State of Adblocking Update Q1 2016
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The document discusses the prevalence of ad blocking, noting that it impacts up to 86% of digital ad spend, affecting display, video, mobile, and even search ads. It highlights variations in ad blocking rates across different demographics and types of websites, emphasizing that tech-savvy audiences often exhibit higher ad blocking. Additionally, it describes the use of a JavaScript measurement tool for detecting ad block rates, which may undercount actual usage due to certain tags being blocked.
![The State of Adblocking
Q1 2016
April 2016
Augustine Fou, PhD.
acfou [at] mktsci.com
212. 203 .7239](https://image.slidesharecdn.com/stateofadblockingupdateq12016-160402151324/85/State-of-Adblocking-Update-Q1-2016-1-320.jpg)
State of Adblocking Update Q1 2016
- 1. The State of Adblocking Q1 2016 April 2016 Augustine Fou, PhD. acfou [at] mktsci.com 212. 203 .7239
- 2. April 2016 / Page 1marketing.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 detected 0 = adblock positively detected to be not present (blank) = no detection, unmeasurable
- 3. April 2016 / Page 2marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou 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
- 4. April 2016 / Page 3marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou 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
- 5. April 2016 / Page 4marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Bot and Ad Block Detection Toolset
- 6. April 2016 / Page 5marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou 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
- 7. April 2016 / Page 6marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou 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
- 8. April 2016 / Page 7marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou 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'
- 9. April 2016 / Page 8marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Highlights of Findings
- 10. April 2016 / Page 9marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou 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
- 11. April 2016 / Page 10marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou 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
- 12. April 2016 / Page 11marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou 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
- 13. April 2016 / Page 12marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou 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
- 14. April 2016 / Page 13marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou 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
- 15. April 2016 / Page 14marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou About the Author
- 16. April 2016 / Page 15marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou 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
- 17. April 2016 / Page 16marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou 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.