State of Adblocking Update Q1 2016

The State of Adblocking Q1 2016

April 2016Augustine Fou, PhD.acfou [at] mktsci.com 212. 203 .7239

mailto:[email protected]

mailto:[email protected]

April 2016 / Page 2marketing.scienceconsulting group, inc.

linkedin.com/in/augustinefou

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 detected0 = adblock positively detected to be not present

(blank) = no detection, unmeasurable



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

http://www.iab.net/media/file/IAB_Internet_Advertising_Revenue_Report_FY_20142.pdf



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



Bot and Ad Block Detection Toolset



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

SAMPLE



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



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'



Highlights of Findings



Non-profitsNon-profit 1

Non-profit 3

Non-profit 2 Adblocking3% 12%

Mobile4% 12%

Unmeasurable8% 19%

8%

10%

6% 19%

Desktop

MobileDesktop

• 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



University websitesUniversity 1

University 3

University 2 Adblocking7% 19%

Mobile7% 16%

Unmeasurable5% 10%

15%

14%

10% 18%

Desktop

MobileDesktop

• 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



Publishers – ad supportedPublisher 1

Publisher 3

Publisher 2Adblocking

12% 27%

Mobile12% 33%

Unmeasurable5% 8%

20%

28%

6% 14%

Desktop

MobileDesktop

• 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



Tech and GamingSite 1

Site 3

Site 2 Adblocking9% 33%

Mobile3% 42%

Unmeasurable3% 16%

27%

35%

7% 18%

Desktop

MobileDesktop

• Tech savvy visitors to these sites have the highest measured ad blocking rates

• Unmeasurable rate is similar between desktop and mobile



How ad block measurement tools may undercount true rate

Javascript measurement tags NOT LOADED

high22%17%

21%

DIRECTLY MEASURED Ad Blocking Rate

low

average

Javascript measurement tags loaded

8% 17%

True rate of the use of ad blocking39%

Some ad tags and javascript measurement tags are now being blocked -- i.e. unmeasurable

unmeasurable



About the Author



Dr. Augustine Fou – Recognized Expert on Ad Fraud

2013

2014

2015SPEAKING ENGAGEMENTS / PANELS4A’s Webinar on Ad Fraud – October Digital Ad Fraud Podcast – JanuaryProgrammatic Ad Fraud Webinar – MarchAdCouncil Webinar on Ad Fraud - AprilTelX Marketplace Live – JuneARF Audience Measurement – JuneIAB Webinar on Ad Fraud / Botnets - September



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.