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Assessment BUS5PA Predictive Analytics - 2021 BUS5PA Assignment 3 BUS5PA Predictive Analytics – Semester 1, 2021 Assignment 3: Customer Segmentation, Association Rule Mining, and MBA Case Studies Release Date: 10th May 2021 Due Date: 4th June 2021 11.59 pm Weight: 30% Format of Submission: A report (electronic form) + SAS files in .spk format (electronic) Submission of project in LMS site. Part A - Cluster Analysis (40%) The manager of a leading supermarket mall is interested in finding out purchasing behaviors of customers. Based on this, he wishes to identify different segments of customers in order to improve the current target marketing campaign. The CUSTOMER_DATA dataset contains the basic details about customers obtained via membership cards. In this dataset each row represents an individual customer. There are five variables in the dataset. The variables in the data set are shown below with the appropriate roles and levels. Name Model Role Measurement Level Description CustomerID ID Nominal Identification number of the customer Gender Input Nominal Gender of the customer Age Input Interval Age of the customer Annual_Income Input Interval Annual Income ($) Spending_Score Input Interval Spending score of the customer based on the previous purchase records. The spending score ranges from 1 to 100 You, as the data analyst, is required to conduct a cluster analysis for the data set and provide an insightful report to the manager of the supermarket mall to understand different customer behaviors. a. Create a new diagram in your project. Name the diagram as profiling. b. Define the data set CUSTOMER_DATA as a data source. c. Add an Input Data Source node to the diagram workspace and select the CUSTOMER_DATA data table as the data source. d. Determine whether the model roles and measurement levels assigned to the variables are appropriate. Examine the distribution of the variables. • Are there any skewed variables? • If yes, use the Transform variables node to transform the skewed variables. (Hint: Use the log transformation; LOG(variable_name) BUS5PA Predictive Analytics - 2021 BUS5PA Assignment 3 e. Add a Cluster node to the diagram workspace and set the number of clusters as four. f. Set the appropriate properties for the Cluster node. Leave the default setting as Internal Standardization Standardization What would happen if inputs were not standardized? Explain using knowledge from discussions in the class. g. Run the diagram from the Cluster node and examine the results. Does the number of clusters created seem reasonable? Discuss using knowledge from class discussions – what is a cluster/how many clusters should you have, etc. h. Specify a maximum of six clusters and re-run the Cluster node. How does the number and quality of clusters compare to that obtained in part e? i. Use the Segment Profile node to summarize the nature of the clusters. Describe the profiles based on different customer behaviors. j. The supermarket manager would like to develop a target marketing strategy based on this cluster analysis. Prepare a brief report (max. 1000 words) presenting: (a) The problem (b) Your solution/approach (c) Outcomes (d) Analysis results and interpretation With the presentation, discuss how the clustering and store profiles you have carried out could be used in such a strategy. Part B - Market Basket Analysis and Association Rules (30%) In order to plan innovative promotions to move items that are often purchased together, a supermarket chain is interested in market basket analysis of groceries purchased. You are a member of the analytics team assigned to the task. The supermarket chose to conduct a market basket analysis of specific items purchased from the online TRANSACTIONS data set contains information about more than 38,000 transactions made over the past three months from 167 different items including: You have access to SAS Enterprise Miner data analytics tools and decided to carry out a market basket and association rule-based analysis of the data. The following instructions will help you to set up the SAS diagram for the analysis. Whole milk soda Tropical fruit Citrus fruit Shopping bags Bottled beer Other vegetables yogurt Bottled water Pip fruit Canned beer Newspapers Rolls/buns Root vegetables sausage pastry Whipped/sour cream frankfurter BUS5PA Predictive Analytics - 2021 BUS5PA Assignment 3 There are three variables in the data set: Name Model Role Measurement Level Description MemberId ID Interval Member identification number Item Target Nominal Product purchased Date Rejected Time ID Date of this product purchased k. Create a new diagram. Name the diagram Retail. l. Create a new data source using the data set TRANSACTION. m. Assign the variable Date the model role Rejected. This variable is not used in this analysis. Assign the ID model role to the variable MemberId and the Target model role to the variable Item. Change the data source role to Transaction. n. Add the TRANSACTIONS data set and an Association node to the diagram. o. Change the setting for the Export Rule by ID property to Yes. p. Leave the remaining default settings for the Association node and run the analysis. Examine the results of the association analysis. Your team leader has indicated that the answer to the following questions will be useful to the management. You have to answer the questions and prepare a report giving evidence to support your answers – (e.g.: Screen shots, numeric values etc.). 1. What is the significance of the lift value of a rule? What is lift and what is the importance in calculating lift? 2. What is the highest lift value for the resulting rules, which rules have this value? What does the highest lift value signify? 3. Based on the association rules, briefly describe 3 example product bundles and promotions that you might suggest? You are required to provide detailed report of the outcomes of the analysis to your manager. Prepare a brief report (max. 1000 words) presenting: (a) The problem (b) Your solution/approach (c) Outcomes (d) Analysis results and interpretation You should explain the approach and outcomes such as support, confidence, lift and-, how could the product bundles you suggested be used (practical value) by the departments. BUS5PA Predictive Analytics - 2021 BUS5PA Assignment 3 Part C – Open Discussion - Analytics Case Study (30%) This question is based on the week 11 guest lecture. It is very important that you attend the guest lecture to be able to answer this question. You will be provided with a case study related to the guest lecture and additional resources with related background knowledge. You are expected to summarize the content of guest lecture and discuss how you relate the guest lecture to the provided case study. • How would you make use of the knowledge and understanding you gained from the guest lecture to relate to the case study.? • Do you think the approach taken in the case study could have been improved or advanced? You are expected to write a report (max 1000 words) discussing the above points. BUS5PA_2021_SEM1-Assignment_3_Answer_Guidelines.pdf BUS5PA Assignment 3 – Answer preparation guidelines (Rubric) A) Expectation Matrix for answer preparation D C B A PART A Appropriately named, implemented project and diagram. Attempt on clustering without further explanations and complete questions A(a) to A(e) with log transformation if necessary. D requirements + Correct data standardization as required. Explanation for questions A(f) to A(h). Basic attempt on segmentation and basic attempt on the report. C requirements + Comprehensive answer to question A(i) and good attempt on the report. B requirement + Answer to question A(j) with brief justification and recommendation of the target market strategy. More focus should be given to the interpretation of results with actionable insights to the client (manager of the supermarket). Detailed report with strong insights and analysis. PART B Appropriately named, implemented project and diagram. Answers to questions B(k) to B(p) D requirements + Correct answer to questions 1 and 2 in the last section with brief explanation in the report. C requirements + Correct answer to question 3 in the last section with brief explanation of product bundles. Good structured attempt in the report. B requirement + Correct answer to report of the outcomes in the last section with recommendations and insights. Detailed report with strong insights and analysis. PART C Demonstrated understanding of the case study and appropriate discussion over the predictive analytics life cycle D requirements + Discussion of how each of the life cycle steps is represented in the case study + mention of 3 key points from the guest lectures that the student found useful C requirements + Extending the discussion to elaborate on how the 3 points from the guest lecture could be used to further understand/add value/elaborate the discussion. B requirement + Demonstration of clear understanding of the case study, related lifecycle steps, highlighting of guest lecture points and expanding the discussion to Banking (references from recent projects/news in the field). B) Report format – A formal report is NOT expected for this assessment. As students of Masters level, you are expected to decide a suitable format for an informal report. Please speak to lecturer if you are unsure about the format. A word or pdf file with the heading BUS5PA Assignment 3, and student details should be submitted. There is no strict word or page length, but students must keep in mind that a report that is too long can ‘hide’ the important points from the reader. A suggested page length is 10-12 pages + appendix containing additional screen shots of results. C) Submission –