Context of Fraud in Digital Advertising Ecosystem

Context of Fraud in
Digital Ad Ecosystem
April 2017
Augustine Fou, PhD.
acfou [at] mktsci.com
212. 203 .7239

April 2017 / Page 2marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Total digital opportunity: search + display
display spend left for good publishers
$83B digital spend (2017)
Source: eMarketer March 2017
Search Spend
$40 $40
Display Spend Other
$21$30
$3
Google Search FB+Google Display
$4E $11E
CPC Fraud CPM Fraud
(75% of search) (52% of display)
$8$6
$29
(outside Google/Facebook)
$33 programmatic
$24 private exchange$9 open

Top good domains vs “sites that carry ads”
100% bot
pageviews on
“fraud sites”
“sites that carry ads”
Source: Verisign, Q4 2016
329M
domains
$83B
digital
Google
Search
FB+GOOG
Display
$29
billion
“sites you’ve heard of”
WSJ
ESPN
NYTimes
Economist
Reuters
Elle
top 1 million + next 10 million
159 million
carry adsno ads
3%
“Digital spend outside
of Google/Facebook”

Display opportunity for good publishersAdvertisers
Publishers
are left with 30%
Bad Guys
siphon dollars OUT
of the ecosystem
30% ($6B)
60% ($11B)
Ad Blocking
users use ad blocking to
protect themselves
10% ($2B)
Ad Tech
“plumbing” and verification
Source: The Guardian, Oct 2016
$5B to Google Display
$16B to Facebook Display
Display Spend$40B
DisplaySpend

0
10
20
30
40
50
60
70
80
90
100
retail finance automotive telecom CPG entertainment pharma travel cons.
electronics
indexed spend share
indexed fraud rate
Every industry is affected, CPC vs CPM
High CPC industries
Hit with CPC Fraud
Source: Ad spend share data from IAB, May 2015 | Fraud rate data from Integral Ad Science Q2 2014 Fraud Report
High Spend industries
Hit with CPM Fraud

Ad fraud comes in large numbers…
Increased CPM prices
by 800%
Decreased impressions
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

Single botnet steals 15% of video spend
Source: Dec 2016 WhiteOps Discloses Methbot Research
“Methbot, steals $2 billion annualized;
and it avoided detection for years.”
1. Targeted video ad inventory
$13 average CPM, 10X
higher than display ads
2. Disguised as good publishers
Pretending to be good
publishers to cover tracks
3. Simulated human actions
Actively faked clicks, mouse
movements, page scrolling
4. Obfuscated data center origins
Data center bots pretended to
be from residential IP addresses

40-50% web traffic is NHT (Non-Human Traffic)
Distil Networks March 2017 – 39% botsIncapsula Dec 2016 – 52% bots

“The equation of ad fraud is simple:
buy traffic for $1 and sell ads for $10
you make $9 of pure profit.”

CPM and CPC buckets are most targeted
Leads
(CPL)
Sales
(CPA)
Lead Gen
$2.0B
Other
$5.0B
• classifieds
• sponsorship
• rich media
Impressions
(CPM/CPV)
Clicks
(CPC)
Search 27%Display 10%
Video 7%
60% fraud
40% fraud
80% fraud
Mobile 47%
50% fraud
91% digital ad spend Source: IAB 1H 2016 Report
mobile display mobile search

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 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 to
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)

Fake sites have no content, no humans
Identical sites
made by template
Alphanumeric
domains
They can sell ad
“inventory” at low prices;
still make huge profits
Source: Sadbottrue.com

Ad dollars diverted to very low CPMs
$40
Display Spend
$16
FB Display
$11E
$5Google Display
CPM Fraud
$8
$33 programmatic
$24 private exchange$9 open
100% bot traffic
“fraud (cash out) sites”
• No content
• Stolen content
• Fake content
low CPMs
higher CPMs
“sites with real content that
real humans want to read”
Source: DCN/ WhiteOps 2015

Bots are automated browsers used for fraud
Headless Browsers
Selenium
PhantomJS
Zombie.js
SlimerJS
Mobile Simulators
35 listed

Bots range in sophistication, and therefore cost
Javascript on
page or scripts
Sophisticated (29%)Moderate (46%)Simple (25%)
Headless browsers
in data centers
Malware on humans’
devices (residential)
Less sophisticated More sophisticated
Source: AdAge/Augustine Fou, Mar 2014 Source: Forensiq Source: Augustine Fou, Oct 2015
1 cent CPMs 10 cent CPMs 1 dollar CPMs
Source: Distil Networks 2017

Mobile fraud doesn’t even need bots
Bad apps load tons
of impressions in
background
Source: Forensiq
Fake mobile devices
install apps and
interact w/ them
Download and Install
Launch and Interact

Some campaigns have very little humans (blue)
Phone calls as conversion events
Comparing five paid display sources

But only humans convert, bots don’t …
Measure
Ads
Measure
Arrivals
Measure
Conversions
346
1743
5
156
A
B
30X more human
conversion events
• More arrivals
• Better quality
more humans (blue)
good publishers
low-cost media,
ad exchanges

About the Author
April 2017
Augustine Fou, PhD.
acfou [at] mktsci.com
212. 203 .7239

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/presentations
https://www.linkedin.com/today/author/augustinefou
2016
2015

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.

Context of Fraud in Digital Advertising Ecosystem

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