Discuss the strength and weaknesses of the data

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Reference no: EM132139055 , Length: 5

Assignment -

In the lectures of 21 August and 18 September and the tutorials following these lectures (21 August, 18 and 25 September) three segmentation solutions were derived using a dataset from Bank X:

1. A segmentation based on RFM theory

2. A segmentation based on cluster analysis using the balances on different products

3. A segmentation based on cluster analysis using revenue, age and income

These segmentation solutions will each have advantages and limitations. Also, the transactional data contains information of customers at Bank X, which also has advantages and limitations. Please address the two following points in evaluating the data that was used for the segmentation and the three segmentation solutions:

1. Discuss the strength and weaknesses of the data that were analysed and the three segmentation solutions mentioned above

2. Evaluate the use of the analysed data for cluster analysis purposes in terms of ethical considerations. Do you think that banks can use data in this way? Why (not)?

After considering the segmentation solutions that were discussed in class, you should address the following two points (note that for points 3 and 4 you use the data that were also used in the 19 and 26 September tutorials):

3. Bank X would like to use cluster analysis for developing different product strategies for different groups of customers. Based on the knowledge that you have gained please formulate the marketing problem more precisely and clarify which variables should be included in the segmentation solution and why.

4. Develop and report the segmentation solution.

Deliverables: A written report of 5 pages (font size 12, double-spaced, including all graphs and tables). It is recommended to align the structure of the report with the questions; that is, include one section to answer each of the questions.

Attachment:- Assignment Files.rar

Reference no: EM132139055

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Reviews

len2139055

10/12/2018 5:44:45 AM

Recommendations for writing a report in Customer Intelligence (156.340) Stick to the requested number of pages +/- 10 percent. There are only few formal requirements (font size, spacing) but these need to be fulfilled. Demonstrate that you did your research by using references. Use consistent citation and referencing style. Use a clean formatting. Avoid mistakes. Bad formatting and many mistakes signal that you have not worked diligently. A clean formatting and an error-free document are minimum requirements to convince a reader that your report can be trusted.

len2139055

10/12/2018 5:44:39 AM

Carefully read the assignment. Make sure you do what has been requested. For instance, do not run a correlation analysis when the assignment asked you to run a regression. Include all information that is necessary to understand how you came to your conclusions and recommendations. That is, describe purpose, research problem and goal of the report, quickly describe the data set, the variables contained, the model(s) specified, the results, and then discuss the results and derive the appropriate conclusions. Make sure you provide the information in the appropriate order. Do not just jump to the analysis without providing the necessary information in advance.

len2139055

10/12/2018 5:44:32 AM

Clearly explain why you did what (e.g., choice of a specific method, model specification, etc…). For instance, if you run different models explain why you did that. Also clearly identify the model and results that you use to derive your recommendations. Again, justify your choice. Do not waste space for screenshots and descriptions of each single step in the SPSS analysis. What you do, why you do it, what are the results and what they imply are the questions that count. How you do it in SPSS (pushing buttons in SPSS) is not what is requested in the assignments.

len2139055

10/12/2018 5:44:26 AM

If the assignment is supposed to be group work: Clearly state your group number. Do not use first person singular (i.e., “I analysed …” etc.). Use first person plural (i.e., “We analysed…”). Make sure you contribute appropriately! If there are complaints about someone not contributing, significant penalty may apply! Evaluation of the report (100 points) - Quality of writing and presentation of the report (25 points) Statistical rigour (25 points) Clarity of the statistical report (25 points) Ability to write up statistical outcomes for managerial audience (25 points).

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