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State of Ad Fraud Ad Blocking Q1 2016 Update Augustine Fou

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Digital ad fraud has not only NOT gone down; it has actually gone up in certain cases. There are some improvements when companies make special efforts. Ad blocking is also emerging as a threat.

Published in: Marketing
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State of Ad Fraud Ad Blocking Q1 2016 Update Augustine Fou

  1. 1. The State of Ad Fraud Q1 2016 Update April 2016 Augustine Fou, PhD. acfou [at] mktsci.com 212. 203 .7239
  2. 2. April 2016 / Page 1marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Executive Summary • Year-over-year, ad fraud has not improved overall; but individual companies see improvements with greater effort • Bots remain the key ingredient for all forms of ad fraud and their actions are polluting analytics, making them unreliable • Viewability standards are widespread now, but ad blocking has emerged as the new “crisis du jour” • Cybercriminals continue to easily avoid or defeat detection technologies because they cheat and don’t play by any rules • The proliferation of connected devices and IoT will increase the capabilities of bots and opportunity for ad fraud • 4D cybersecurity approaches are needed to fight ad fraud
  3. 3. April 2016 / Page 2marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Ad Fraud Background Update
  4. 4. April 2016 / Page 3marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Year-over-year fraud estimates continue to vary widely WhiteOps/DCN (Oct 2015)WhiteOps/ANA (Dec 2015) PublishersAdvertisers Average Bots 3% Range: 2% - 7% Average Bots 11% Range: 3% - 37% “there are industry average bot% and very wide ranges; but what really matters is the bot activity on YOUR site.”
  5. 5. April 2016 / Page 4marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Bad guys continue to focus on where the money is Impressions (CPM/CPV) Clicks (CPC) Search $18.8B $43 billion Display $7.9B Video $3.5B Mobile $6.2B$6.2B Leads (CPL) Sales (CPA) Lead Gen $2.0B Other $5.0B • classifieds • sponsorship • rich media estimated fraud not at risk (86% of digital spend - 2014)
  6. 6. April 2016 / Page 5marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Two main types of fraud have the same 2 key ingredients Impression (CPM) Fraud (includes mobile display, video ads) 1. Put up fake websites and load tons of ads on the pages Search Click (CPC) Fraud (includes mobile search ads) 2. Use bots to repeatedly load pages to generate fake ad impressions (hide the true origins to avoid detection) 1. Put up fake websites and participate in search networks 2. Use bots to type keywords to cause search ads to load and then to click on the ad to generate the CPC revenue (screenshots of fraud sites)
  7. 7. April 2016 / Page 6marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Bots are the cause of ALL automated ad fraud Headless Browsers Selenium PhantomJS Zombie.js SlimerJS Mobile Simulators 35 listed Bots are made from 1) malware compromised PCs or 2) headless browsers (no screen) in datacenters.
  8. 8. April 2016 / Page 7marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou “Ad fraud and ad blocking are now related because of bots”
  9. 9. April 2016 / Page 8marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Bots of all kinds do all kinds of fraud
  10. 10. April 2016 / Page 9marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Different kinds of bots create different kinds of fraud Malware (on PCs)Botnets (from datacenters) Toolbars (in-browser)Javascript (on webpages)
  11. 11. April 2016 / Page 10marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Bad guys’ (advanced) bots are not on any industry list 10,000 bots observed in the wild user-agents.org bad guys’ bots 3% Dstillery, Oct 9, 2014_ “findings from two independent third parties, Integral Ad Science and White Ops” 3.7% Rocket Fuel, Sep 22, 2014 “Forensiq results confirmed that ... only 3.72% of impressions categorized as high risk.” 2 - 3% comScore, Sep 26, 2014 “most campaigns have far less; more in the 2% to 3% range.” detect based on industry bot list “not on any list” disguised as normal browsers – Internet Explorer; constantly adapting to avoid detection
  12. 12. April 2016 / Page 11marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Advanced bots need to be detected differently Confirmed humans • found page via search • observed events (mouse click with coordinates) “Honest” (declared) bots • search engine crawlers • declare user agent honestly • observed to be 1 – 5% of websites’ traffic Fraud bots • come from data centers • malware compromised PCs • deliberately disguised user agent as normal browsers
  13. 13. April 2016 / Page 12marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Any device with a chip and internet can be used as a bot Traffic cameras turned into botnet (Engadget, Oct 2015) mobile devices webcams connected traffic lights connected cars thermostat connected fridge
  14. 14. April 2016 / Page 13marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Fraud Activities Mess Up Measurement
  15. 15. April 2016 / Page 14marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Bad guys hide fraud by passing fake parameters Click thru URL passing fake source “utm_source=msn” fake campaign “utm_campaign=Olay_Search” http://www.olay.com/skin-care- products/OlayPro- X?utm_source=msn&utm_medium= cpc&utm_campaign=Olay_Search_D esktop_Category+Interest+Product.P hrase&utm_term=eye%20cream&ut m_content=TZsrSzFz_eye%20cream_ p_2990456911
  16. 16. April 2016 / Page 15marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Bad guys fake KPIs, trick measurement systems Bad guys have higher CTR 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 average viewability.
  17. 17. April 2016 / Page 16marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Bad guys’ bots earn more money, more efficiently Cash out sitesCookie collecting Source: DataXu/DoubleVerify Webinar, April 2015 100 1x1 iFrames
  18. 18. April 2016 / Page 17marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Bad guys’ bots can fake quantity and quality metrics click on links load webpages tune bounce rate tune pages/visit
  19. 19. April 2016 / Page 18marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Turn off 1 ad network to cut out 90% bot traffic (red) • Bot volumes are flat across (red line at top; green volume bars at bottom) • Human traffic patterns are messy and irregular (blue line at top) • Dark red area decreased after we turned off a single bad ad network • Share blacklists through central data repository to increase impact
  20. 20. April 2016 / Page 19marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Google analytics view of traffic from single fraud domain Despite losing all of the traffic from these fake/fraud sites, there was no change to the number of pledges, during the same period of time. 102,231 sessions 0 sessions goal events – no change “ … because bots don’t make donations!”
  21. 21. April 2016 / Page 20marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou AppNexus example – cleaned up 92% of impressions Increased CPM prices by 800% Decreased impression volume by 92% “AppNexus aggressively detected and discarded fraudulent inventory; good for them and good for those who buy from them. This should be an example for publishers.” Source: http://adexchanger.com/ad-exchange-news/6-months-after-fraud-cleanup-appnexus-shares-effect-on-its-exchange/
  22. 22. April 2016 / Page 21marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou What normal (human) traffic patterns look like (5 + 2) • Notice the normal 5+2 pattern of weekday versus weekend traffic • Human traffic is lowest between 2a – 5a , because humans sleep • Bot volumes are now seen to be roughly tuned to human pattern 5 weekdays 5 weekdays (lower volume on 2 weekend days)
  23. 23. April 2016 / Page 22marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou End of month traffic and impressions fulfillment Traffic surge end of February Impressions surge on Feb 29th
  24. 24. April 2016 / Page 23marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Bad acting mobile apps and .xyz domains (abnormal CTRs) .xyz domainssuspicious mobile apps
  25. 25. April 2016 / Page 24marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Connection with Ad Blocking
  26. 26. April 2016 / Page 25marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Ad blocking impacts both CPM and CPC ads Ad blocking ONNo ad blocking Search Ads Display Ads
  27. 27. April 2016 / Page 26marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Humans use adblock, fraud bots don’t block ads Publisher 1 “We have long used ad block detection as a signal for human users because humans use adblock.” “Fraud bots that want the ads to load don’t block ads.” Note that we focus on the % of ads that successfully loaded, not blocked. 80 – 85% loaded is a good rule of thumb Publisher 2
  28. 28. April 2016 / Page 27marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou University websites (no ads) University 1 University 3 University 2
  29. 29. April 2016 / Page 28marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Tech and Gaming (tech savvy users) Site 1 Site 3 Site 2
  30. 30. April 2016 / Page 29marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Ad supported content sites see highest ad blocking rates Publisher 1 Publisher 3 Publisher 2
  31. 31. April 2016 / Page 30marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Recommended Actions
  32. 32. April 2016 / Page 31marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Debunk ALL assumptions and discard all averages • Ad Fraud / Bots • Ad Blocking • Measurement • Bots are low; list-based detection catches very little • Bots are malware on PCs; more and more from data centers • Bots are simple (cant fake clicks, mouse, scrolling); they do • Ad blocking is lower in mobile; mobile is less measurable • Ad blocking is higher among younger users; not necessarily • Ad blocking is still in the single digits; look at “ads served” • Higher CTRs are better; not if the clicks are fake • Higher viewability is better; not if the sites fake viewability • Data is reliable; not so if you don’t know bot/blocking levels
  33. 33. April 2016 / Page 32marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou About the Author
  34. 34. April 2016 / Page 33marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Dr. Augustine Fou – Recognized Expert on Ad Fraud 2013 2014 SPEAKING ENGAGEMENTS / PANELS 4A’s Webinar on Ad Fraud Digital Ad Fraud Podcast Programmatic Ad Fraud Webinar AdCouncil Webinar on Ad Fraud TelX Marketplace Live ARF Audience Measurement IAB Webinar on Ad Fraud / Botnets Publishers Forum 2015
  35. 35. April 2016 / Page 34marketing.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.

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