Marketing Analytics for FGP Customer Loyalty Program: Brief

Background

The FGP customer loyalty program① is a program run in an Asian country. It consists of three merchant members, a fast food chain (F), a grocery store chain (G), and a petrol station chain (P). The three merchant members are independent firms, but they form a league via this customer loyalty program. That is, a customer who joins the FGP loyalty program will be rewarded 1 point for each dollar she spends at any of the three firms, and each reward point is worth $0.01 and can be   redeemed from any of the three firms. The three firms believe this program can create more value  for their customers and therefore the customers will become more loyal.

The three firms hired a third party to run the program for them, and the FGP program has run well in the past 11 years. Jennifer, the loyalty program manager, is ambitious and is considering expanding the loyalty program to attract more customers and additional merchant members. But    she also needs to deal with some complaint from the existing merchant members. For example, her assistant told her that one merchant member manager thought his firm contributes more to the loyalty program than the other two firms; therefore the other two firms should compensate by sharing more costs of the loyalty program operations.

Although the potential problems have not become serious issues yet, Jennifer knows that it is critical to pre-empt these problems. At the same time, she needs insights to guide her expansion plan and evidence to persuade the current three merchant members (that they will benefit more from the loyalty program with the expansion). Therefore, Jennifer hired your team to study the data from the past operations and find out insights and evidence for her. Based on Songting’s suggestion, Jennifer has also conducted a survey and studied customers’ satisfaction towards the FGP loyalty program and its merchant members, and their willingness to recommend the FGP loyalty program to their friends or colleagues. This set of survey data has also been provided to you.

Manager’s Questions

To address her managerial needs, Jennifer believes that insights to the following two questions will be very helpful.

.     How to estimate the value of a customer in the loyalty program, predict if a customer will churn, and manage the customers accordingly?

.     How does each merchant member contribute to the loyalty program and benefit from the program? Does the synergy of the three merchants help retain customers?

Obviously, to provide insights to these two problems, one needs to thoroughly analyse the customer database, and have a good understanding of the customers’ behaviour in the loyalty program. Due to the length of the report, your team is expected to focus on ONE question and provide analytical insights to help managers make informed decisions. Alternatively, if your team has another angle which can also help with Jennifer’s managerial needs in some way, you are more than welcome to propose your own managerial problem.

Keep in mind that, given the length of your report, the goal is not to address the entire problem,  but to provide quality insights and recommendations to help Jennifer with a part of the problem that she is facing.

Dataset Description

The dataset provided to you consists of 3,200+ customers. There are 3 worksheets in the Excel data file, and the data items are described below. Sales and redemption data cover a time period from Jan, 2018 to Sep, 2019, all before the global pandemic.

Sheet “customers”

This sheet has the data on customer characteristics and their opinions learnt from the survey. The data items include:

.     MemberID (a unique ID for each customer)

.    Gender (“F”=Female, “M”=Male)

.     Race (“RACE1”, “RACE2”, “OTHER”)

.    OwnCar (“Y”=Yes, “N”=No)

.    OwnCreditCard (“Y”=Yes, “N”=No)

.     HomeCity (“CityA” ~ “CityF” + “Other”)

.     BirthYear (the year of birth)

.     RegisterYear (the year of registration)