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February 2019 / Page 0marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
How Brands Are Solving
Ad Fraud Themselves
February 2019
Augustine Fou, PhD.
acfou [at] mktsci.com
212. 203 .7239
February 2019 / Page 1marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Agenda
• What is ad fraud?
• How did it happen?
• Why is it not detected?
• What have some marketers done?
February 2019 / Page 2marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
What is Ad Fraud?
February 2019 / Page 3marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
What is digital ad fraud ?
Ad Fraud = ad impressions caused
by bots, not seen by humans
Impression Fraud
(CPM) Fraud
(includes mobile display, video ads)
Click Fraud
(CPC) Fraud
(includes mobile search ads)
February 2019 / Page 4marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Why? Largest spend buckets
Leads
(CPL)
Sales
(CPA)
Lead Gen
$2.0B
Other
$5.0B
• classifieds
• sponsorship
• rich media
Impressions
(CPM/CPV)
Clicks
(CPC)
Search 46%
Display 31%
Video 14%
91% digital ad spend Source: IAB FY 2017 Report
Estimated >$300B in 2018
9% spend
February 2019 / Page 5marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
How? Three step process
1. set up
FAKE SITES
2. buy
FAKE TRAFFIC
3. sell
FAKE ADS
February 2019 / Page 6marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Why is ad fraud bad?
Advertisers Publishers
Bad Guys
1/3
2/3
Ads are not shown
to humans, wasted
ad dollars
Ad revenue declines
because dollars are
stolen by bad guys.
Steal money using fake
ads; siphon dollars out
of ecosystem.
February 2019 / Page 7marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Ad dollars fund child abuse sites
“Using a variety of sophisticated techniques to avoid detection,
offenders are exploiting online advertising networks to monetise their
distribution of child sexual abuse material.”
Source: The Drum Nov 6, 2018
Source: CNN, Feb 2019
February 2019 / Page 8marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
(2013) Ad dollars fund piracy sites
“Highly Lucrative, Profitable
The aggregate ad revenue
for the sample of 596 sites
was an estimated $56.7
million for Q3 of 2013,
projecting out to $226.7
million dollars annually,
with average profit margins
of 83%, ranging from 80% to
as high as 94%.”
Source: Digital Citizens Alliance Study
https://thetrichordist.com/2013/01/28/over-50-major-
brands-supporting-music-piracy-its-big-business/
February 2019 / Page 9marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
DDoS traffic for ad revenueDDoS attacks overwhelm with traffic; now use traffic to make ad revenue
Google Digital Attack Map
February 2019 / Page 10marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Economics of botnets explained
Source: MIT Tech Review, May 2018
“distributed denial-of-service
attacks using a network of 30,000
bots can generate around
$26,000 a month. Spam
advertising with 10,000 bots
generates around $300,000 a
month, and bank fraud with
30,000 bots can generate over
$18 million per month. But the
most profitable undertaking is
click fraud, which generates well
over $20 million a month of
profit.”
Botnets can be used
for a variety of things
February 2019 / Page 11marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Ad Tech Gave Rise to
Ad Fraud
February 2019 / Page 12marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Adtech enabled siphoning
PublishersAdvertisers
Human
Audience
Advertisers
Publishers
Human
Audience
Fake Users
Fake Sites
1995
2015
February 2019 / Page 13marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Badtech Tax: 60-70% extracted
Source: WFA, April 2017
Source: ANA, May 2017
February 2019 / Page 14marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Case examples of this …
Publisher only gets 30-60c on the dollar after middlemen fees
https://mediatel.co.uk/newsline/2016/10/04/where-did-the-
money-go-guardian-buys-its-own-ad-inventory
2016
The Guardian
“for every pound an advertiser
spends programmatically on the
Guardian only 30 pence actually
goes to the publisher.”
2017
BusinessInsider
“$40,000 worth of ad inventory
through the open exchanges,
the publication only saw $97.”
http://adage.com/article/digital/business-insider-york-times-
shed-details-ad-industry-s-biggest-problem/311081/
February 2019 / Page 15marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
U.S. Digital Ad Spend Distribution
$46 Search Display/Video $46
$32$39
$8
Google Search FB+Google Display$29
(outside Google/Facebook)
$100 Billion Digital SpendSource: IAB 2H 2018 Report
Source: Verisign, Q4 2016
329M
domains
est. 1 million est. 164 million
7M
apps
Source: Statista, March 2017
est. 10,000 est. 6.99 million
1% of
impressions
99% of
impressions
$10B $19B
Good Publishers “sites/apps with ads”
February 2019 / Page 16marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Scarcity … vs unlim fake ads
Infinite quantities of digital ads can be created on real or fake sites
Unlike real billboards that
people actually drive by in
the physical world …
Limitless quantities of digital
ads can be created on fake
sites that humans never visit.
February 2019 / Page 17marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Myth of the long tail
Most people visit sites they know most; occasionally long tail ones
“There are numerous pieces of research on how even as people
accumulate hundreds of TV channels, they only watch seven. It's rather
commonly accepted that in a sea of millions of mobile apps, most people
stick to half a dozen.” http://www.businessinsider.com/the-advertising-industry-has-been-living-a-lie-2017-10
February 2019 / Page 18marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Myth of Hypertargeting
After 3 parameters, the matching audience gets really tiny
Female Male
18-25 13-17 25-34 35-49 50+
1. gender
2. age range
3. geographic location
50%
10%
2%
100 params?
300 params?
Starting Audience 100%
?
?
% of AudienceTargeting parameters
February 2019 / Page 19marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Myth of behavioral targeting
Ad tech sold the idea of deriving intent from web history
Outdoor
enthusiast?Male? Female?
“This works on simplistic examples, like the above. But when the list of sites grows
longer and more diverse, the assumptions used to derive data points, even gender, are
going to be less and less accurate. In fact, a recent study of online identifiers determined
that over 80% of the records were designated as BOTH male and female.”
Source: Yeah, Your Data’s Screwed
February 2019 / Page 20marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
hypertargeting
behavioral targeting
“Badtech” harms all parties
Good Publishers
(lower revenue, CPMs)
Consumers
(privacy violations)
Advertisers
(ad fraud, no outcomes)
Badtech
Industrial
Complex
Badtech
Industrial
Complex long tail sites
February 2019 / Page 21marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Gross Failures of Fraud
Detection Tech
February 2019 / Page 22marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Bad guys easily avoid detection
Blocking of tags, altering measurement to avoid detection
Detection Tag Blocking— analytics
tags/fraud detection tags are accidentally
blocked or maliciously stripped out
“malicious code manipulated data to
ensure that otherwise unviewable ads
showed up in measurement systems
as valid impressions, which resulted in
payment being made for the ad.”
Source: Buzzfeed, March 2018
February 2019 / Page 23marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Traffic sellers’ “high quality traffic”
Many sources to buy “traffic” and even tune “quality” level
Choose Your “Traffic Quality Level”
“Valid traffic” goes
for higher prices
February 2019 / Page 24marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
(2017) Pop-Unders / Redirects
These forms of fraud typically get by current fraud detection tech
a.k.a. “zero-click” “pop-under”
“forced-view” “auto-nav”
Source: https://www.buzzfeed.com/craigsilverman/remember-tom
February 2019 / Page 25marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
(2018) Cheetah was cheating
“Eight apps with a total of more than 2 billion
downloads in the Google Play store have been
exploiting user permissions as part of an ad
fraud scheme that could have stolen millions
of dollars.”
Source: Buzzfeed News, Nov 2018
February 2019 / Page 26marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Fake sites/apps NOT detected
1221e236c3f8703.com
62b70ac32d4614b.com
a6f845e6c37b2833148.com
da60995df247712.com
d869381a42af33b.com
a1b1ea8f418ca02ad4e.com
1de10ecf04779.com
2c0dad36bdb9eb859f0.com
a6be07586bc4a7.com
fe95a992e6afb.com
42eed1a0d9c129.com
da6fda11b2b0ba.com
afa9bdfa63bf7.com
739c49a8c68917.com
baa2e174884c9c0460e.com
d602196786e42d.com
153105c2f9564.com
8761f9f83613.com
20a840a14a0ef7d6.com
31a5610ce3a8a2.com
5726303d87522d05.com
3ac901bf5793b0fccff.com
b014381c95cb.com
2137dc12f9d8.com
06f09b1008ae993a5a.com
fbfd396918c60838.com
97ff623306ff4c26996.com
b1f6fe5e3f0c3c8ba6.com
23205523023daea6.com
6068a17eed25.com
b1fe8a95ae27823.com
f4906b7c15ba.com
eac0823ca94e3c07.com
1f7de8569ea97f0614.com
21c9a53484951.com
24ad89fc2690ed9369.com
efd3b86a5fbddda.com
34c2f22e9503ace.com
0926a687679d337e9d.com
6a40194bef976cc.com
33ae985c0ea917.com
02aa19117f396e9.com
f8260adbf8558d6.com
9376ec23d50b1.com
pushedwebnews.com
a0675c1160de6c6.com
0f461325bf56c3e1b9.com
850a54dbd2398a2.com
com.dxnxbgj.mkridqxviiqaogw
com.obugniljhe.fptvznqwhmcjm
com.bpo.ksuhpsdkgvbtlsw
com.rlcznwgouw.vvtexstbfttngc
com.kasbgf.sbzwtgpcbjexi
com.bprlgbl.vbze
com.zka.lzhsoueilo
com.alxsavx.mizzucnlb
com.jxknvk.lrwfdfirdzpsw
com.tvwvqbt.wbshaguqy
com.iwnxtpahcu.leyuehdwdbb
com.okf.rhvemtykfibzpxj
com.obpmirzste.ldsjpv
com.zmm.shmxvjxnsagndui
com.nqzwr.leusrmpmsq
com.rced.zcdsglptpdlwpu
com.kerms.ehlsgnc
com.cmia.iabhheltm
com.skggynmtx.tyyjnwpefvqtll
com.kgdtltnuv.hayvfhob
com.ztzsiqg.dyojlxdscxws
com.xlwuqe.ddrdhsuosbn
com.rkrhmzee.wjcoznxu
com.ebhzb.hbzvomzpcctovj
Fake sites Fake sites Fake apps
February 2019 / Page 27marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Chase: -99% reach, no impact
“JPMorgan had already decided
last year to oversee its own
programmatic buying operation.
Advertisements for JPMorgan
Chase were appearing on about
400,000 websites a month. [But]
only 12,000, or 3 percent, led to
activity beyond an impression.
[Then, Chase] limited its display
ads to about 5,000 websites. We
haven’t seen any deterioration on
our performance metrics,” Ms.
Lemkau said.”
“99% reduction in ‘reach’ … Same Results.”
Source: NYTimes, March 29, 2017
(because it wasn’t real, human reach)
February 2019 / Page 28marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
P&G: cut $200M, no impact
“Once we got transparency, it
illuminated what reality was,” said
Mr. Pritchard. P&G then took matters
into its owns hands and voted with
its dollars, he said.”
“As we all chased the Holy Grail of
digital, self-included, we were
relinquishing too much control—
blinded by shiny objects,
overwhelmed by big data, and ceding
power to algorithms,” Mr. Pritchard
said.
Source: WSJ, March 2018
February 2019 / Page 29marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Just because you can’t measure it
… doesn’t mean it’s not there.
February 2019 / Page 30marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Marketer 1 Case Study
February 2019 / Page 31marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Which site would you buy from?
A
B
February 2019 / Page 32marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Which site would you buy from?
A
B
February 2019 / Page 33marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
What we measured – ads and site
IN-AD
tag placed in display ads,
to determine quality of
sites and apps that
loaded them
ON-SITE
embed code placed on a
brand site to determine
quality of visitors arriving
on the site; cross check
clicks from the ads
February 2019 / Page 34marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Confirmed Bots – 2.3%, not bad
Good media buying limited fraud to < 3% in impressions
February 2019 / Page 35marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Datacenter visits – 1% (half of bots)
Data center bots made up about half of the confirmed bots
February 2019 / Page 36marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Confirmed Bots – Supporting Data
The data confirmed servers (Linux x86_64), from data centers
February 2019 / Page 37marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Confirmed Bots – Supporting Data
Bots had 0x0 window sizes and a good portion was hidden
February 2019 / Page 38marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Select high volume site(s) to investigate
February 2019 / Page 39marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Why s***********y.com is suspicious
Note, all of the site’s traffic is from Android 8.0.0 devices, strange.
February 2019 / Page 40marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Sites to turn off
February 2019 / Page 41marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Top apps to turn off
February 2019 / Page 42marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Marketer 2 Case Study
February 2019 / Page 43marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Would you buy from this site?
Unique devices loading ads 100% Android 8.0.0 visitors
February 2019 / Page 44marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Fraud type: Apps load webpages
“fraud sites’ traffic comes from apps that load hidden webpages”
Openly selling on LinkedIn
February 2019 / Page 45marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Mobile apps loading webpages
Almost all disguised to be from Facebook app; nearly 100% Android
February 2019 / Page 46marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Top 10 apps ate 57% of volume
Turned off the line items of these apps in the campaign interface
within the first day; rest of the campaign ran more cleanly.
February 2019 / Page 47marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Overall fraud is more than just bots
Sites and apps that cheat may look fine in bot detection reports
1.3% + 57% = 58%
bot fraud site/app fraud overall fraud
bot detection sees this
bot detection misses this
February 2019 / Page 48marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Marketer 3 Case Study
February 2019 / Page 49marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Would you buy from these sites?
Bad guys may not
even wait till the ad
is served since they
are already paid
based on the number
of impressions won.
From the data, the
more fraudulent the
site, the greater the
discrepancy
– e.g. 80 – 100%
DSP says Adserver says
February 2019 / Page 50marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Taking control of digital media
2016
Still buying
through exchanges
Measure In-Ad
and arrivals On-Site
2017
Buy their own ads
through DSP
Took buying in-
house
2018
Started serving
their own ads
Took ad serving
in-house
2019 …
Buying direct from good publishers
February 2019 / Page 51marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Detect and reduce fraud in-flight
Launch Week 3 onwardWeeks 1-2
Initial baseline
measurement
Measurement after
first optimization
After eliminating several
“problematic” networks
Stacked percent chart
Blue (human)
Red (bots)
February 2019 / Page 52marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Better media = better outcomes
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
February 2019 / Page 53marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Local TV websites - clean
Great consistency in the data over long periods of time
February 2019 / Page 54marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Local radio websites - clean
Great consistency in the data over long periods of time
February 2019 / Page 55marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Magazine websites - clean
Great consistency in the data over long periods of time
February 2019 / Page 56marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Human CPM, not just CPM
Low CPM sources result in
higher cost per human –
like 11X the cost.
Sources of different
quality send widely
different amounts of
humans to landing pages.
February 2019 / Page 57marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Display 4
2,036 humans
human conversion rate
More humans = more outcomes
Site Traffic Conversions
8,482 818
4,216 humans
5%
human conversion rate
14,539 193
225 humans
9%
human conversion rate
2,248 23
168 humans
5%
human conversion rate
1,527 9
Display 3
Display 2
Display 1
Humans
40%
February 2019 / Page 58marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
#defendthespend
“marketers can (and should) reduce the
flow of dollars to cybercriminals that are
committing ‘major economic crimes’.”
Then, and only then, will we get
back to REAL digital marketing.”
February 2019 / Page 59marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Digital Marketing circa 2018
February 2019 / Page 60marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
About the Author
Augustine Fou, PhD.
acfou [@] mktsci.com
212. 203 .7239
February 2019 / Page 61marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Dr. Augustine Fou – Researcher
2013
2014
Published slide decks and posts:
http://www.slideshare.net/augustinefou/presentations
https://www.linkedin.com/today/author/augustinefou
2016
2015
2017
20192018

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How Brands are Solving Ad Fraud Themselves

  • 1. February 2019 / Page 0marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou How Brands Are Solving Ad Fraud Themselves February 2019 Augustine Fou, PhD. acfou [at] mktsci.com 212. 203 .7239
  • 2. February 2019 / Page 1marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Agenda • What is ad fraud? • How did it happen? • Why is it not detected? • What have some marketers done?
  • 3. February 2019 / Page 2marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou What is Ad Fraud?
  • 4. February 2019 / Page 3marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou What is digital ad fraud ? Ad Fraud = ad impressions caused by bots, not seen by humans Impression Fraud (CPM) Fraud (includes mobile display, video ads) Click Fraud (CPC) Fraud (includes mobile search ads)
  • 5. February 2019 / Page 4marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Why? Largest spend buckets Leads (CPL) Sales (CPA) Lead Gen $2.0B Other $5.0B • classifieds • sponsorship • rich media Impressions (CPM/CPV) Clicks (CPC) Search 46% Display 31% Video 14% 91% digital ad spend Source: IAB FY 2017 Report Estimated >$300B in 2018 9% spend
  • 6. February 2019 / Page 5marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou How? Three step process 1. set up FAKE SITES 2. buy FAKE TRAFFIC 3. sell FAKE ADS
  • 7. February 2019 / Page 6marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Why is ad fraud bad? Advertisers Publishers Bad Guys 1/3 2/3 Ads are not shown to humans, wasted ad dollars Ad revenue declines because dollars are stolen by bad guys. Steal money using fake ads; siphon dollars out of ecosystem.
  • 8. February 2019 / Page 7marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Ad dollars fund child abuse sites “Using a variety of sophisticated techniques to avoid detection, offenders are exploiting online advertising networks to monetise their distribution of child sexual abuse material.” Source: The Drum Nov 6, 2018 Source: CNN, Feb 2019
  • 9. February 2019 / Page 8marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou (2013) Ad dollars fund piracy sites “Highly Lucrative, Profitable The aggregate ad revenue for the sample of 596 sites was an estimated $56.7 million for Q3 of 2013, projecting out to $226.7 million dollars annually, with average profit margins of 83%, ranging from 80% to as high as 94%.” Source: Digital Citizens Alliance Study https://thetrichordist.com/2013/01/28/over-50-major- brands-supporting-music-piracy-its-big-business/
  • 10. February 2019 / Page 9marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou DDoS traffic for ad revenueDDoS attacks overwhelm with traffic; now use traffic to make ad revenue Google Digital Attack Map
  • 11. February 2019 / Page 10marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Economics of botnets explained Source: MIT Tech Review, May 2018 “distributed denial-of-service attacks using a network of 30,000 bots can generate around $26,000 a month. Spam advertising with 10,000 bots generates around $300,000 a month, and bank fraud with 30,000 bots can generate over $18 million per month. But the most profitable undertaking is click fraud, which generates well over $20 million a month of profit.” Botnets can be used for a variety of things
  • 12. February 2019 / Page 11marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Ad Tech Gave Rise to Ad Fraud
  • 13. February 2019 / Page 12marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Adtech enabled siphoning PublishersAdvertisers Human Audience Advertisers Publishers Human Audience Fake Users Fake Sites 1995 2015
  • 14. February 2019 / Page 13marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Badtech Tax: 60-70% extracted Source: WFA, April 2017 Source: ANA, May 2017
  • 15. February 2019 / Page 14marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Case examples of this … Publisher only gets 30-60c on the dollar after middlemen fees https://mediatel.co.uk/newsline/2016/10/04/where-did-the- money-go-guardian-buys-its-own-ad-inventory 2016 The Guardian “for every pound an advertiser spends programmatically on the Guardian only 30 pence actually goes to the publisher.” 2017 BusinessInsider “$40,000 worth of ad inventory through the open exchanges, the publication only saw $97.” http://adage.com/article/digital/business-insider-york-times- shed-details-ad-industry-s-biggest-problem/311081/
  • 16. February 2019 / Page 15marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou U.S. Digital Ad Spend Distribution $46 Search Display/Video $46 $32$39 $8 Google Search FB+Google Display$29 (outside Google/Facebook) $100 Billion Digital SpendSource: IAB 2H 2018 Report Source: Verisign, Q4 2016 329M domains est. 1 million est. 164 million 7M apps Source: Statista, March 2017 est. 10,000 est. 6.99 million 1% of impressions 99% of impressions $10B $19B Good Publishers “sites/apps with ads”
  • 17. February 2019 / Page 16marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Scarcity … vs unlim fake ads Infinite quantities of digital ads can be created on real or fake sites Unlike real billboards that people actually drive by in the physical world … Limitless quantities of digital ads can be created on fake sites that humans never visit.
  • 18. February 2019 / Page 17marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Myth of the long tail Most people visit sites they know most; occasionally long tail ones “There are numerous pieces of research on how even as people accumulate hundreds of TV channels, they only watch seven. It's rather commonly accepted that in a sea of millions of mobile apps, most people stick to half a dozen.” http://www.businessinsider.com/the-advertising-industry-has-been-living-a-lie-2017-10
  • 19. February 2019 / Page 18marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Myth of Hypertargeting After 3 parameters, the matching audience gets really tiny Female Male 18-25 13-17 25-34 35-49 50+ 1. gender 2. age range 3. geographic location 50% 10% 2% 100 params? 300 params? Starting Audience 100% ? ? % of AudienceTargeting parameters
  • 20. February 2019 / Page 19marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Myth of behavioral targeting Ad tech sold the idea of deriving intent from web history Outdoor enthusiast?Male? Female? “This works on simplistic examples, like the above. But when the list of sites grows longer and more diverse, the assumptions used to derive data points, even gender, are going to be less and less accurate. In fact, a recent study of online identifiers determined that over 80% of the records were designated as BOTH male and female.” Source: Yeah, Your Data’s Screwed
  • 21. February 2019 / Page 20marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou hypertargeting behavioral targeting “Badtech” harms all parties Good Publishers (lower revenue, CPMs) Consumers (privacy violations) Advertisers (ad fraud, no outcomes) Badtech Industrial Complex Badtech Industrial Complex long tail sites
  • 22. February 2019 / Page 21marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Gross Failures of Fraud Detection Tech
  • 23. February 2019 / Page 22marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Bad guys easily avoid detection Blocking of tags, altering measurement to avoid detection Detection Tag Blocking— analytics tags/fraud detection tags are accidentally blocked or maliciously stripped out “malicious code manipulated data to ensure that otherwise unviewable ads showed up in measurement systems as valid impressions, which resulted in payment being made for the ad.” Source: Buzzfeed, March 2018
  • 24. February 2019 / Page 23marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Traffic sellers’ “high quality traffic” Many sources to buy “traffic” and even tune “quality” level Choose Your “Traffic Quality Level” “Valid traffic” goes for higher prices
  • 25. February 2019 / Page 24marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou (2017) Pop-Unders / Redirects These forms of fraud typically get by current fraud detection tech a.k.a. “zero-click” “pop-under” “forced-view” “auto-nav” Source: https://www.buzzfeed.com/craigsilverman/remember-tom
  • 26. February 2019 / Page 25marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou (2018) Cheetah was cheating “Eight apps with a total of more than 2 billion downloads in the Google Play store have been exploiting user permissions as part of an ad fraud scheme that could have stolen millions of dollars.” Source: Buzzfeed News, Nov 2018
  • 27. February 2019 / Page 26marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Fake sites/apps NOT detected 1221e236c3f8703.com 62b70ac32d4614b.com a6f845e6c37b2833148.com da60995df247712.com d869381a42af33b.com a1b1ea8f418ca02ad4e.com 1de10ecf04779.com 2c0dad36bdb9eb859f0.com a6be07586bc4a7.com fe95a992e6afb.com 42eed1a0d9c129.com da6fda11b2b0ba.com afa9bdfa63bf7.com 739c49a8c68917.com baa2e174884c9c0460e.com d602196786e42d.com 153105c2f9564.com 8761f9f83613.com 20a840a14a0ef7d6.com 31a5610ce3a8a2.com 5726303d87522d05.com 3ac901bf5793b0fccff.com b014381c95cb.com 2137dc12f9d8.com 06f09b1008ae993a5a.com fbfd396918c60838.com 97ff623306ff4c26996.com b1f6fe5e3f0c3c8ba6.com 23205523023daea6.com 6068a17eed25.com b1fe8a95ae27823.com f4906b7c15ba.com eac0823ca94e3c07.com 1f7de8569ea97f0614.com 21c9a53484951.com 24ad89fc2690ed9369.com efd3b86a5fbddda.com 34c2f22e9503ace.com 0926a687679d337e9d.com 6a40194bef976cc.com 33ae985c0ea917.com 02aa19117f396e9.com f8260adbf8558d6.com 9376ec23d50b1.com pushedwebnews.com a0675c1160de6c6.com 0f461325bf56c3e1b9.com 850a54dbd2398a2.com com.dxnxbgj.mkridqxviiqaogw com.obugniljhe.fptvznqwhmcjm com.bpo.ksuhpsdkgvbtlsw com.rlcznwgouw.vvtexstbfttngc com.kasbgf.sbzwtgpcbjexi com.bprlgbl.vbze com.zka.lzhsoueilo com.alxsavx.mizzucnlb com.jxknvk.lrwfdfirdzpsw com.tvwvqbt.wbshaguqy com.iwnxtpahcu.leyuehdwdbb com.okf.rhvemtykfibzpxj com.obpmirzste.ldsjpv com.zmm.shmxvjxnsagndui com.nqzwr.leusrmpmsq com.rced.zcdsglptpdlwpu com.kerms.ehlsgnc com.cmia.iabhheltm com.skggynmtx.tyyjnwpefvqtll com.kgdtltnuv.hayvfhob com.ztzsiqg.dyojlxdscxws com.xlwuqe.ddrdhsuosbn com.rkrhmzee.wjcoznxu com.ebhzb.hbzvomzpcctovj Fake sites Fake sites Fake apps
  • 28. February 2019 / Page 27marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Chase: -99% reach, no impact “JPMorgan had already decided last year to oversee its own programmatic buying operation. Advertisements for JPMorgan Chase were appearing on about 400,000 websites a month. [But] only 12,000, or 3 percent, led to activity beyond an impression. [Then, Chase] limited its display ads to about 5,000 websites. We haven’t seen any deterioration on our performance metrics,” Ms. Lemkau said.” “99% reduction in ‘reach’ … Same Results.” Source: NYTimes, March 29, 2017 (because it wasn’t real, human reach)
  • 29. February 2019 / Page 28marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou P&G: cut $200M, no impact “Once we got transparency, it illuminated what reality was,” said Mr. Pritchard. P&G then took matters into its owns hands and voted with its dollars, he said.” “As we all chased the Holy Grail of digital, self-included, we were relinquishing too much control— blinded by shiny objects, overwhelmed by big data, and ceding power to algorithms,” Mr. Pritchard said. Source: WSJ, March 2018
  • 30. February 2019 / Page 29marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Just because you can’t measure it … doesn’t mean it’s not there.
  • 31. February 2019 / Page 30marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Marketer 1 Case Study
  • 32. February 2019 / Page 31marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Which site would you buy from? A B
  • 33. February 2019 / Page 32marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Which site would you buy from? A B
  • 34. February 2019 / Page 33marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou What we measured – ads and site IN-AD tag placed in display ads, to determine quality of sites and apps that loaded them ON-SITE embed code placed on a brand site to determine quality of visitors arriving on the site; cross check clicks from the ads
  • 35. February 2019 / Page 34marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Confirmed Bots – 2.3%, not bad Good media buying limited fraud to < 3% in impressions
  • 36. February 2019 / Page 35marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Datacenter visits – 1% (half of bots) Data center bots made up about half of the confirmed bots
  • 37. February 2019 / Page 36marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Confirmed Bots – Supporting Data The data confirmed servers (Linux x86_64), from data centers
  • 38. February 2019 / Page 37marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Confirmed Bots – Supporting Data Bots had 0x0 window sizes and a good portion was hidden
  • 39. February 2019 / Page 38marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Select high volume site(s) to investigate
  • 40. February 2019 / Page 39marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Why s***********y.com is suspicious Note, all of the site’s traffic is from Android 8.0.0 devices, strange.
  • 41. February 2019 / Page 40marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Sites to turn off
  • 42. February 2019 / Page 41marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Top apps to turn off
  • 43. February 2019 / Page 42marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Marketer 2 Case Study
  • 44. February 2019 / Page 43marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Would you buy from this site? Unique devices loading ads 100% Android 8.0.0 visitors
  • 45. February 2019 / Page 44marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Fraud type: Apps load webpages “fraud sites’ traffic comes from apps that load hidden webpages” Openly selling on LinkedIn
  • 46. February 2019 / Page 45marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Mobile apps loading webpages Almost all disguised to be from Facebook app; nearly 100% Android
  • 47. February 2019 / Page 46marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Top 10 apps ate 57% of volume Turned off the line items of these apps in the campaign interface within the first day; rest of the campaign ran more cleanly.
  • 48. February 2019 / Page 47marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Overall fraud is more than just bots Sites and apps that cheat may look fine in bot detection reports 1.3% + 57% = 58% bot fraud site/app fraud overall fraud bot detection sees this bot detection misses this
  • 49. February 2019 / Page 48marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Marketer 3 Case Study
  • 50. February 2019 / Page 49marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Would you buy from these sites? Bad guys may not even wait till the ad is served since they are already paid based on the number of impressions won. From the data, the more fraudulent the site, the greater the discrepancy – e.g. 80 – 100% DSP says Adserver says
  • 51. February 2019 / Page 50marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Taking control of digital media 2016 Still buying through exchanges Measure In-Ad and arrivals On-Site 2017 Buy their own ads through DSP Took buying in- house 2018 Started serving their own ads Took ad serving in-house 2019 … Buying direct from good publishers
  • 52. February 2019 / Page 51marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Detect and reduce fraud in-flight Launch Week 3 onwardWeeks 1-2 Initial baseline measurement Measurement after first optimization After eliminating several “problematic” networks Stacked percent chart Blue (human) Red (bots)
  • 53. February 2019 / Page 52marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Better media = better outcomes 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
  • 54. February 2019 / Page 53marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Local TV websites - clean Great consistency in the data over long periods of time
  • 55. February 2019 / Page 54marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Local radio websites - clean Great consistency in the data over long periods of time
  • 56. February 2019 / Page 55marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Magazine websites - clean Great consistency in the data over long periods of time
  • 57. February 2019 / Page 56marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Human CPM, not just CPM Low CPM sources result in higher cost per human – like 11X the cost. Sources of different quality send widely different amounts of humans to landing pages.
  • 58. February 2019 / Page 57marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Display 4 2,036 humans human conversion rate More humans = more outcomes Site Traffic Conversions 8,482 818 4,216 humans 5% human conversion rate 14,539 193 225 humans 9% human conversion rate 2,248 23 168 humans 5% human conversion rate 1,527 9 Display 3 Display 2 Display 1 Humans 40%
  • 59. February 2019 / Page 58marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou #defendthespend “marketers can (and should) reduce the flow of dollars to cybercriminals that are committing ‘major economic crimes’.” Then, and only then, will we get back to REAL digital marketing.”
  • 60. February 2019 / Page 59marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Digital Marketing circa 2018
  • 61. February 2019 / Page 60marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou About the Author Augustine Fou, PhD. acfou [@] mktsci.com 212. 203 .7239
  • 62. February 2019 / Page 61marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Dr. Augustine Fou – Researcher 2013 2014 Published slide decks and posts: http://www.slideshare.net/augustinefou/presentations https://www.linkedin.com/today/author/augustinefou 2016 2015 2017 20192018