Next-Generation Campaign Section Title Validation & Optimization


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A Sprint Case Study

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  • To get some market reaction, we introduced a charter program of some really large advertisers.We were delighted by the response to the program, and let me take the opportunity to say to them, Thanks you for participatingNow let us talk about what we learned.
  • Prior to the introduction of vCE, there hasn’t been a proven standard technology in the marketplace that could measure all three types of iframes to get a complete read of visibilityMeasuring the first two – directly on the site iframes and friendly iframes is relatively easy, and there have been solutions for these. However, unfriendly iframes, or cross domain iframes, are hard to measure in terms of location on the screen. Unfortunately, a large percent of ads are delivered this way, meaning that missing this piece of the equation, means not covering the entire story. vCE accounts for ALL THREE providing insight into total visibility.
  • Difference of in-view rates between Top 50 sites and long tail sites in their category was a full 16-percentage points in the USEuropean Results:Top 50                  66%Top 100                63%Top 500                61%501+                    55% The only minor difference with the US is that we’ve taken the full range of sites rather than just a category We had half the publisher volume we saw in the US, and a lot have very small numbers of impressions which, when visible, skew upwards the long tail visibility average.  The overall data set tells the best story and is most consistent with the original US slide.
  • To clarify, being in-view has nothing to do with being above or below the fold. In fact, there are some myths the charter study helped to debunk. For some campaigns less than half of the above the fold placements where actually seen.
  • On the other hand some placements below the fold where in almost 70% of the time.
  • Next-Generation Campaign Section Title Validation & Optimization

    1. 1. Next-Generation Campaign Section Title Validation & Optimization: A Sprint Case Study
    2. 2. In 2007, comScore’s First Post-Buy Analysis Across 8 Digital US Campaigns Showed Execution Left a Lot to be Desired … 70% Percent of Ad Impressions for 8 Campaigns 60% 50% 40% 30% 61% 20% 10% 19% 8% 12% 0% In US But Not Target Hit Target Hit Target Outside US Frequency >=5 Frequency <=4
    3. 3. Branding advertisers on TV are accustomed to audience guarantees and expect the same in digital Accuracy of cookie-based digital plan delivery is problematic: Cookie Deletion Cookie Proliferation X Cookies Are Not People Source: comScore 2011
    4. 4. Some Things We’ve Learned About Digital Media Plan Delivery• The negative impact of cookie deletion – Cookie deletion inflates ad frequency and deflates ad reach by as much as a factor of 2.5X• Targeting accuracy using cookies: – 70% for 1 demo (e.g. women) – 48% for 2 demos (e.g. women age 18-34) – 11% for 3 demos (e.g. women age 18-34 with kids) – 36% for behavioral targeting (e.g. people visiting travel sites)
    5. 5. Cookies Can’t Accurately Identify Who is Using a Computer at any Given Point in Time due to Multiple Users Over 64% of home users share a computer with other users 3+ users 1 user 32% of the36% 30% time, someone other than the Facebook logged-in person is actually using the 2 users computer 32%
    6. 6. Cookie Deletion is a Global Reality …and a Global Challenge Accurately counting reach with cookies is not possible,yet is currently the method used in most ad servers and analytics systems Ad Server Cookies Percent of Average # of cookies Country computers deleting per computer for same campaign Australia 37% 5.7 Brazil 40% 6.6 U.K. 35% 5.9 U.S. 35% 5.4
    7. 7. Arguably the Most Important Digital Advertising Initiative To Date: Making Measurement Make Sense (3MS) Mission  Reduce costs of doing business due to complexity of digital advertising ecosystem  ‘Single Tag’ solution to reduce complexity  Improve reporting of ad exposure  Bolster confidence that ads delivered are actually visible
    8. 8. What is a vGRP?• validated Gross Rating Points (GRP) based on validated impressions delivered to the Total Census Population for selected Geographic Market, or 100 * % Pop Reach * Average Frequency for the reporting period• Comparable to GRPs used in television because it used the same calculations• vGRPs must: – Deliver in the target geography – Not be fraudulent deliveries – Be in brand safe content – Be viewable – Hit the target audience
    9. 9. vGRP can provide more accurate analysis of campaign effectiveness in Marketing Mix Models GRP: Negative vGRP: Positive Correlation Correlation100 80 100 8 90 90 70 7 80 80 60 6 70 70 vGRP GRP 50 5 60 60 Sales Sales 50 40 50 4 40 40 30 3 30 30 20 2 20 20 10 1 10 10 0 0 0 0 Month 1 Month 2 Month 1 Month 2
    11. 11. vCE US Charter Study:12 Major Branded Advertisers Came Together to Lead & Learn 18 campaigns 2 billion impressions 400,000 sites Allstate
    12. 12. Charter Study replicated in Europe with similar results 15 campaigns 640 million impressions 213,000 sites
    13. 13. Study ObjectiveQuantify incidence of sub-optimal ad delivery across key ad delivery dimensions…… to better understand sources of waste and identifyopportunities to extract more value for all players in the onlineadvertising ecosystem
    14. 14. Importantly, all impressions in the study weredelivered in iframes, including the notoriously difficult- to-measure cross-domain iframes Directory on site Same-domain iframe Cross-domain iframe (friendly) (un-friendly) ad ad ad web web web site site site 61+% of iframed ads use this method
    15. 15. Across all campaigns, the average in-view rate was 69%, meaning 3 out of 10 ads weren’t seen Percentage of Ads In-View by Campaign
    16. 16. vCE Charter Study:In-View Rates Need to Be Improved US EU 69% 67%AVERAGE AVERAGECampaign In-View ad rates ranged from:US 55% to 93% EU 64% to 72%
    17. 17. In-view rates by site ranged from 7% to100%, suggesting the importance of validation across all sites Percentage of Ads In-View by Site
    18. 18. Large sites scored better than long-tail sites Percentage of Ads Served In-View 77% 74% 70% 61% 66% 63% 61% 55% US EU
    19. 19. The Classic Leaderboard delivered the strongest in-view rates but there was significant variance across all sites with a range of 7% to 93% using this size Percent of Ads Delivered In-View by Ad Size one potential cause? the relationship between ad sizes and their typical placement on a web page
    20. 20. Digital Ad Economics: The Good Guys Aren’t Necessarily Winning Low correlation of In-View Rates & CPM R²=0.0373An equally as weak correlation was also observed between CPM and ability to hit a primary demographic target
    21. 21. On a campaign-by-campaign basis, one performedflawlessly, while another delivered 15% of its impressions to the wrong geography Percent of Ads Delivered In Geography by Campaign Sub-optimal geographic delivery is often a result of communication or human error, and it can be remedied with in-flight alerting and blocking
    22. 22. Of those ads delivered outside of their target, a goodportion of them landed in countries where English is not even the primary language% of Ads Delivered to Geographic Market Among All Impressions Delivered Outside of N.A.
    23. 23. Brand safety should be of the utmost importance to advertisers.Even one poorly delivered ad can leave a very bad impressionPercent of Campaigns with Impressions DeliveredNext to Content Deemed “Not Brand Safe”
    24. 24. The Above-the-Fold Myth?Above-the-fold in-view rates ranged from 48% to 100% source: comScore vCE charter study
    25. 25. Some Below-the-Fold adsare actually premium inventory Below-the-fold in-view ranged from 3% to 67%. source: comScore vCE charter study
    26. 26. There is good news for advertisers and publishers Analogous to TV audience guarantees Eliminating unseen online inventory supply results in:  More effective / efficient campaigns and less waste for advertisers  More accurate metrics for market mix models  Better proof of digital ad effectiveness Increased transparency/accountability means increased confidence in digital
    27. 27. Thank You!Download the whitepaper, continue the conversation