Using the provided Customer Dataset,

MMG 625 Assignment

Using the provided Customer Dataset, which is a dataset that was used in both MMG 625 and MMG 525,

you are to construct a case study detailing how you would use the said Customer Dataset to develop data

analytics-based customer retention program (meaning an overall strategy, and specific activities). As

discussed numerous times in class, Customer Dataset contains 5,000 records of customers of a telephone

company (such as Verizon or AT&T) and about 40 individual variables representing a cross-section of

purchase behaviors, demographics, and lifestyle metrics – such data are commonly used by companies to

develop customer retention strategies and tactics (among other things), which is what you are asked to do.

The basic idea behind this assignment is for you to act as a manager who is providing very specific

directions to your analyst, where your directions (as detailed in the your report) are geared toward

conducting specific analyses that are to inform and guide the aforementioned customer retention efforts.

Here are the specifics of your assignment:

• Clearly outline and describe your customer retention strategy:

o Are you going to try to retain all customers, regardless of their spending amount? If so,

what is your rationale for investing in retaining customers who spend very little on your

products and services? To be clear, such an approach is generally frowned upon in

practice, so if you decide to select that approach you will be expected to provide clear

and compelling justification.

o If you intent to focus your retention efforts on your ‘high value customers’, which is

commonly done, how will you define what constitutes ‘high value’, and how will you

identify high value customers in your dataset? You are not expected to conduct any

analyses, but you have to detail how you would do that, which means specifying

variables that you would use, and describing how those variables would be analyzed to

produce the required information, and clearly describing the expected outcomes.

• Clearly describe and categorize your data in terms of general categories, such as ‘demographics’

or ‘purchase details’; that means that you need to develop an overarching variable categorization

schema (i.e., create a set of categories or ‘buckets’ into which the individual variables can be

divided) so that each of your 40 or so variables can be placed into what you consider to be the

most appropriate category.

• Detail the specifics of your data analytical approach; the following need to be discussed:

o What specific statistical or machine learning technique/model you plan to use and why?

o What specific variables will be analyzed?

o What are the expected data analytic outcomes, and how those outcomes are to be used?

For example, if you were to use correlation analysis, you would need to identify specific

variables to be correlated (keeping in mind the underlying measurement scales), you

would then need to specify correlation coefficients as outcomes, and describe how those

correlation coefficients would be used to support the information need at hand (in this

case, customer retention)

• Discuss how the above contemplated data analytic outcomes would support/further the stated goal

of customer retention. Keep in mind that your strategy and all subsequent analyses and

considerations are to be focused on retention of phone company customers contained in the

aforementioned Customer Dataset.

Your report should be about five (5) single-spaced pages in length (Times New Roman 11 point font),

excluding any title pages, references, or appendices.

Your work will be assessed as follows:

Analytic appropriateness: 50%

The extent to which your data analytic approach can be reasonably expected to solve the problem at

hand, which here is to provide meaningful informational basis to support customer retention strategy.

Clarity of presentation: 30%

The logic and layout of your report, grammatical and syntactical structure.

Informational needs – data analytic linkage: 20%

The degree to which the business goal at hand (customer retention) and the chosen data analytic

steps are in alignment.

IMPORTANT:

1. This is an individual assignment.

2. You have four (5) weeks to complete the assignment, which is due June 11, 2021 11:59 pm

EST.

3. All reports are to be emailed to [email protected]