Assignment: Leveraging Predictive Analytics for Customer Engagement Objective:

The objective of this assignment is for students to understand the impact of predicting customer routines on business strategy and customer engagement. Students should analyze the findings presented in the article by Eva Ascarza and colleagues and explore potential applications for different industries.

Instructions: 1. Article Understanding: Read the provided article by Eva Ascarza and colleagues. Summarize the key findings regarding the advantages of services becoming part of a customers routine. Identify how routine customers contribute higher value to organizations, even after controlling for their level of consumption.

2. Case Study Analysis: Analyze the case study involving a rideshare company in New York City. Explain how the researchers tracked routine users and developed a model to identify routines. Discuss the implications of the routine-based model for predicting customer behavior in the ridesharing industry.

3. Generalization to Other Industries: Explore how the routine-based model and predictive analytics can be applied to industries beyond ridesharing. Provide examples of other service industries (e.g., streaming video, online retailing) that might benefit from using similar predictive models.

4. Business Strategy and Customer Engagement: Discuss how businesses, such as Procter & Gamble, Adidas, and McDonalds, could benefit from harnessing customer routines. Explore the idea of tailoring marketing messages and services based on the identified routines of customers. Consider the potential advantages routine customers may have, including tolerance for price increases and increased loyalty during service issues.

5. Implications for Policymakers: Analyze the potential implications of tracking routines for policymakers, using examples from the transportation sector. Discuss how understanding patterns of behavior, especially in transport, could be relevant for policymakers in designing flows and infrastructure.