Analytics And Intelligent Systems

NUS ISS AIS Practice Group

Managing Customer Loyalty through Acquisition, Retention and Experience Efforts: An Empirical Study on Service Consumers in India — June 5, 2017

Managing Customer Loyalty through Acquisition, Retention and Experience Efforts: An Empirical Study on Service Consumers in India

Recent developments in the marketing literature highlight the significance of consumer relationship management (CRM) in driving consumer loyalty (CL). In order to provide a clear understanding of the impact of CRM on CL, this study develops an integrated framework of CRM activities: Acquisition, retention, and experience to manage Customer Loyalty through direct and indirect approaches (with the mediation of satisfaction, trust, and commitment). The article utilizes a survey-based empirical study of 600 consumers from three service sectors (health, retail, and wellness). The findings of the study suggest that a firm that pays more attention to manage consumer experiences would be significantly benefited from the implementation of CRM programs. Consumer experience efforts have the positive impact on CL through commitment in all three sectors. Service manager should have clarity and consciousness that consumers are not looking for just traditional CRM benefits such as value proportion, reward points and so on but specifically seek for a pleasant experience of various touchpoints. Various frameworks of acquisition of CRM activities to manage Customer Loyalty has been analyzed.

Key Words:
Consumer loyalty, Consumer relationship management, Consumer experience management, Satisfaction, Trust, Commitment

Managing customer Loyalty

Source : Managing Consumer Loyalty through Acquisition, Retention and Experience Efforts: An Empirical Study on Service Consumers in India

Submitted by TEAM MARS

  1. Mutharasan Anbarasan(A0163257A)
  2. Raghavan Kalyanasundaram(A0163316L)
  3. Saravanan Kalastha Sekar(A0163309H)
  4. Seshan Sridharan(A0148476R)
  5. Sindhu Rumesh Kumar(A0163342M)
Customer Churn Prediction in the Telecommunications Sector Using Rough Set Approach —

Customer Churn Prediction in the Telecommunications Sector Using Rough Set Approach

This study aims to develop an improved customer churn prediction technique, as high customer churn rates have caused an increase in the cost of customer acquisition. This technique will be developed through identifying the most suitable rule extraction algorithm to extract practical rules from hidden patterns in the telecommunications sector.

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Submitted by:
Arun Kumar Balasubramanian
Devi Vijayakumar
Sunil Prakash
Gaelan Gu
Sambit Kumar Panigrahi

Recurrent Neural Networks for Customer Purchase Prediction on Twitter —

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

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

ChineseCulture

 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