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Study of customer preference, price elasticity and customer segmentation using RFM

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Customer-Segmentation---SAS


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About

Analysis of toothbrush sales in the US Market. This exercise was the part of Predictive Analytics coursework at The University of Texas at Dallas.

The following analysis were made to come out with the recommendation for improvement in the market share

  • Segmentation of customers through Recency, Frequency and Monetory (RFM Analysis)
  • Price Elasticity
  • Preference of customer of brand based on price reduction flag, display etc

Data Description

The dataset is primarily about the toothbrush sales of different brands sold in the US. The analysis we performed is for the Colgate brand.

Data, Code and Report

The data used for the analysis, code and the complete interpretations of the output of the analysis can be found here

Recommendation

Oral-B is the market leader and the tough competitor for Colgate compared to any other brand. To be the market leader Colgate must battle with Oral-B for new market shares

  • Reducing price would not improve the sales to a greater extent but reducing the price and having right advertisement like price reduction tag and feature display would improve the sales.
  • If Oral-B along with price reduction also has a display, this could affect the sale of Colgate, this is when manager must place the right advertisement for Colgate in line with competitor Oral-B
  • From the brand choice analysis, we see that customers are less likely to choose Oral-B if there is price reduction along with display advisement by Colgate. When there is price reduction sale it’s important to have display advisement, else the price reduction is not that effective
  • From the RFM analysis we can conclude that we need to concentrate the marketing campaign on Big Spenders, Potential Loyal and Customer at Risk. ~23% are lost and non-monetary, these people should be removed from the marketing campaign and focus must be on who are likely to churn, which is ~28% customers

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Study of customer preference, price elasticity and customer segmentation using RFM

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