Ad fraud update for publishers Feb 2020

February 2020 / Page 0marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Update on Digital
Ad Fraud
February 2020
Augustine Fou, PhD.
acfou [at] mktsci.com
212. 203 .7239

Local news killed by fake news
Local news sites relied on ad revenue; fake sites stole ad budgets
McClatchy Bankruptcy 1,300 local news “deserts”2,000 newspapers died

Fake news feeds on ad dollars
Fake local news sites tricked users, committed ad fraud for years
Discovery of Fake Sites
fake local news sites

How did it get this bad?

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.

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

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

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

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

Badtech Tax: 60-70% extracted
Source: WFA, April 2017
Source: ANA, May 2017

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/

Bad for Publishers; also
Bad for Advertisers

(2015) AppNexus purged 92% of ads
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

(2018) Lotame purges 400M bots
“[LOTAME] purged 400
million of its over 4
billion profiles after
identifying them as
bots or otherwise
fraudulent accounts.
Lotame CEO Andy
Monfried estimated
that 40 percent of all
web traffic is
fictional.”
Adweek, Feb 2018

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)

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

Uber: cut 80%, no change
• Uber cut $120M from $150M, signups remained steady; paid
signups dropped, and organic signups increased to replace it.
• Uber sued 100 mobile exchanges for falsifying placement
reports and fabricating transparency reports.

Good Publishers

Long-term Consistency
Great consistency in the data; confirmed humans (blue), low bots

Known bots coming to site
Declared (orange), search (yellow), other bots can be identified

Search crawlers are 5-10%
Search engine crawlers (yellow) can account for 5-10% of traffic

Good Publishers Don’t
Have a Privacy Problem

1st Party … now “badtech”
“Then” 1995 “Now” 2015
Real human audiences who
came to your site – 1st party
“badtech” trackers hidden from
user, tracking w/o consent

Audiences stolen by badtech
specialized audience:
oncologists
jco.ascopubs.org
specialized audience can
be targeted elsewhere
“cookie matching”
(by placing javascript on your site)

Human audiences are
scarce and valuable

You get what you pay for ...
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.

Good Publishers vs “Badtech”
Ad Exchange Good Publisher Take-Away
Left after
Fees
60% 100% When buyers buy direct from publisher, 100%
of every dollar goes towards “working media”
Not Bots 74%
(avg NHT 26%)
97%
(avg NHT 3%)
Not bots, but doesn’t necessarily mean
humans. Buy direct from good publishers,
rather than use fraud detection tech to clean
up afterward.
Viewable 41% 91% Viewability is generally much higher in good
pubs than sites that belong to exchanges.
Not Ad
Blocked
80%
(avg 20% blocked)
100% Good publishers don’t call ads when ad is
active. This is confirmed when measuring in-ad.
Confirmed
Humans
16% 61% Good publishers have real content that real
humans want to read; so they have human
audiences. Also bots can’t make money going
there.
Productivity
of Ads
2% 54%
Buying from good publishers means your
dollar goes at least 27X further than buying
from programmatic sources. This is BEFORE
targeting and ad effectiveness.

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

Widely different relative quality
Campaign 1
• Blue means humans
• Red means bots Campaign 2
“increase spend on sources driving more humans
(blue); reduce spend on sources with more bots (red)”

Display 4
2,036 humans
human conversion rate
More humans = more outcomes
Site Traffic Conversions
8,482 818
4,216 humans
5%
14,539 193
225 humans
9%
2,248 23
168 humans
5%
1,527 9
Display 3
Display 2
Display 1
Humans
40%

Risks for Publishers

Badtech extracts 40-60%
Source: WFA, April 2017
Source: ANA, May 2017

Audiences stolen by badtech
specialized audience:
oncologists
jco.ascopubs.org
specialized audience can
be targeted elsewhere
“cookie matching”
(by placing javascript on your site)

New risk of ad fraud - spoofing
Because… “Bad guys must pretend to be
good sites (by passing domain into bid
request) in order to get bids.”
publisherA.com
What portion of
the inventory is
real? vs spoofed
If you sell on exchanges, bad guys can pretend to
be your domain and steal ad dollars from you.

Lower CPMs, MORE unsold
“How can you maintain $10 CPMs on your site
when buyers know they can get ads on your
site by buying it on exchanges for $1 CPMs?
They will wait till it goes
remnant, and then buy it.
You are CAUSING more inventory to go unsold.

Users’ privacy being violated
Source: https://freedom-to-tinker.com/2017/11/15/no-boundaries-exfiltration-of-personal-data-by-session-replay-scripts/
“Exfiltration of personal
data by session-replay
scripts; and recording of
user actions on the site.”

Selling on viewable impressions
Hypothesis:
Make more money selling
viewable impressions
Reality:
• Sellers cut their own sellable
inventory significantly
• Buyers are using viewability
rates to get refunds, rarely paid
more to publishers in reality
• Viewability measurement may
be wrong and not verifiable or
transparent
• Only bad guys have 100%
viewability all the time; buyers
shift dollars to them
Bad guys have higher viewability
AD
Bad guys stack
ads above the
fold to fake
100% viewability
Good guys have to
array ads on the
page – e.g. lower
sitewide average
viewability.
Dec 2017, Digiday: Publishers are underwhelmed by the payoff from hitting viewability standards

Malware ads hijack users
Malicious javascript can break out of ad
iframe -- take over the page, redirect user
Source: https://digiday.com/media/every-vendor-
problem-website-redirects-keep-plaguing-publishers/
Source: https://blog.confiant.com/nov-22-25-
attack-of-the-cyber-turkey-7a57a1ed498f

Pubs wrongly accused of IVT
Good publishers are blacklisted while bad guys continue fraud
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.

What Good Publishers
Are Doing

Good publishers protect users
42 trackers
24.3s load time
8 trackers
1.3s load time
“minimize 3rd party javascript trackers on pages”

Good publisher, progressively cleaning
10% red
3% red
“Filter GIVT and data centers; don’t call ads”
27% red
17% red
-7%
-10%
On-Site measurement
In-Ad measurement
Filter applied Stopped buying traffic

“New Deal” – balances 3 parties
Good Publishers
(higher CPMs, revenue)
Consumers
(privacy respected)
Advertisers
(business outcomes)

“For years, publishers have been convinced
by badtech – aka “ad tech” – that there
were vast new riches to me made with
their tech …
… but the reality is publishers have seen
revenue decline, lower CPMs, audience
dilution, and new risks like ad fraud.”

Questions to Ask
• Has the revenue from programmatic matched
the promises?
• Do the compliance and regulatory risks
(violating your users’ privacy, GDPR/CCPA)
justify continuing letting adtech on the sites?
• How do you develop better relationships with
your audience and your advertisers?

Extorting publishers openly
Scammers threaten to
flood a publisher’s site
with easily detectable
bad traffic to cause
Google to reduce ad
volume or ban the
domain, or withhold
payment, unless
publisher pays ransom
in bitcoin.
https://www.engadget.com/2020/02/18/google-adsense-
extortion-bad-traffic-ban-ads/

About the Author

Dr. Augustine Fou – Digital Marketer
2013
2014
Published slide decks and posts:
http://www.slideshare.net/augustinefou/presentations
https://www.linkedin.com/today/author/augustinefou
2016
2015
2017

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