Facebook, Inc.

Meta Platforms, Inc.

Leon R Cho

Shyamsundar Rajaram

Chinmay Deepak Karande

Robert Oliver Burns Zeldin

Zheng Chen

Sushma Nagesh Bannur

Raghavendra Rao Donamukkala

Rami Mahdi

Toby Jonas F Roessingh

An online system calculates bids for content items to display to users based on the value of a product described in the content item and the likelihood of a viewing user purchasing the product. The online system identifies an impression opportunity for an ad request and computes an expected value of the conversion and a likelihood of the conversion. The online system computes a bid amount based on the expected conversion value and the likelihood of the conversion. Bids based on the value of the conversion allow a third party system offering the product to optimize for the value of each conversion instead of the conversion rate.

Calculating bids for content items based on value of a product associated with the content item

The present disclosure is directed toward systems and methods for optimizing view-through conversion rates. For example, systems and methods described herein train and utilize a machine learning model that predicts whether providing a digital impression to a particular networking system user will result in a conversion. Systems and methods described herein identify view-through conversions by generating a vector associated with the provision of a digital impression to a networking system user and receiving third-party conversion information during an attribution window. The systems and methods described herein then utilize the vector and conversion information to train the machine learning model to predict future conversions.

Optimizing conversion rates for impressions provided in a networking system

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Chicago, IL, United States of America

Leon R Cho