Bayesian Non-parametric model to Target Gamification Notifications Using Big Data

TL;DR

This paper presents a Bayesian non-parametric model that enables scalable, real-time targeting of gamification notifications to users by adaptively learning from streaming data, improving marketing effectiveness.

Contribution

It introduces a flexible Bayesian non-parametric approach for targeting gamification notifications, capable of learning from streaming data and adapting over time.

Findings

Model is scalable and suitable for streaming data

Allows dynamic adjustment of task order based on user data

Enhances targeting effectiveness in online marketing

Abstract

I suggest an approach that helps the online marketers to target their Gamification elements to users by modifying the order of the list of tasks that they send to users. It is more realistic and flexible as it allows the model to learn more parameters when the online marketers collect more data. The targeting approach is scalable and quick, and it can be used over streaming data.