Metrics and User Engagement

Metrics and User Engagement researchers collaborate across product teams to define metrics for experimentation, user engagement, and product success. We use data-driven user understanding methods to enable optimization of products through experimentation, and guide product development by using large-scale data in deep, grounded analysis.

Publications

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January 24, 2023

AISTATS '23

Precision/Recall on Imbalanced Test Data

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October 10, 2019

WSDM 2020

Ad Close Mitigation for Improved User Experience in Native Advertisements

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June 17, 2019

MIS Quarterly

Enhancing Social Media Analysis with Visual Data Analytics: A Deep Learning Approach

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January 1, 2019

Journal of Marketing

Serial Position Effects on Native Advertising Effectiveness: Differential Results Across Publisher and Advertiser Metrics

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January 1, 2019

Information Processing and Management

Impact of Response Latency on Sponsored Search

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January 1, 2019

SIGIR 2019 workshop on eCommerce

PSAC: Context-Based Purchase Prediction Framework via User's Sequential Actions

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January 1, 2019

KDD

Understanding Consumer Journey Using Attention-Based Recurrent Neural Networks

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January 1, 2019

WSDM 2019

Domain Switch-Aware Holistic Recurrent Neural Network for Modeling Multi-Domain User Behavior

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January 1, 2019

Marketing Science

Frontiers: Asymmetric Effects of Recreational Cannabis Legalization

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