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Situation- A leading news brand was supported by ad monetization i.e users watching would be shown pre-roll and mid-roll ads. Our north star metric was # of users watching video since our assumption was more the videos watched, more the ad monetization.
Task- The ad monetization revenue was still lagging despite increase in number of videos watched. We were probably looking at a wrong north star metric
Action- I looked at the ad consumption data, most of the customers dropped off when they reached the mid roll ad. Due to which we were only able to get through pre-roll ad. To resolve this, we decided to add a functionality to supress mid roll ad if the user has already seen an add for the past 4 mins. This reduced the amount of users dropping after the mid roll ad. We also updated our north start metric as # of users who have watched the video for atleast 60% of duration since mid roll ad is shown at 50% of the video segment.
Result- The new north star metric was a true representation of ad monetization since it demonstrated the users who had definitely seen the pre-roll ad and a portion of users who had seen mid roll ads
Task- The ad monetization revenue was still lagging despite increase in number of videos watched. We were probably looking at a wrong north star metric
Action- I looked at the ad consumption data, most of the customers dropped off when they reached the mid roll ad. Due to which we were only able to get through pre-roll ad. To resolve this, we decided to add a functionality to supress mid roll ad if the user has already seen an add for the past 4 mins. This reduced the amount of users dropping after the mid roll ad. We also updated our north start metric as # of users who have watched the video for atleast 60% of duration since mid roll ad is shown at 50% of the video segment.
Result- The new north star metric was a true representation of ad monetization since it demonstrated the users who had definitely seen the pre-roll ad and a portion of users who had seen mid roll ads
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