression Fraud: 26% share of voice of IVT

The report includes a list of the Top 10 Google Play Store and Apple App Store apps with the highest IVT rate, as measured by Pixalate.

Download the full reports here.

For additional 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 Most Common Mobile Invalid Traffic (IVT) Types Reports (the ‘Reports’), reflect 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.” IVT is also sometimes referred to as “ad fraud.” 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.”

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