Do you think fraud detection tech works? Consider this. Bad guys are hackers. They have better tech and are always 1 step ahead of good guys trying to detect and catch them. Here are some questions to ask of fraud detection vendors so you can tell if you are getting ripped off and if they can actually do what they claim to be doing.

1. November 2018 / Page 0marketing.scienceconsulting group, inc.
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MARKETERS’ PLAYBOOK
Questions to Ask
Verification Vendors
Augustine Fou, PhD.
acfou [at] mktsci.com

2. November 2018 / Page 1marketing.scienceconsulting group, inc.
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“Digital ad fraud is at all time highs
– both in dollar and rate.
Most of the fraud is missed by fraud
detection tech, because bad guys have
better tech and easily trick or block them.”

3. November 2018 / Page 2marketing.scienceconsulting group, inc.
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Ad fraud is at all-time highs
There’s $100B in digital ad spend to steal from, year after year
U.S. Digital Ad Spend
($ billions)
Actuals Projected
Digital Ad Fraud
($ billions)
($300B worldwide)

4. November 2018 / Page 3marketing.scienceconsulting group, inc.
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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

5. November 2018 / Page 4marketing.scienceconsulting group, inc.
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Executive Summary
Marketers can take control and fight fraud with analytics/insights
1. Marketers should not assume that fraud verification
vendors can detect fraud and stop it. There are
technical limitations to what can be measured, how
much is measured, and if it is measured.
2. Marketers should look at their own analytics to see
if there are still tell-tale signs of fraud.
3. Marketers should ask hard and detailed questions
of their verification vendors to assess whether they
are even doing what they claim they can do.

6. November 2018 / Page 5marketing.scienceconsulting group, inc.
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Questions to ask your
fraud detection vendor

7. November 2018 / Page 6marketing.scienceconsulting group, inc.
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Do they have in-ad vs on-site tags?
Tags tuned for in-ad versus on-site measurement are needed
In-Ad
(rides with marketers’ ad)
On-Site
(installed on-site by publisher)
0% humans
60% bots
60% humans
3% bots
“fraud measurements could be entirely wrong, depending on
where the tag is placed and where the measurement is done.”

8. November 2018 / Page 7marketing.scienceconsulting group, inc.
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Do they measure for humans?
Measuring for humans is crucial; as is reporting not-measurable
volume bars (green)
Stacked percent
Blue (human)
White (not measurable)
Red (bots)
red v blue trendlines
“Fraud detection that only reports NHT/IVT is not correct”
10% bots does NOT mean 90% humans

9. November 2018 / Page 8marketing.scienceconsulting group, inc.
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Do they check for other fraud? How?
Fraud detection looks for IVT(bots); may miss other forms of fraud
% bot + % site + % mobile fraud
% overall fraud = 23%, not 5%
5% 11% 7%

10. November 2018 / Page 9marketing.scienceconsulting group, inc.
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Do they detect popunders/redirects
These forms of fraud typically get by current fraud detection tech
Vendor openly selling
125 billion page
redirects (pageviews)
per month, at low
CPMs)
a.k.a. “zero-click” “pop-under” “forced-view” “auto-nav”

11. November 2018 / Page 10marketing.scienceconsulting group, inc.
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Do they detect mobile app fraud?
“fraud sites’ traffic comes from apps that load hidden webpages”
Openly selling on LinkedIn

12. November 2018 / Page 11marketing.scienceconsulting group, inc.
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Do they sample the data?
Sampling can lead to large discrepancies and bad measurements
WRONG IVT Measurement
Source 3 - in ad iframe, badly sampled
Incorrect, due to sampling

13. November 2018 / Page 12marketing.scienceconsulting group, inc.
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Can they explain their measurement?
If something is marked as fraud, why?... or not fraud, why?
“detailed supporting data to show client why something was
marked as fraudulent, or marked as clean – not black box.”

14. November 2018 / Page 13marketing.scienceconsulting group, inc.
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Why are legit sites marked as fraud
Something is wrong when legit sites are marked fraud and blocked
Domain (spoofed) % SIVT
esquire.com 77%
travelchannel.com 76%
foodnetwork.com 76%
popularmechanics.com 74%
latimes.com 72%
reuters.com 71%
bid request
fakesite123.com
esquire.com
passes blacklist
passes whitelist
✅
✅
declared
1. fakesite123.com has to pretend
to be esquire.com to get bids;
2. fraud measurement shows high
IVT b/c it is measuring the fake
site with fake traffic
3. Fake esquire.com gets mixed with
real so average fraud rates
appear high.
4. Real esquire.com gets backlisted;
bad guy moves on to another
domain.

15. November 2018 / Page 14marketing.scienceconsulting group, inc.
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How much of their tags are blocked?
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

16. November 2018 / Page 15marketing.scienceconsulting group, inc.
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Why is obvious fraud getting through
After fraud filters, obvious fraud is still impacting campaigns
Repeatedly loading slideshow pages—
log file data easily shows strange
behavior, like slideshow pages loaded
sequentially, or not sequentially
Site with 100% Android visitors—log file
data shows all devices were Android
8.0.0 and browsers were identical version

17. November 2018 / Page 16marketing.scienceconsulting group, inc.
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Why so many sellers offer valid traffic?
Many sellers of “traffic” say they get by all fraud detection filters
Choose Your “Traffic Quality Level”
“Valid traffic” goes
for higher prices
Source: Shailin Dhar

18. November 2018 / Page 17marketing.scienceconsulting group, inc.
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Why are bots still getting through?
Launch Week 3 and beyondWeek 2
Initial baseline
measurement
Measurement after
first optimization
After eliminating several
“problematic” networks
Obvious bots still
get through

19. November 2018 / Page 18marketing.scienceconsulting group, inc.
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After all flavors of“fraud filters”
Obvious fraud still
gets through (90-
100% win rates);
but we turned off
manually early in
the campaign

20. November 2018 / Page 19marketing.scienceconsulting group, inc.
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declared to be:
How does brand safety tech work?
They cannot read the content of the site with tags that are in ads
Pre-scanned Domain List
In-ad tag
Ad tags that are in the foreign
iframe (different domain) cannot
look outside the iframe – i.e.
cannot read content on the site
to determine brand safety.
bad word
porn
terrorism
hate
badsite123.com
badsite123.com
badsite123.com
badsite123.com
goodsite123.com
goodsite123.com
goodsite123.com
Domain Placement Reports
goodsite123.com
goodsite123.com
goodsite123.com
goodsite123.com
goodsite123.com
goodsite123.com
goodsite123.com
FAILS because it is not directly
measured; relies on domain placement
reports which have declared data.

21. November 2018 / Page 20marketing.scienceconsulting group, inc.
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Why is “verified” no different than control
“Verified Bots”
“Verified Humans”
Control: No Targeting
+$0.25 data CPM
+$0.25 data CPM
“verified bots” and “verified
humans” showed no difference in
quality to each other – AND both
were no different than the
control where no targeting
was used.

22. November 2018 / Page 21marketing.scienceconsulting group, inc.
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“Note that I did NOT recommend
asking them if they are ‘accredited’
or ‘certified against fraud’.”
(they all are, so their numbers
have gotta be right…. Right?)

23. November 2018 / Page 22marketing.scienceconsulting group, inc.
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“fight ad fraud with
common sense”
- stop wasting money on tech that
doesn’t work
- insist on detailed data and look at
the analytics yourself
Here are some ideas to get you started (Marketers’ Anti-Ad Fraud Playbook)
https://www.slideshare.net/augustinefou/b2c-marketers-anti-adfraud-playbook

24. November 2018 / Page 23marketing.scienceconsulting group, inc.
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About the Author

25. November 2018 / Page 24marketing.scienceconsulting group, inc.
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Dr. Augustine Fou – Anti-Ad Fraud Consultant
2013
2014
Published slide decks and posts:
http://www.slideshare.net/augustinefou/presentations
https://www.linkedin.com/today/author/augustinefou
2016
2015
2017

26. November 2018 / Page 25marketing.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.