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State of Digital Ad Fraud2017 Update
March 2017
Augustine Fou, PhD.
212. 203 .7239
Ad Fraud is VERYLucrative and Scalable
March 2017 / Page 2marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
How profitable is ad fraud? EXTREMELY
Source: https://hbr.org/2015/10/why-fraudulent-ad-networks-continue-to-thrive
“the profit margin is 99% …
[especially with pay-for-use cloud services ]…”
Source: Digital Citizens Alliance Study, Feb 2014
“highly lucrative, and profitable… with
margins from 80% to as high as 94%…”
March 2017 / Page 3marketing.scienceconsulting group, inc.
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How scalable are fraud operations? MASSIVELY
Cash out sites are massively scalable
131 ads on pageX
100 iframes=
13,100 ads /page
One visit redirected dozens of times
Known blackhat technique to hide real referrer and replace with faked referrer.
Example how-to:http://www.blackhatworld.com/blackhat-seo/cloaking-content-generators/36830-cloaking-redirect-referer.html
Thousands of requests per pageSingle mobile app calling 10k impressions
Source: Forensiq
March 2017 / Page 4marketing.scienceconsulting group, inc.
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Example – AppNexus cleaned up 92% of impressions
Increased CPM prices
by 800%Decreased impression
volume by 92%
Source: http://adexchanger.com/ad-exchange-news/6-months-after-fraud-cleanup-appnexus-shares-effect-on-its-exchange/
260 billion
20 billion
> $1.60
< 20 cents
March 2017 / Page 5marketing.scienceconsulting group, inc.
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Ad fraud is now the largest form of crime
$20 billion
CounterfeitGoods U.S.
$18 billion
Somalipirates
$70B 2016E Digital Ad Spending
Bank robberies
$38 million
$31 billionU.S. alone
$1 billion
ATM Malware
Payment Card Fraud 2015
$22 billion
Source: NilsonReport Dec 2016
Source: ICC, U.S. DHS, et. al
Source: World Bank Study 2013
Source: Kaspersky 2015
$7 in $100$3 in $100
“this is a PER YEAR number”
Digital Ad Fraud
Source: IAB H1 2016
$44 in $100
March 2017 / Page 6marketing.scienceconsulting group, inc.
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Methbot eats $1 in $6 of $10B video ad spend
Source: Dec 2016 WhiteOps Discloses Methbot Research
“the largest ad fraud discovered to date, a single botnet, Methbot, steals $3 - $5 million per day, $2 billion annualized.”
1. Targets video ad inventory$13 average CPM, 10X higher than display ads
2. Disguised as good publishersPretending to be good publishers to cover tracks
3. Simulated human actionsActively faked clicks, mouse movements, page scrolling
4. Obfuscated data center originsData center bots pretended to be from residential IP addresses
Where is Ad Fraud Concentrated?
March 2017 / Page 8marketing.scienceconsulting group, inc.
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CPM/CPC buckets (91% of spend) is most targeted
Impressions(CPM/CPV)
Clicks(CPC)
Search27%
91% digital spend
Display10%
Video7%
Mobile47%
Leads(CPL)
Sales(CPA)
Lead Gen$2.0B
Other$5.0B
• classifieds• sponsorship• rich media
(89% in 2015)
Source: IAB 1H 2016 Report
(86% in 2014)
March 2017 / Page 9marketing.scienceconsulting group, inc.
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Two key ingredients of CPM and CPC Fraud
Impression(CPM) Fraud
(includes mobile display, video ads)
1. Put up fake websites and load tons of display ads on the pages
Search Click (CPC) Fraud
(includes mobile search ads)
2. Use fake users (bots) to repeatedly load pages to generate fake ad impressions
1. Put up fake websites and participate in search networks
2. Use fake users (bots) to type keywords and click on them to generate the CPC revenue
screen shots of fake sites
Fake Websites(cash-out sites)
March 2017 / Page 11marketing.scienceconsulting group, inc.
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Websites – spectrum from bad to good
Ad Fraud Sites
Click Fraud Sites
100% bot
mostly human
Piracy Sites
Premium Publishers
Sites w/ Sourced Traffic
“fraud sites” “sites w/ questionable practices” “good guys”
“real content that real humans want to read”
March 2017 / Page 12marketing.scienceconsulting group, inc.
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Countless fraud sites made by template
100% bot
Fake Visitors(bots)
March 2017 / Page 14marketing.scienceconsulting group, inc.
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Bots are automated browsers used for ad fraud
Headless BrowsersSeleniumPhantomJSZombie.jsSlimerJS
Mobile Simulators35 listed
Bots are made from malware compromised PCs or headless browsers (no screen) in datacenters.
Bots
March 2017 / Page 15marketing.scienceconsulting group, inc.
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Bots range in sophistication, and therefore cost
Javascript installed on webpage
Malware on PCsData Center BotsOn-Page Bots
Headless browsers in data centers
Malware installed on humans’ devices
Less sophisticated Most sophisticated
Source: AdAge/Augustine Fou, Mar 2014 Source: Forensiq Source: Augustine Fou, Oct 2015
“the official industry lists of bots catch NONE of these bots, not one.”
1 cent CPMsLoad pages, click
10 cent CPMsFake scroll, mouse movement, click
1 dollar CPMsReplay human-like mouse movements, clone cookies
“The equation of ad fraud is simple: buy traffic for $1 CPMs, sell ads for $10 CPMs; pocket $9 of pure profit.”
March 2017 / Page 17marketing.scienceconsulting group, inc.
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How Ad Fraud Harms
Advertisers
March 2017 / Page 18marketing.scienceconsulting group, inc.
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Messes up your analytics
click on links
load webpages tune bounce rate
tune pages/visit
“bad guys’ bots are advanced enough to fake most metrics”
March 2017 / Page 19marketing.scienceconsulting group, inc.
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Messes up your KPIsProgrammatic display
(18-45% clicks from advanced bots)Premium publishers(0% clicks from bots)
0.13% CTR(18% of clicks by bots)
1.32% CTR(23% of clicks by bots)
5.93% CTR(45% of clicks by bots)
Campaign KPI: CTRs
March 2017 / Page 20marketing.scienceconsulting group, inc.
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Want 100% viewability? 0% NHT (bots)?
Bad guys cheat and stack ALL ads above the fold to make 100% viewability.
“100% viewability? Sure, no problem.”
AD• IAS filtered traffic, • DV filtered traffic• Pixalate filtered traffic, • MOAT filtered traffic, • Forensiq filtered traffic
“0% NHT? Sure, no problem.”
Current State of NHT Detection
March 2017 / Page 22marketing.scienceconsulting group, inc.
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Fraud bots are NOT on any list
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
March 2017 / Page 23marketing.scienceconsulting group, inc.
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Three main places for NHT detection
In-Ad(ad iframes)
On-Site(publishers’ sites)
• Used by advertisersto measure ad impressions
• Limitations – tag is in foreign iframe, severe limits on detection
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
March 2017 / Page 24marketing.scienceconsulting group, inc.
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In-ad measurements could be entirely wrong
Publisher Webpage
publisher.com
Foreign Ad iFrames
adserver.com
Cross-domain (XSS) security restrictions mean iframe cannot:• read content in parent frame• detect actions in parent frame• see where it is on the page
(above- or below- fold)• detect characteristics of the
parent page
1x1 pixeljs ad tags ride along
inside iframe
incorrectly reported as100% viewable
March 2017 / Page 25marketing.scienceconsulting group, inc.
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5% bots doesn’t mean 95% humans
good publishers
ad exchanges/networks
volume bars (green)
Stacked percentBlue (human)Red (bots)
red v blue trendlines
“Having fraud DETECTION is not the same as having fraud PROTECTION.”
Case Examples
March 2017 / Page 28marketing.scienceconsulting group, inc.
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Stepwise improvement using our data
Period 1 Period 3Period 2
Initial baseline measurement
Measurement after first optimization
Eliminating several “problematic” networks
March 2017 / Page 29marketing.scienceconsulting group, inc.
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Better media leads to way better outcomesMeasure Ads Measure Arrivals Measure Conversions
clean, good media
low-cost media, ad exchanges
346
1743
5
156
30X better outcomes• More arrivals• Better quality
March 2017 / Page 30marketing.scienceconsulting group, inc.
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More accurate analytics when data is clean
7% conversion rate 13% conversion rateartificially low actually correct
Bot Fraud Game Show
March 2017 / Page 32marketing.scienceconsulting group, inc.
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Where would you prefer to place your ads?
A
B
March 2017 / Page 33marketing.scienceconsulting group, inc.
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Which chart shows real human traffic surges?
A
B
March 2017 / Page 34marketing.scienceconsulting group, inc.
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Traffic surges caused by bots vs real humans
Caused by bots
Caused by humans
A
B
March 2017 / Page 35marketing.scienceconsulting group, inc.
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Which chart shows fake/sourced traffic?
A
B
March 2017 / Page 36marketing.scienceconsulting group, inc.
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Which chart shows fake/sourced traffic?
A
B
March 2017 / Page 37marketing.scienceconsulting group, inc.
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Which chart shows fraudulent mobile apps?
A B
March 2017 / Page 38marketing.scienceconsulting group, inc.
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Which chart shows fraudulent mobile apps?
A B
March 2017 / Page 39marketing.scienceconsulting group, inc.
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Would you buy more media from this site?
102,231 sessions
0 sessions
goal events
YES NO
March 2017 / Page 40marketing.scienceconsulting group, inc.
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Would you buy more media on this site? NO!
102,231 sessions
0 sessions
goal event – no change
March 2017 / Page 41marketing.scienceconsulting group, inc.
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Mix and Match – which goes with which?
A
B
C
video entertainment
sports info site
investment info site
“Let’s go fight some bad guys
together!”
March 2017 / Page 43marketing.scienceconsulting group, inc.
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About the Author
March 2017
Augustine Fou, PhD.
212. 203 .7239
March 2017 / Page 44marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
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
March 2017 / Page 45marketing.scienceconsulting group, inc.
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Harvard Business Review – October 2015
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.