Download - Ad Fraud in Mobile Research by Augustine Fou
“is ad fraud higher or lower in mobile?”
April 2017
Augustine Fou, PhD.
acfou [@] mktsci.com
212. 203 .7239
“it’s more lucrative and less measurable… hmm,
what do you think?”
April 2017 / Page 2marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
NONE of the bot lists work
user-agents.org
bad guys’ bots
2% and “on the wane”Source: GroupM, Feb 2017
bot list-matching
4% Source: IAB Australia, Mar 2017
400 bot names in list
“not on any list”disguised as popular browsers – Internet Explorer; constantly
adapting to avoid detection
10,000bots observed
in the wild
April 2017 / Page 3marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
NONE of current js detection worksIn-Ad
(ad iframes)On-Site
(publishers’ sites)
• Used by advertisers to
measure ad impressions
• Limitations – tag is in foreign iframe, cannot look outside itself
ad tag / pixel(in-ad measurement)
javascript embed(on-site measurement)
In-Network(ad exchange)
• Used by publishers to
measure visitors to pages
• Limitations – most detailed and complete analysis of visitors
• Used by exchanges to
screen bid requests
• Limitations – relies on blacklists or probabilistic algorithms, least info
ad served
bot
human
fraud site
good site
April 2017 / Page 4marketing.scienceconsulting group, inc.
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Bad acting apps load more ad impressionsApp Name
Source: Forensiq
April 2017 / Page 5marketing.scienceconsulting group, inc.
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Fake mobile devices install appsDownload and Install
Launch and Interact
April 2017 / Page 6marketing.scienceconsulting group, inc.
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Suspicious apps (CTRs too high)
suspicious mobile apps
April 2017 / Page 7marketing.scienceconsulting group, inc.
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Magnitude of the ad fraud problem
websites
Source: Verisign, Q4 2016
329Mdomains
mobile apps
159 million“sites that carry ads”
11 milion“sites you’ve heard of”
WSJESPNNYTimes
EconomistReuters
Elle
10,000“apps you’ve heard of”
FacebookSpotifyPandora
ZyngaPokemonYouTube
96%“apps that carry ads”
3%
no adsno ads
7Mapps
Source: Statista, March 2017
April 2017 / Page 8marketing.scienceconsulting group, inc.
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Top 25 apps used by humans
April 2017 / Page 9marketing.scienceconsulting group, inc.
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Top 10 apps by time spent by humans
April 2017 / Page 10marketing.scienceconsulting group, inc.
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Top apps used by humans by category
April 2017 / Page 11marketing.scienceconsulting group, inc.
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Half of humans download 0 apps /mo
April 2017 / Page 12marketing.scienceconsulting group, inc.
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Apps have 1/3rd uniques, 20X time spent
April 2017 / Page 13marketing.scienceconsulting group, inc.
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Primary mobile revenue is from ads
In-App Advertising
App Store
April 2017 / Page 14marketing.scienceconsulting group, inc.
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Mobile ad revenue mostly from games
April 2017 / Page 15marketing.scienceconsulting group, inc.
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Top apps April 2017
“do you think bad guys will install your fraud detection SDK in their apps?”
“your CPI campaigns are not immune to fraud”
“it’s not lower in mobile, you just can’t measure it.”
April 2017 / Page 17marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
About the Author
April 2017 / Page 18marketing.scienceconsulting group, inc.
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Dr. Augustine Fou – Independent Ad Fraud Researcher
2013
2014
Follow me on LinkedIn (click) and on Twitter @acfou (click)
Further reading:http://www.slideshare.net/augustinefou/presentationshttps://www.linkedin.com/today/author/augustinefou
2016
2015
April 2017 / Page 19marketing.scienceconsulting group, inc.
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Harvard Business Review
Excerpt:
Hunting the Bots
Fou, a prodigy who earned a Ph.D. from MIT at 23, belongs to the generation that witnessed the rise of digital marketers, having crafted his trade at American Express, one of the most successful American consumer brands, and at Omnicom, one of the largest global advertising agencies. Eventually stepping away from corporate life, Fou started his own practice, focusing on digital marketing fraud investigation.
Fou’s experiment proved that fake traffic is unproductive traffic. The fake visitors inflated the traffic statistics but contributed nothing to conversions, which stayed steady even after the traffic plummeted (bottom chart). Fake traffic is generated by “bad-guy bots.” A bot is computer code that runs automated tasks.