Iab bots how to_find_them_webinar_2014_03_27


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Iab bots how to_find_them_webinar_2014_03_27

  1. 1. Bots: How to Find Them & Keep Them Out of Digital Advertising
  2. 2. Questions? Attendees should ask questions by typing into the Question box on the GoToWebinar user interface at any time during the presentations. – We will create a queue and answer as many questions as possible following the presentations. – Additional questions should be directed to Nicole Horsford, Nicole@iab.net
  3. 3. Agenda  Setting the Stage  Speakers ● Marvin Hidalgo Senior Product Manager, Integral Ad Science ● Vamshi Sriperumbudur VP of Platform Marketing, Yume ● Elizabeth Cowley VP Global Partnerships, Viewster  Open Discussion / Q&A
  4. 4. Marvin Hidalgo Senior Product Manager
  5. 5. What Are Bots? Bots noun ˈbäts a device or piece of software that can execute commands, reply to messages, or perform routine tasks, or problem routine tasks with minimum human intervention Illegal bots noun (ˈ)i(l)-ˈlē-gəlˈbäts computers that are compromised and whose security defenses have been breached and control conceded to a third party Botnet: noun ˈbät net a collection of bots communicating with command center in order to perform tasks
  6. 6. Fraud: Why Does It Take Place? • Supply and Demand • Because of the way that we buy media: • Eyeballs (CPM) • Action Taken (CPC, CPA) • Because it’s easy for hackers
  7. 7. Who Are the Participants? Profile Hacker: Sex: Male Age:18-35 Location: Eastern Europe, Asia Background: good computer skills BotnetOperator: Sex: Male Age: 34+ Location:Eastern Europe Characteristics:Disregard to law, confident,driven by money TypicalInfected Computer Owner: Technologicallychallenged Owns a dated computer and software Suburban,rural, household without kids Unlikelyto own a smart phone/tablet
  8. 8. How are Bots Detected ? First we look at behavioral patterns We flag the following un-human signals: Cookies that are deleted at the end of activity cycle Intense activity Reoccurring activities patterns/levels At this point: some bots are detected, others are able to go undetected Next – we look at each impression • Signals that are untypical for human • Density of page loads • Density of page visits • Untypical distribution of browsers • Browser spoofing • Conflicting measurement results • Was the impression traded in a suspicious way Cross validate all of the above and determine validity of signals and patterns Bot …or not
  9. 9. How do Publisher’s approach Fraud? Proactive Passive Pretend the problem doesn’t exist Knowingly or unknowingly sell bot traffic Able to eliminate some of the bot traffic Eliminate most to all bot traffic Partially address the problem: • Use a subpar list based solution • Run the technology only on part of the inventory Are serious about fraud: • Use cutting edge technology to vet 100% of inventory
  10. 10. Vamshi Sriperumbudur VP of Platform Marketing
  11. 11. Ad Industry | Market Opportunity $517 $544 $568 $596 $117 $132 $146 $160 2013 2014 2015 2016 Global Ad Spend (in billions) Total Ad Spend Total Digital Spend $171 $179 $188 $198 $42 $50 $57 $65 2013 2014 2015 2016 US Ad Spend (in billions) Total Ad Spend Total Digital Spend Source: eMarketer, Dec. 2013 & Mar. 2014 reports
  12. 12. 44% 42% 51% 61% 0% 10% 20% 30% 40% 50% 60% 70% Q1 Q2 Q3 Q4 19% 22% 27% 25% Q1 Q2 Q3 Q4 Ad Industry | Challenges Non-human Mobile Activity Non-human Web Activity 2013 Source: Solve Media, Mar. 2014 2013 US Non-human Traffic – Online & Mobile Challenge: In 2013, non-human Online Activity in US grew 40% & non-human Mobile Activity grew 30% Solution: Publishers and Advertisers should prioritize investments in anti-fraud technologies CTV platform needs review
  13. 13. Traffic Quality Solutions Viewability Tracking and measuring ad positions on publisher pages and properties Fraud Detection Monitoring of non-human traffic resulting from traffic fraud designed to manipulate ad-serving counts Brand Safety Consideration of the content quality and context that appears next to the ad
  14. 14. Solutions | Viewability At least 50% of the ad is visible on the users screen for at least 1 second Above the fold View Area Width x Height Player Width x Height 3 Player Location 3 4 View Area 4 2 Player Size 2 5 No auto-play 5 1 Minimum Player Visibility 1
  15. 15. Solutions | Fraud Detection 1. Diligent evaluation of every publisher before adding to the network to make sure they meet the standards 2. SDK / Process for Placement Quality – Algorithms to grade value of each video ad impression and assign quality score. Fraud detection capabilities to address: • Click Fraud (bots browse/click on bogus & legit sites) • Impression Scams (bogus ad requests) • Ad Stacking (stacked muted auto-play ads behind in- view video ad) • Ad Clutter (multiple ads in close proximity) 3. SDK & Data – Machine learning for mimicking human behavior to downgrade fraudulent inventory 4. SDK & Surveys – First-party audience survey response rate to gauge inventory quality 5. Partnerships with right vendors who specialize in fraud detection
  16. 16. Publisher Site Domain blacklisted Player not in view Safe domain, player in-view Additionally, review every site/app of a Publisher and their syndication partners:  Only click-to-play or user initiated video ad playback  No skip button for 15 or 30s ads  No muted audio  Post-rolls after video content not acceptable Publisher Syndicated Sites Solutions | Brand Safety 2 Context 2 1 Content 1
  17. 17. Solutions | YuMe in The Press “YuMe wants to ensure that there's a human behind every impression. These improvements to our fraud detection system and PQI, combined with our newly-launched anti-spam best practices, will provide an essential layer of comfort for those planning media buys or monetizing ad inventory.” - Jayant Kadambi, CEO & Co-Founder, YuMe According to Radar Research, up to 50 percent of all ad impressions are never seen by the intended audience. Inclusion of unseen impressions in campaign reporting results in inaccurate metrics. This industry-first capability allows YuMe to prevent ads from running in video players that have been embedded on inappropriate websites, and to work with publishers to constantly monitor and improve the list of sites where their syndicated and user- embeddable players are appearing. Oct 2013 Nov 2011 Jun 2010
  18. 18. Elizabeth Cowley VP Global Partnerships
  19. 19. What is Viewster? Founded in 2007 & HQ: Zurich, Switzerland with offices in US, UK, & Australia VOD Service with focus on TV and Movie content Available globally in 10 languages on PC and 1M connected devices # 18 US Video Content Provider by comScore reaching 18M unique visitors/month
  20. 20. Flavors of Bad Traffic •Non-Human Traffic – bots •Human but not Viewable Traffic – hidden iFrames “<iframe src=‘http://StealBrandMoney.com style=‘visibility:hidden;position:absolute;left0;top0;’></iframe>” •Human & Viewable Traffic - Fraudulent Arbitrage – Browser Plug Ins Spoof URL – In-banner sold as onsite – Multiple Players on same page – Ads run in pop-under pages – Ads auto-start BTF Buyer is sold… But gets this
  21. 21. Bad Traffic Ecosystem Fraudsters sell bad Traffic Because they can – Buyer metrics are fakable. Bad traffic hits the market and real publishers with real video [and real associated costs] are forced to compete with fake traffic that has no content cost. Real publishers look to buy affordable traffic to compete Bad Traffic enters the marketplace DIRECTLY through exchanges & lower-end adnets. It can then be laundered and sold as premium. INDIRECTLY through legit publishers buying traffic to compete.
  22. 22. Removing Bad Traffic from the Marketplace Stop Buying It! Publishers, AdNets and AdExchanges need to stop buying bad traffic. Brands Can Help Too •Brands should expect to pay a decent price for decent inventory and a high price for premium inventory. •Buyers should consider campaign metrics tied to human activity. – Increased brand recognition – Increased sales – Hijack device camera to confirm eyeball on ad? [just kidding…]
  23. 23. How to Spot Bad Traffic • Before Buying – Is the price unreasonably low? – Check Alexa Rank – does the site have real traffic? – Check referring URLs in Alexa – lets you know where the traffic’s traffic is coming from? – Check against known offenders list • Run Test Campaign – Manual checks to verify placement – 3rd Party Traffic Verification such as IAS, Adometry or similar – 3rd Party Viewability Tool such as OpenVV • After Buying – Don’t fall for a bait & switch. Continue to monitor manually and via 3rd party technologies. Do not underestimate the value of a relationship between buyer and seller.
  24. 24. Publisher Challenges with 3rd Party Verification Tools Publisher Traffic GOOD BAD Publishers need actionable data not just a verdict of good or bad. A good step would be if 3rd party verification technologies would work with publishers to determine where their algorithms are producing data useful to buyers and where it is not. There is no standard for “good” or “viewable” traffic therefore technologies do not agree with one another.
  25. 25. IAB 3MS Initiative “Making Measurement Make Sense” – intended standardize digital media metrics and promote shift from gross “served” impressions to audience-based “viewed” impressions (50% viewable for a minimum of 1 second). IAB Safe Frame 1.0 Initiative Open source iframe code that removes browser-type restrictions on the geometric approach and enables the same level of verification coverage as browser optimization approach. TOGI Task Force “Traffic of Good Intent” task force created to address bad traffic. Industry Best Practice Initiatives
  26. 26. Brendan Riordan-Butterworth Director, Technical Standards Marvin Hidalgo Senior Product Manager Open Discussion / Q&A Elizabeth Cowley VP Global Partnerships Vamshi Sriperumbudur VP of Platform Marketing