Open-sourced Propensity Model Package: Accelerating Data-Driven Decisions (Workshop #1) | Google
About This Video
A propensity model attempts to estimate the propensity (probability) of a behavior (e.g., conversion, churn, purchase, etc.) happening during a well-defined time period into the future based on historical data. It is a widely used technique by organizations or marketing teams for providing targeted messages, products or services to customers. This workshop shares an open-sourced package developed by Google, for building an end-to-end Propensity Modeling solution using datasets like GA360, Firebase or CRM and using the propensity predictions to design, activate and measure the impact of a media campaign. The package has enabled companies from e-commerce, retail, gaming, CPG and other industries to make accelerated data-driven marketing decisions.
This workshop was conducted by Lingling Xu, Bingjie Xu, Shalini Pochineni and Xi Li, data scientists on the Google APAC team.
Useful resources for this workshop:
– https://bit.ly/github_propensity_mode…
– https://bit.ly/bigquery_export_schema
– https://bit.ly/ga_sample_dataset
– https://bit.ly/ml_windowing_pipeline
In This Video
Marketing Data Scientist, Google
Dr Lingling Xu is an experienced data scientist with a PhD from National University of Singapore (Information Systems & Analytics). In the past 10 years, she was in the public health, consumer goods, and technology industry, where she applied statistics and data science to improve business operations, inform product innovation, and influence company strategy. Currently, Lingling is a data scientist for Business & Marketing at Google. She works with Google’s largest clients to build quantitative models to address the challenges of marketing effectiveness, return on investment and prediction.
Marketing Data Scientist, Google
Bingjie is working at Google to support the stakeholders in GRCN across multiple industries, including E-commerce, Short video, Technology, and Gaming, by leveraging her skill sets in Data Science to solve data-driven business challenges. Bingjie graduated from University of Michigan – Ann Arbor with degrees in Computer Science Engineering and Statistics. Bingjie has also had industrial experience working in the Finance, Job Search, and Medicine industries on solving engineering and data science problems.
Senior Data Scientist, Google
Shalini is a post graduate in management, with 9+ years of experience in data science, marketing analytics, risk management and operations solutions. Her functional strengths include Machine Learning, Risk analytics, Marketing Analytics, Digital Fraud Detection & Prevention. She has experience working across financial and technology-based companies.
Data Scientist, Google
Xi is a Data Scientist at Google, supporting clients in the E-commerce and Gaming industry with best in class data science solutions. Prior to Google, Xi studied applied mathematics and statistics at École polytechnique fédérale de Lausanne. She also worked as a Data Scientist in IT consulting firms and other technology companies.