2 research outputs found
Audience Prospecting for Dynamic-Product-Ads in Native Advertising
With yearly revenue exceeding one billion USD, Yahoo Gemini native
advertising marketplace serves more than two billion impressions daily to
hundreds of millions of unique users. One of the fastest growing segments of
Gemini native is dynamic-product-ads (DPA), where major advertisers, such as
Amazon and Walmart, provide catalogs with millions of products for the system
to choose from and present to users. The subject of this work is finding and
expanding the right audience for each DPA ad, which is one of the many
challenges DPA presents. Approaches such as targeting various user groups,
e.g., users who already visited the advertisers' websites (Retargeting), users
that searched for certain products (Search-Prospecting), or users that reside
in preferred locations (Location-Prospecting), have limited audience expansion
capabilities. In this work we present two new approaches for audience expansion
that also maintain predefined performance goals. The Conversion-Prospecting
approach predicts DPA conversion rates based on Gemini native logged data, and
calculates the expected cost-per-action (CPA) for determining users'
eligibility to products and optimizing DPA bids in Gemini native auctions. To
support new advertisers and products, the Trending-Prospecting approach matches
trending products to users by learning their tendency towards products from
advertisers' sites logged events. The tendency scores indicate the popularity
of the product and the similarity of the user to those who have previously
engaged with this product. The two new prospecting approaches were tested
online, serving real Gemini native traffic, demonstrating impressive DPA
delivery and DPA revenue lifts while maintaining most traffic within the
acceptable CPA range (i.e., performance goal). After a successful testing
phase, the proposed approaches are currently in production and serve all Gemini
native traffic.Comment: In Proc. IeeeBigData'2023 (Industry and Government Program
Conversion-Based Dynamic-Creative-Optimization in Native Advertising
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.Comment: Accepted to IEEE Big Data 2022 conferenc