H2O World - Learning How Humans and Non-Humans Interact with Digital Ads
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This document discusses how Integral Ad Science helps brands ensure their marketing messages are effectively delivered to humans through digital advertising. It covers how the company detects and prevents non-human (bot) ad fraud using a combination of offline and streaming data processing. It also examines how to determine which human interaction metrics are meaningful, such as viewability versus length of ad exposure, through randomized testing and causal inference methods. The goal is to identify environments and metrics that maximize a brand's message being heard by humans.
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H2O World - Learning How Humans and Non-Humans Interact with Digital Ads
- 1. LEARNING HOW HUMANS AND NON-‐HUMANS INTERACT WITH DIGITAL ADS H2O World, November 10, 2015 Sergei Izrailev SVP, Data Science sergei@integralads.com
- 2. 1 • About Integral Ad Science - What we do - About our data - Tech stack • Non-‐Humans: Ad Fraud - Overview - DetecKon and prevenKon • Human InteracKon - Did anyone see the ad? - What metrics are important? - How can we help the brand’s message to be heard? H20 World, 11/10/2015 AGENDA
- 3. 2 DIGITAL ADVERTISING MARKETING MESSAGE “Right Offer” 1 AUDIENCE TARGETING “Right Person” 2 MEDIA PLACEMENT “Right Place” 3 CAUSAL IMPACT & USER ENGAGEMENT “ROI”
- 4. • Brand Safety - The brand is protected • Fraud DetecKon - You only pay for ads delivered to humans • Geo VerificaKon - The ads are delivered in the right market / region • Viewability - A person actually has a chance to see the ad and has the opportunity to engage WE HELP BRANDS ENSURE THEIR STORIES ARE HEARD 3 H20 World, 11/10/2015 ESTABLISH A BASELINE – AND GO BEYOND ELIMINATE ADS THAT HAVE NO CHANCE OF DELIVERING A MESSAGE
- 5. 4 • ReporKng - What happened • Blocking the ad from showing in bad places - Before it’s too late • TargeKng good environments - Before you buy • CreaKng and packaging good environments - Before you sell H20 World, 11/10/2015 HOW THE DATA IS USED
- 6. H20 World, 11/10/2015 5 DATA COLLECTION AND PROCESSING STACK
- 8. H20 World, 11/10/2015 7 AD FRAUD NEARLY ALL AD FRAUD IS CAUSED BY BOT ACTIVITY Ad Stacking Placing mulKple ads on top of one other in a single ad placement, with only the top ad in view Illegal Bots Compromised computers with breached security defenses conceded to a third party Pixel Stuffing Stuffing an enKre ad-‐ supported site into a 1x1 pixel AD
- 9. H20 World, 11/10/2015 8 FRAUD DETECTION facebook cnn ebay nothingtoseehere.com thisisnotabotnet.com
- 10. H20 World, 11/10/2015 9 FRAUD DETECTION facebook cnn ebay nothingtoseehere.com thisisnotabotnet.com
- 11. 10 • Offline data processing (Hadoop) - Batch models: flag machines and sites • Streaming data processing (Storm / Kaea) - Near real-‐Kme online models: flag machines • In-‐browser measurement - Real-‐Kme rules and models: flag impressions Combine all signals in real Kme to flag fraudulent impressions H20 World, 11/10/2015 FRAUD DETECTION COMBINATION
- 13. H20 World, 11/10/2015 12 SOME METRICS MAY BE MISLEADING MOUSE HOVER RATE
- 14. VIEWABILITY 13 H20 World, 11/10/2015
- 15. • How many Kmes the driver sees the billboard? • How ofen? • Is there enough Kme to read it? IS VIEWABILITY ALL THAT MATTERS? 14 H20 World, 11/10/2015 THE IMPORTANCE OF THE ENVIRONMENT
- 16. H20 World, 11/10/2015 15
- 17. H20 World, 11/10/2015 16
- 18. H20 World, 11/10/2015 17 HOW CAN ONE TELL IF A METRIC MATTERS? RANDOMIZED A/B TESTING IS GREAT Campaign AdPSA But sometimes… TreatmentControl
- 19. NATURAL EXPERIMENTS 18 H20 World, 11/10/2015 OBSERVATIONAL CAUSAL ESTIMATION versus bit.ly/ias-‐kdd15-‐causal
- 20. CAUSAL LIFT VS NUMBER AND LENGTH OF EXPOSURE 19 H20 World, 11/10/2015 RESULTS FOR A TELECOM CAMPAIGN 1 45 90 0 0.1 0.2 0.3 0.4 0.5 120756030155 N = 9 impressions Causallift Exposure time (sec) Causallift N impressions 1 5 10 Exposure = 15-30 secs 0 0.1 0.2 0.3 0.4 0.5
- 21. CAUSAL LIFT VS NUMBER AND LENGTH OF EXPOSURE 20 H20 World, 11/10/2015 RESULTS FOR A TELECOM CAMPAIGN
- 22. 21 • FighKng ad fraud is an ongoing challenge - Faster detecKon helps • We are able to tell which metrics are meaningful - Causal inference is criKcal - Mouse hover rate is not a good measure of engagement - Viewability is important, but is not the ulKmate goal or means - Number and frequency of exposure mahers - Total exposure duraKon mahers - One long exposure doesn’t quite reach the goal H20 World, 11/10/2015 SUMMARY