Distil Networks Releases New Data on The State of Digital Advertising Fraud
Findings show large majority of publishers (75 percent) and advertisers (59 percent) are either unable, or unsure, about how to decipher human versus non-human traffic
October 22, 2015
PRESS RELEASE
San Francisco, CA – Oct. 22, 2015 – Distil Networks, the global leader in bot detection and mitigation, today announced the results of a survey of digital publishers’ and advertisers’ concerns regarding non-human traffic and digital ad fraud. The survey, conducted as part of a joint webinar with the Interactive Advertising Bureau (IAB), asked 138 publishers and advertisers responsible for either buying or supplying digital advertising to estimate how much bot traffic affects their web properties and performance of online campaigns.
According to IAB, digital advertising spend will reach an estimated $56 billion by the end of 2015. At the same time, IAB estimates that one third of spend is being siphoned out of the advertising ecosystem due to fraudulent activity. The digital advertising marketplace – both supply-side and demand-side – is under sustained attack from increasingly sophisticated automated programs known as bots designed to divert, steal, and defraud billions of dollars every year. According to the 2015 Bad Bot Landscape Report, 22.7 percent of all web traffic in 2014 was bad bots, and digital publishers led all other industries in bad bot traffic (32 percent).
“As digital ad fraud continues to track closely behind digital advertising spend, it’s staggering to see the lack of meaningful measurement by both advertisers and publishers for real human traffic,” said Distil Networks co-Founder and CEO, Rami Essaid. “Bots are a relatively cheap and easy way to divert funds from digital advertising spend, and so far have had an easy run at it. This needs to change.”
“As more and more digital ads are placed entirely programmatically the opportunity for fraud increases as the bad guys fully automate their fraud operations,” said Mike Zaneis, President of the Trustworthy Accountability Group (TAG). “TAG supports Distil Networks’ efforts to help the industry measure and mitigate non-human traffic.”
Key Findings:
· A large amount of advertisers (37 percent) are willing to pay at least an 11 percent premium for certified human traffic.
· However, a large majority of publishers (75 percent) and advertisers (59 percent) are either unable, or unsure, about how to decipher human versus non-human traffic.
· Many digital advertisers (40 percent) and publishers (48 percent) are unable to estimate the negative effects that bot traffic has on their web properties or the performance of online campaigns, yet almost no one denies the issue.
· 37 percent of advertisers think non-human traffic has a significant negative effect on their campaigns compared to only 14 percent of the publishers.
· Click and impression fraud are the top concerns for both publishers (86 percent) and advertisers (100 percent) when it came to web traffic issues.
· Skewed analytics (50 percent) and lead fraud and fake registrations (32 percent) are also important non-human traffic problems to both publishers and advertisers.
· To download a copy of the survey and report, visit: http://info.distilnetworks.com/digital-ad-fraud-white-paper
About Distil Networks
Distil Networks, the global leader in bot detection and mitigation, is the first easy and accurate way to identify and police malicious website traffic, blocking 99.9% of bad bots without impacting legitimate users. Distil protects against web scraping, brute force attacks, competitive data mining, account hijacking, unauthorized vulnerability scans, spam, man-in-the-middle attacks and click fraud. Slash the high tax that bots place on your internal teams and web infrastructure by outsourcing the problem to the team with a maniacal focus on blocking malicious bots. For more information on Distil Networks, visit us at www.distilnetworks.com or follow @DISTIL on Twitter.
You May Also Like
Cybersecurity Day: How to Automate Security Analytics with AI and ML
Dec 17, 2024The Dirt on ROT Data
Dec 18, 2024