Individual Report. A dataset will be available on Blackboard for this report. This dataset reflects customer information for a large retailer. It summarises (by customer level) the total amount spent last year, the total number of transactions (i.e. number of times the customer has visited the store) last year and the date of the last transaction.
There are two activities for this assignment:
(M) value for each customer. Afterwards, use these three variables to create RFM bins. Assume the date for creating these RFM bins is on 1 January 2017. These bins will summarise the behaviour of the customer between 1 January 2016 and 31 December 2016. You need to prepare a short executive summary to summarise the following:
How you defined Recency, Frequency and Monetary in your analysis?
The approach you chose to create the RFM bins (e.g. Hard-coding RFM Bins, Exact Quintiles RFM, etc.) and explain the reason of using this approach.
The number (or the distribution) of customers in each of these RFM bins.
RFM analysis is a common approach used by companies to understand the customer transaction behaviour. Write a short note to explain what RFM analysis is and how a company can use RFM analysis in conducting any marketing activities.
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