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Effectiveness of Digital Ads Q2 2017 Update by augustine fou

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“Before a single ad impression is shown, a third of every dollar goes to ad tech middlemen, in the very best scenario.”

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Effectiveness of Digital Ads Q2 2017 Update by augustine fou

  1. 1. Effectiveness of Digital Ads Q2 2017 Update July 2017 Augustine Fou, PhD. acfou [at] mktsci.com 212. 203 .7239
  2. 2. July 2017 / Page 1marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou “Before a single ad impression is shown, a third of every dollar goes to ad tech middlemen, in the very best scenario.” “Before a single ad impression is shown, a third of every dollar goes to ad tech middlemen, in the very best scenario.”
  3. 3. July 2017 / Page 2marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Programmatic Digital Ad Productivity Served ad impressions Not NHT 74% 26% Avg NHT “working digital media” fees, profit margin (ad tech, middlemen) 1/3rd 2/3rd “At the very best, only 60 cents of every dollar spent in digital media actually goes towards ‘working digital media’.” “productive digital ads” 59% not viewable 35% ad blocked Viewable 41% Not Blocked 10% confirmed humans 16%
  4. 4. July 2017 / Page 3marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Good Publisher Digital Ad Productivity 3% Avg NHT “working digital media” 100% “productive digital ads” 87% Served ad impressions Not NHT 97% confirmed humans 61% Viewable 91% Not Blocked 10% Not Viewable
  5. 5. July 2017 / Page 4marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Good Publishers vs Ad Exchanges 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.
  6. 6. July 2017 / Page 5marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou 60¢ per $1 left for “working digital media” “Supporting details confirm that for every $1 the advertiser spends, only 57 – 63 cents goes towards digital media.” “mark up” “working media” “working media” “mark up”
  7. 7. July 2017 / Page 6marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou NHT (bots) is night and day, so is humans Good Publisher Ad Exchange
  8. 8. July 2017 / Page 7marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Viewability by network type “Taking viewability as 50% of the pixels in view or greater, we can see statistically different rates of viewability by network.” Good Publishers Ad Networks Open Exchange 91% viewable 66% viewable 41% viewable
  9. 9. July 2017 / Page 8marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou “Naked Ad Calls” are bad on exchanges “Naked ad calls are ad impressions served without webpages” Good Publishers Exchange Media Bottom of Barrel 47% avg 77% avg 11% avg
  10. 10. July 2017 / Page 9marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Ad blocking on good publishers’ sites Marketing Science analyzed 1.5 billion pageviews and 3 billion ad impressions from 303 websites of mainstream publishers in the U.S. and Canada in June 2017. The data was directly measured with an embed code installed by publishers on their websites (on-page and in-ad). Mobile means mobile web; no in-app. The methodology includes the following: • On-page measurement – measured the users arriving on the page that had ad blocking turned on. • In-ad measurement – measured in the ad iframe – these would never be called if ad blocking were active; our data confirms good publishers do not call ads when ad blockers are on. • Portion of the data that could not be measured - on average 11% of the pageviews and 16% of the ad impressions could not be directly measured for ad blocking, and thus excluded. • Bots were scrubbed - on average, good publishers had 1 - 4% bots (NHT, IVT), which were scrubbed from the data. Bots do not block ads, humans do. Therefore for accuracy of the ad blocking measurement, bot traffic should not be counted, when reporting ad blocking rates. (range was 6 – 14% blocking)
  11. 11. July 2017 / Page 10marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou About the Author July 2017 Augustine Fou, PhD. acfou [@] mktsci.com 212. 203 .7239
  12. 12. July 2017 / Page 11marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Dr. Augustine Fou – Independent Ad Fraud Researcher 2013 2014 Follow me on LinkedIn (click) and on Twitter @acfou (click) Further reading: http://www.slideshare.net/augustinefou/presentations https://www.linkedin.com/today/author/augustinefou 2016 2015
  13. 13. July 2017 / Page 12marketing.scienceconsulting group, inc. linkedin.com/in/augustinefou Harvard Business Review 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.