The Fifth Elephant 2023 Winter

Abstract

Optimizing action events, like purchases and bookings, is the cornerstone for boosting revenue across diverse domains. While the industry has often focused on interest and desire data, such as clicks and impressions, neglecting the critical dimension of action data, in the context of ML modelling, to drive success. Our research at Glance, a leader in personalized content delivery to 200M+ smartphone users, transcends this paradigm. By harnessing action event data, we have witnessed substantial improvements in various facets, underscoring the broader significance of this approach. This paper explores our journey and insights into the pivotal role of prioritizing action events and their impact beyond the realm of advertising, extending to diverse industries.

Key Takeaways

• Large-Scale Model Deployment: Learn strategies and techniques for deploying and scaling machine learning models to serve 200M+ users effectively.

• Elevating Revenue and Enhancing User Experiences with Action Event Data: Explore how it enhances company revenue through precise recommendations, while simultaneously elevating user experiences by delivering only relevant content.

• Advanced Feature Processing: Discover novel feature importance techniques employed in optimizing action event data for better model performance.

• ML Model Advancements: Explore insights and advancements in machine learning models tailored to action event data for enhanced user engagement and revenue growth.

Talk Outline

• Introduction

  • Setting the stage for the importance of action event data

• The Shift in Focus

  • Exploring the industry’s emphasis on interest and desire data

• Glance’s Journey

  • How Glance embraced action event data and its impact on the company

• Key Takeaways

  • Summarizing the insights and implications for organizations

Labels

Recommender Systems, Revenue Growth, Mobile Advertising, User Engagement, Recommender Systems, Data-Driven Decision Making, Personalization

Speakers

Priyansh Jain, MLE - III, InMobi Group

Sumit Yadav, MLE - II, InMobi Group