Tell me a scenario where data was used to make/change an ad serving decision.
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@Nag
Platinum PM
Platinum PM
Situation- We had a scenario where users watching family shows were dropping off during the watching segment of 3-5 pm specifically after 15 mins of watch segment (where the mid roll ad plays)
Task- Understand the drop in user base and its relationship with type of ads being shown
Action- We analyzed the data as follows:
1) The device where the content was being watched- OTT
2) User segment- Adult male, 35-45 years of age
3) Cross device association- Tablet and OTT platform belonged to the same user
4) Audience insights- as above
It was found that the ads being played were relevant to the user watching owning the account whereas the content was being watched as a family. Due to this, as soon as ads were being played; the couple lost interest and moved on to something else
Result- The ad recommendation engine was fixed to provide higher weightage to the content being and genre and other content specific metrics being played than the user or the behavioral attributes of the user
Task- Understand the drop in user base and its relationship with type of ads being shown
Action- We analyzed the data as follows:
1) The device where the content was being watched- OTT
2) User segment- Adult male, 35-45 years of age
3) Cross device association- Tablet and OTT platform belonged to the same user
4) Audience insights- as above
It was found that the ads being played were relevant to the user watching owning the account whereas the content was being watched as a family. Due to this, as soon as ads were being played; the couple lost interest and moved on to something else
Result- The ad recommendation engine was fixed to provide higher weightage to the content being and genre and other content specific metrics being played than the user or the behavioral attributes of the user
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