Adblocking is a hot topic and many groups are studying the levels of ad blocking and the growth trajectory. However there are many differences due to the measurement technologies and techniques and the assumptions that went into interpreting the data.

1. The State of Adblocking
Q1 2016
April 2016
Augustine Fou, PhD.
acfou [at] mktsci.com
212. 203 .7239

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Humans use adblock, fraud bots don’t block ads
Publisher 1
Challenge all assumptions
• Ad blocking on mobile is not necessarily
lower than desktop; lower numbers may
be due to incomplete detection
• Ad blocking ranges observed are from
single digit percentages to over 50%
• It is critical to disclose the portion of the
data that is not measurable (see the row
that has no value; “1” means ad block)
• Younger audiences do not always have
higher ad blocking
• Tech savvy gamers appear to have the
highest rates of ad blocking
“We have long used ad block detection
as a signal for human users because
humans use adblock. Bots used to
commit ad fraud don’t because they
want the ad impressions to load.”
1 = adblock positively detected
0 = adblock positively detected to be
not present
(blank) = no detection, unmeasurable

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UPDATED: Full Year Digital Ad Spend – $50B
Impressions
(CPM/CPV)
Clicks
(CPC)
Leads
(CPL)
Sales
(CPA)
Search 38%
$18.8B
Video 7%
$3.5B
Lead Gen 4%
$2.0B
10% Other
$5.0B
Source: IAB, FY 2014 Internet Advertising Report, May 2015
$42.5B
Display 16%
$7.9B
Mobile 25%
$6.2B$6.2B
CPM Performance
• classifieds
• sponsorship
• rich media
$7.0B

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Ad blocking impacts up to 86% of digital spend
Everyone knows ad blocking removes display, video, and
mobile ads, but did you know it also blocks search ads?
$42.5B of $50B may be impacted by ad blocking

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Bot and Ad Block Detection Toolset

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Detection Toolset – Javascript “tag”
• Uses standard javascript APIs
which are set and maintained
by W3C
• The javascript “tag” collects
details about the browser like
the version, the operating
system, screen resolution,
plugins, etc.
• No personally identifiable
information is collected
• Users don’t interact with it in
any way – does not log in,
enter any data
• The collected data points are
combined together to generate
anonymous “fingerprint”
• Cookies can be turned on and
off as necessary.
• Not all parameters are
collected for every visit

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Where we deploy our tag
In-ad (display ads served)On-site (clients’ websites)
• To detect and characterize
each visitor to the website
• Installed just like Google
Analytics via 2 lines of code
• Served in the ad creative in
order to characterize the user
that caused the ad to load

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Examples of common parameters collected
'time'
'window'
'appVersion'
'video'
'product'
'sessionStorage'
'localStorage'
'vendor'
'productSub'
'appCodeName'
'inner'
'cookieEnabled'
'appName'
'platform'
'timezone'
'cookies'
'language'
'doNotTrack'
'frame'
'hidden'
'outer'
'vendorSub'
'url'
'userAgent'
'fontrender'
'referrer'
'clock'
'sort'
'globals'
'TIMESTAMP'
'cookie'
'HTTP_USER_AGENT'
'HTTP_CONNECTION'
'HTTP_X_FORWARDED_FOR'
'HTTP_ACCEPT'
'HTTP_ACCEPT_LANGUAGE'
'GEO_LAT_0'
'GEO_LNG_0'
'GEO_CITY_0'
'GEO_REGION_0'
'GEO_COUNTRY_0'
'GEO_IP_0'
'GEO_AS_0'
'HTTP_ACCEPT_ENCODING'
'devicelight'
'document'
'framerate'
'plugins'
'HTTP_REFERER'
'orientation'
'HTTP_COOKIE'
'motion'
'mousemove'
'HTTP_DNT'
'scroll'
'custom_site'
'custom_campaign'
'custom_advertiser'
'custom_IO'
'custom_placement'
'custom_creative'
'custom_adunit'
'custom_section'
'HTTP_CACHE_CONTROL'
'mousedown'
'mouseup'
'click'
'touchstart'
'HTTP_UA_CPU'
'touchend'
'touchmove'
'HTTP_VIA'
'HTTP_X_WAP_PROFILE'
'HTTP_X_REQUESTED_WITH'
'HTTP_ACCEPT_CHARSET'
'HTTP_X_UIDH'
'keydown'
'keyup'
'touchcancel'
'GEO_LNG_1'
'GEO_IP_1'
'GEO_AS_1'
'GEO_COUNTRY_1'
'GEO_REGION_1'
'GEO_CITY_1'
'GEO_LAT_1'
'HTTP_X_ATT_DEVICEID'
'HTTP_X_BLUECOAT_VIA'
'keypress'
'HTTP_PRAGMA'
'HTTP_DEVICE_STOCK_UA’
'clicktype'
'HTTP_X_IMFORWARDS'
'HTTP_FORWARDED'
'HTTP_CLIENT_IP'
'HTTP_X_GETZIP'
'HTTP_X_OPERAMINI_PHONE_UA'
'HTTP_X_OPERAMINI_PHONE'
'HTTP_X_OPERAMINI_FEATURES'
'GEO_AS_2'
'HTTP_SCHEME'
'GEO_IP_2'
'GEO_COUNTRY_2'
'GEO_REGION_2'
'GEO_CITY_2'
'GEO_LNG_2'
'GEO_LAT_2'
'"frame'
'HTTP_X_P2P_PEERDIST'
'"clock'
'"document'
'HTTP_XROXY_CONNECTION'
'HTTP_PREFER'
'"devicelight'
'"scroll'
'HTTP_PROXY_CONNECTION'
'select'
'HTTP_CONTENT_SUPORT'
'HTTP_X_REAL_IP'
'HTTP_X_NETWORK_TYPE'
'"framerate'
'"mousemove'
'HTTP_X_BROWSER_TYPE'
'HTTP_X_NOKIA_DEVICE_TYPE'
'HTTP_X_MOBILE_GATEWAY'
'HTTP_X_COUNTRY_CODE'
'"globals'
'HTTP_CLIENTIP'
'HTTP_VERSION'
'"plugins'
'"touchend'
'noscript'

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Highlights of Findings

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Non-profits
Non-profit 1
Non-profit 3
Non-profit 2 Adblocking
3% 12%
Mobile
4% 12%
Unmeasurable
8% 19%
8%
10%
6% 19%
Desktop
Mobile
Desktop
• Non-profit sites that carry no advertising show
relatively modest ad blocking rates
• The rate of unmeasurable visits are very
similar comparing desktop versus mobile

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University websites
University 1
University 3
University 2 Adblocking
7% 19%
Mobile
7% 16%
Unmeasurable
5% 10%
15%
14%
10% 18%
Desktop
Mobile
Desktop
• Desktop and mobile adblocking is similar
• Unmeasurable rate is higher in mobile
• Younger audiences don’t necessarily have
higher ad blocking than general population
• A third of visitors to websites are using mobile

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Publishers – ad supported
Publisher 1
Publisher 3
Publisher 2
Adblocking
12% 27%
Mobile
12% 33%
Unmeasurable
5% 8%
20%
28%
6% 14%
Desktop
Mobile
Desktop
• Visitors to publishers that are ad supported
show higher ad blocking rates (than university
and non-profit sites that are not ad supported)
• Mobile users appear to have higher ad
blocking rates
• Mobile is also more unmeasurable

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Tech and Gaming
Site 1
Site 3
Site 2 Adblocking
9% 33%
Mobile
3% 42%
Unmeasurable
3% 16%
27%
35%
7% 18%
Desktop
Mobile
Desktop
• Tech savvy visitors to these sites have the
highest measured ad blocking rates
• Unmeasurable rate is similar between desktop
and mobile

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How ad block measurement tools may undercount true rate
Javascript measurement tags
NOT LOADED
high
22%17%
21%
DIRECTLY MEASURED Ad Blocking Rate
low
average
Javascript measurement tags
loaded
8% 17%
True rate of the use of ad blocking
39%
Some ad tags and javascript measurement tags are now being blocked -- i.e. unmeasurable
unmeasurable

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About the Author

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Dr. Augustine Fou – Recognized Expert on Ad Fraud
2013
2014
2015
SPEAKING ENGAGEMENTS / PANELS
4A’s Webinar on Ad Fraud – October
Digital Ad Fraud Podcast – January
Programmatic Ad Fraud Webinar – March
AdCouncil Webinar on Ad Fraud - April
TelX Marketplace Live – June
ARF Audience Measurement – June
IAB Webinar on Ad Fraud / Botnets - September

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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.