Pixalate Releases Q1 2024 Global Ad Fraud (IVT) Benchmarks for Desktop & Mobile Web Traffic: 11% IVT Rate on Desktop Web Traffic; Firefox (24%) & Apple’s Safari (20%) Browsers Have Highest IVT Rate

Research into global invalid traffic (IVT, including ad fraud) in open programmatic website advertising reveals Argentina and the USA has the highest mobile web IVT rate (15%), as measured by Pixalate


LONDON, May 22, 2024 (GLOBE NEWSWIRE) -- Pixalate, the global market-leading ad fraud protection, privacy, and compliance analytics platform, today released the Q1 2024 Global Desktop & Mobile Web Invalid Traffic Benchmark Report, analyzing the invalid traffic (IVT, including ad fraud) rates for open programmatic advertising on desktop and mobile websites in Q1 2024.

Pixalate's data science team analyzed 450k+ domains and subdomains and 19+ billion global open programmatic advertising impressions across desktop and mobile web in Q1 2024 to compile this research. The report benchmarks IVT and ad fraud across desktop and mobile web browsers by global region (Global, North America, EMEA, APAC, LATAM), country, browser (Google Chrome, Firefox, Apple Safari, Microsoft Edge, Opera), device type, and ads.txt. Pixalate’s findings concerning the mobile web traffic analysis cover smartphones as well as tablet devices.

Key Findings

IVT Benchmarks in Open Programmatic Advertising on Desktop Web

  • The global invalid traffic (IVT) rate for desktop web was 12%
    • Among the top five desktop web browsers, traffic on Mozilla Firefox had the highest IVT risk of 22%
  • The IVT rate for desktop web traffic in Canada and the USA was 13%, while Mexico and the UK saw a 12% IVT rate

IVT Benchmarks in Open Programmatic Advertising on Mobile Web

  • Global invalid traffic (IVT) rate for mobile web was 10%
  • Apple devices saw the highest IVT rate at 15%, followed by Samsung devices at 14%
  • Argentina and the USA has the highest mobile web IVT rate (15%), as measured by Pixalate

Download all of Pixalate’s Ad Fraud Benchmarks Reports

About Pixalate

Pixalate is a global platform for privacy compliance, ad fraud prevention, and data intelligence in the digital ad supply chain. Founded in 2012, Pixalate’s platform 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 MRC-accredited for the detection and filtration of Sophisticated Invalid Traffic (SIVT). www.pixalate.com 

Disclaimer

The content of this press release, and the Q1 2024 Desktop and Mobile Web Invalid Traffic Benchmarks Report (the "Report"), reflect Pixalate's opinions with respect to 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 programmatic advertising activity in the time period studied. Pixalate does not independently verify third-party information. 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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