what are things that performance marketers can do themselves to reduce their exposure to ad fraud? They dont need specialized verification tech; they just need to know where to look in their own analytics and what to look for. Here are some starting points.
1. November 2018 / Page 0marketing.scienceconsulting group, inc.
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B2B MARKETER’S
ANTI-AD FRAUD PLAYBOOK
Augustine Fou, PhD.
acfou [at] mktsci.com
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“Digital ad fraud is literally the
bad guys’ ATM – it spits out cash.
And every year $300 billion of
marketers’ digital ad budgets refills it.”
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Executive Summary
Marketers can take control and fight fraud with analytics/insights
1. B2B or “performance” marketers should not
assume they are immune to ad fraud. Bad guys use
tech to easily create clicks and trick performance
measurement and attribution.
2. Marketers can run one or more of the following
“plays” themselves without any specialized fraud
detection tech to see if they are exposed to fraud.
3. Each “play” tells marketers where to look and what
to look for in their own reports and analytics, so
they can take action when they find fraud.
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Despite fraud detection tech…
Obvious fraud still gets through; analyze and turn off the fraud
Launch Week 3 and beyondWeek 2
Initial baseline
measurement
Measurement after
first optimization
After turning off more “sites
that cheat”
30% bots
15% bots
3% bots
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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 per year)
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Bad guys avoid/ trick detection
Blocking of ad 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
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Anti-Fraud Playbook
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Measure Full-Funnel, Always
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
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Shift budgets to higher quality
Some channels have more humans, shift budget to these
• Blue means humans
• Red means bots
Where to find this?
Your own bots versus humans
measurement, with detailed
and complete supporting data.
What to look for?
Be sure to measure for both
bots and humans; rank order
channels, sources, or sites by
highest humans first.
What to do?
Some channels have more
humans (blue) and others have
more bots (red); shift budgets
during campaign to more
human channels.
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Very high click-thru rates
Click rates that are significantly higher than benchmark are suspect
Where to find this?
Any placement reports
from DSP, ad server, etc.
What to look for?
If display ad CTRs are
significantly above 0.1% it
should be investigated.
Also, if click rates are
identical from day to day,
something is strange.
What to do?
Identify the sites that
exhibit abnormally high
CTRs and turn them off.
Stop buying from them.
CTR Benchmarks over Years
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Click-thru rates by domain
Detailed reports by domain reveal obvious fraud
Where to find this?
Your campaign reports,
with details by domain.
What to look for?
If click-thru rates are 100%,
something is wrong; be
sure to ignore low volume
rows.
What to do?
Identify the sites that
exhibit these abnormal
click-thru rates and turn
them off in the campaign
interface – don’t buy the
fraud any more.
12. November 2018 / Page 11marketing.scienceconsulting group, inc.
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Abnormal traffic patterns
Humans sleep at night, visit sites during waking hours
Where to find this?
Hourly analytics reports
(e.g. Google Analytics, ad
server reports)
What to look for?
Are there normal
fluctuations in volume
(lower overnight, higher
daytime); if flat across,
then something is wrong.
What to do?
Identify the sites or
impressions that exhibit
abnormal patterns and
turn them off. Stop buying.
Abnormal – flat across
Normal daily fluctuations
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Abnormal data consistency
When analytics are TOO consistent, something is suspicious
top 4 referring sites – exact same pattern Where to find this?
Hourly analytics reports
(e.g. Google Analytics, ad
server reports)
What to look for?
If select parameters look
too similar across multiple
domains, that is suspicious
(e.g. same pages/session,
ultra low bounce rates,
99% Android visits).
What to do?
Identify the sites that
exhibit abnormal
consistency; investigate
further andd turn them off.
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Compare to organic benchmarks
Paid traffic characteristics benchmarked against organic traffic
Where to find this?
Your own analytics reports
What to look for?
Look at organic traffic
benchmarks (this tells you what
people do and how long they
stay). Compare your paid
channels to this benchmark.
What to do?
If your paid channels are
significantly different from your
organic, then something is
wrong. For example if display
ads show much higher bounce
rate, or much lower time on
site, something is suboptimal.
Paid channels
compare favorably
Paid channels don’t
compare favorably
15. November 2018 / Page 14marketing.scienceconsulting group, inc.
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Zero conversion sources
Zero conversions, no change when turned off; not worth spending
Where to find this?
Your own analytics reports
What to look for?
Be sure to select metrics that
are not quantity metrics that
are easily faked by bots; look for
large volume sites/referrers that
yield zero conversions
What to do?
Identify the sites that show zero
conversions; pause or turn off
ad spend and see if there is any
change to overall conversions or
conversion rate. If no change,
then leave off (it wasn’t driving
anything anyway).
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Display 4
2,036 humans
human conversion rate
Compare actual 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%
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About the Author
18. November 2018 / Page 17marketing.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