Conversion-Based Dynamic-Creative-Optimization in Native Advertising
- URL: http://arxiv.org/abs/2211.11524v1
- Date: Sun, 13 Nov 2022 13:13:00 GMT
- Title: Conversion-Based Dynamic-Creative-Optimization in Native Advertising
- Abstract summary: Dynamic creative optimization (DCO) is a recent Gemini native product that was launched two years ago and is increasingly gaining more attention from advertisers.
To accommodate this request, we present a post-auction solution, where DCO ads combinations are favored according to their predicted conversion rate (CVR)
An online evaluation of this explore-exploit solution, via online bucket A/B testing, showed a 53.5% CVR lift, when compared to a control bucket serving all combinations uniformly at random.
- Score: 2.8461446020965435
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Yahoo Gemini native advertising marketplace serves billions of impressions
daily, to hundreds millions of unique users, and reaches a yearly revenue of
many hundreds of millions USDs. Powering Gemini native models for predicting
advertise (ad) event probabilities, such as conversions and clicks, is OFFSET -
a feature enhanced collaborative-filtering (CF) based event prediction
algorithm. The predicted probabilities are then used in Gemini native auctions
to determine which ads to present for every serving event (impression). Dynamic
creative optimization (DCO) is a recent Gemini native product that was launched
two years ago and is increasingly gaining more attention from advertisers. The
DCO product enables advertisers to issue several assets per each native ad
attribute, creating multiple combinations for each DCO ad. Since different
combinations may appeal to different crowds, it may be beneficial to present
certain combinations more frequently than others to maximize revenue while
keeping advertisers and users satisfied. The initial DCO offer was to optimize
click-through rates (CTR), however as the marketplace shifts more towards
conversion based campaigns, advertisers also ask for a {conversion based
solution. To accommodate this request, we present a post-auction solution,
where DCO ads combinations are favored according to their predicted conversion
rate (CVR). The predictions are provided by an auxiliary OFFSET based
combination CVR prediction model, and used to generate the combination
distributions for DCO ad rendering during serving time. An online evaluation of
this explore-exploit solution, via online bucket A/B testing, serving Gemini
native DCO traffic, showed a 53.5% CVR lift, when compared to a control bucket
serving all combinations uniformly at random.
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