Akamai Data Leveraged in Landmark Scientific Study on the Effectiveness of Online Video Advertisements
New measurement study pursues scientific understanding of when viewers complete watching video ads and when they abandon them
Akamai Technologies, Inc. (NASDAQ: AKAM), the leading provider of cloud services for delivering, optimizing and securing online content and business applications, today announced the publication of a new scientific study that leveraged data from hundreds of millions of online videos and advertisements measured using the Akamai Sola Analytics media measurement and analysis product. The research paper, "Understanding the Effectiveness of Video Ads: A Measurement Study," coauthored by S.S. Krishnan and R.K. Sitaraman, will be presented at the ACM Internet Measurement Conference (IMC) in Barcelona on Thursday, October 24, 2013.
The study analyzed in aggregate 367 million videos and 257 million ads from over 3,000 publishers that were viewed by 65 million unique users worldwide. Among the key findings:
The position of an ad has the single largest impact on completion rate, with a mid-roll ad 18.1 percent more likely to be completed than the same ad as a pre-roll, and pre-rolls 14.3 percent more likely to be completed than the same ad as a post-roll.
Repeat visitors to a site have higher completion rates for ads on that site than one-time visitors to that site.
Viewers are more tolerant of video ads than of slow-loading videos. Viewers who must wait 10 seconds for their video to load are three times more likely to abandon than users who spend the same amount time watching a pre-roll ad.
Users who abandon ads leave early. One-third of the abandoners leave at or before the quarter-way mark and two-thirds at or before the halfway mark in the ad.
Ads that play within long-form content such as TV episodes and movies complete at a higher rate (87 percent) than those that play in short-form content such as news clips and sports highlights (67 percent).
Time of day and day of week do not affect ad completion rates substantially.
"This study is unique in that it goes above and beyond tracking and comparing completion rates, and rather takes an in-depth look at when viewers complete watching video ads and when they abandon them," said Dr. Ramesh K. Sitaraman, Akamai Fellow and computer science professor at UMass-Amherst, who led the study. "By using novel scientific techniques for extracting knowledge from huge amounts of anonymized viewer data, we are able to gain a deeper understanding of video ads that are key to the monetization economics of online videos."
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