Analytics And Intelligent Systems

NUS ISS AIS Practice Group

Recurrent Neural Networks for Customer Purchase Prediction on Twitter — June 5, 2017

Recurrent Neural Networks for Customer Purchase Prediction on Twitter

Objective: To identify whether a user will buy a product based on their sequential tweets and to improve the prediction of customer purchase. It is also to eliminate the non-buyers based on tweets.

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Source: Recurrent Neural Networks For Customer Purchase Prediction on Twitter

Submitted By: Ashok Kuruvilla Eapen, Abhilasha Kumari, Pranav Agarwal, Navneet Goswami and Rohit Pattnaik

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Objective
This Study was done to understand the impact of culture to win back defected customers. This study was conducted on college age consumers in America and China. This segment of consumers are target consumers of many technology and personal services.
Hypotheses
H1: Chinese customers, when compared to American customers, will be more influenced by WOW offer when deciding on switching back to original provider
H2: Chinese Customers will be more influenced by relative social capital when deciding on switching back
H3: Chinese Customers will be less influenced by their post-switching regret when decide to switch back

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 Source: https://faculty.unlv.edu/gnaylor/JCSDCB/Volume25/Liu_etal.pdf”>

CONSIDERING CULTURE TO WIN BACK LOST CUSTOMERS: COMPARING CHINESE AND AMERICAN CONSUMERS
Submitted by:
Muni Ranjan<A0163382E>, Pradeep Kumar<A0163453H>, Anusuya Manickavasagam<A0163300Y>, Khine Zin Win<A0163222U>

LINEAR MODELLING AND OPTIMIZATION TO EVALUATE CUSTOMER SATISFACTION AND LOYALTY —

LINEAR MODELLING AND OPTIMIZATION TO EVALUATE CUSTOMER SATISFACTION AND LOYALTY

Journal Summarization for Customer Relationship Management (EB5203) Assignment

In this study, a conceptual framework is postulated to mathematically evaluate and ascertain the hypothesised relationship that perceived value and interactivity has with customer dissatisfaction issues. Then, the relationship between customer satisfaction issues and loyalty and customer acquisition, will be tested to enhance customer satisfaction and loyalty.

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Team Members:-

Prashant Jain, Praveen Tiwari, Kavya AK, Praman Shukla

Customer Acquisition and Retention Spending: An Analytical Model and Empirical Investigation in Wireless Telecommunications Markets — June 3, 2017

Customer Acquisition and Retention Spending: An Analytical Model and Empirical Investigation in Wireless Telecommunications Markets

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Journal Summary for Customer Relationship Management (EB5203) Assignment by Min, Sungwook, et al. The Journal modeled Acquisition and Retention Costs in the Telecommunication industry based on 3 factors: market leader, number of competing firms, and market penetration.

Team Members: Lynette Seow Hui Xin, Meng Yang, Raghavendra Shanthappa, Stella Ellyanti

A Hybrid Segmentation Approach for Customer Value —
Do Loyalty Programs Really Enhance Behavioural Loyalty? — November 11, 2016

Do Loyalty Programs Really Enhance Behavioural Loyalty?

As part of the Customer Relationship Management elective, our team has come up with a one-page summary of the paper published by Leenheer, J., van Heerde, H.J., Bijmolt, T.H.A., and Smidts, A. (2007)  titled “Do loyalty programs really enhance behavioral loyalty? An empirical analysis accounting for self-selecting members.”.

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Team Members: Chua Jialing Vivien, Liang Jialiang, Prateek Nagaria, Supriyaa

ISS Learning Day 2016 — September 7, 2016