这是一篇来自新加坡的关于担任当地一家连锁超市（类似于新加坡的NTUC、成祥、冷库和巨头）的新数据分析师作业代写。主要任务是审查和改进由之前离开公司的数据分析师进行的客户细分研究
The Task
Assume the role of being a new data analyst of a local superstore chain (similar to NTUC, Seng Siong, Cold Storage and Giant in Singapore). You are tasked to review and improve a customer segmentation study (refer to Hands-on Exercise 4) conducted by the previous data analyst who had left the company. The customer segmentation study was performed based on Recency,Frequency and Monetary (RFM) principle of marketing science by using a dataset that contains household level transactions over two years from a group of 2,500 households who are frequent shoppers.
The specific tasks of the further study are as follows:
- Critic the limitations of methods used to derive the RFM variables if any, and suggest alternative methods to derive the variables.
- Increase the numbers of clustering variable to 8 and not more than 12. The clustering variables must represent the shopping behaviour of customers.
The Data
For the purpose of this study, seven data files are provided (Be warned: You are not expected to use all of them in the study). They are all in csv format. The content of each data file are as follows:
transaction_data
This table contains all products purchased by households within this study. Each line found in this table is essentially the same line that would be found on a store receipt.
The variable SALES_VALE in this table is the amount of dollars received by the retailer on the sale of the specific product, taking the coupon match and loyalty card discount into account. It is not the actual price paid by the customer. If a customer uses a coupon, the actual price paid will be less than the SALES_VALUE because the manufacturer issuing the coupon will reimburse
the retailer for the amount of the coupon.
hh_demographic
This table contains demographic information for a portion of households.
campaign_table
This table lists the campaigns received by each household in the study. Each household received a different set of campaigns.
campaign_desc
This table gives the length of time for which a campaign runs. So, any coupons received as part of a campaign are valid within the dates contained in this table.
product
This table contains information on each product sold such as type of product, national or private label and a brand identifier.
coupon
This table lists all the coupons sent to customers as part of a campaign, as well as the products for which each coupon is redeemable. Some coupons are redeemable for multiple products.
One example is a coupon for any private label frozen vegetable. There are a large number of products where this coupon could be redeemed.
For campaign TypeA, this table provides the pool of possible coupons. Each customer participating in a TypeA campaign received 16 coupons out of the pool. The 16 coupons were selected based on the customer’s prior purchase behavior. Identifying the specific 16 coupons that each customer received is outside the scope of this database.
For campaign TypeB and TypeC, all customers participating in a campaign receives all coupons pertaining to that campaign.
coupon_redempt
This table identifies the coupons that each household redeemed.
Deliverables
- An executive summary in MS PowerPoint format.
o The executive report should not be more than ten slides, exclusive of cover-page and content page.
o It should comprise of both the major findings and managerial recommendations.
o The discussions should be in bullet point format.
o The font size of the bullet point should not be less than 24 points.
o Name the file ISSS602_AY2022-23Jan _Assign2_ES_Your full name.
- A technical report of not more than 3000 words in Microsoft Word format (12 points for main text) with the following contents:
o A detailed description of the data preparation.
o A detailed description of the analysis procedures used.
o A clear discussion and interpretation of the analysis results.
o A clear description of managerial recommendations.
o Name the file ISSS602_AY2022-23Jan _Assign2_TR_Your full name.
- An analytical sandbox in JMP file format.
Submission Instruction
- The executive summary, technical report and analytical sandbox are to be submitted in softcopy. You are required to upload the final deliverable into the Dropbox of LMS before the stated assignment due date. Late work will be severely penalised. Students must check and confirm on LMS the assignment due date.
- The final deliverables (e.g. executive summary, technical report and analytical sandbox,etc) must be zipped in a single zip file format.
- Name the zip file according to the course code and assignment, for example:
ISSS602_Assign2.