Marketing Sementation by Unsupervised Learning

Perform marketing segmentation for advertising by unsupervised learning techniques: clustering (k-means), principal component analysis and auto encoders

Posted by Zhiyi Li on August 30, 2022 · 3 mins read

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Understand Marketing Segmentation

Why Marketing is essential?

  • Marketing is crucial for the growth and sustainability of businesses
  • Marketing could help to build the company’s brand, engage customers, grow revenue and increase sales
  1. Growth: empowering business growth by reaching new customers
  2. Education: educating and communicating value porposition to customers
  3. Drive sales: driving sales and traffic to products/services
  4. Engagement: engaging customers and understand their needs

Why Market Segmentation is important?

  • One of the key pain points for marketers is to know customers and identify their needs
  • By understanding customers, marketers could launch a targeted marketingg campaign to tailor for specific needs
  • Data Sciene could be used to perform market segmentation

Task: Launch targeted ad marketing compaign by dividing customers into distinctive groups data: banking data about customers for past 6 months

Data Source: https://www.kaggle.com/arjunbhasin2013/ccdata

Data Information: This case requires to develop a customer segmentation to define marketing strategy. The sample Dataset summarizes the usage behavior of about 9000 active credit card holders during the last 6 months. The file is at a customer level with 18 behavioral variables.

Following is the Data Dictionary for Credit Card dataset :-

  • CUSTID : Identification of Credit Card holder (Categorical)
  • BALANCE : Balance amount left in their account to make purchases
  • BALANCEFREQUENCY : How frequently the Balance is updated, score between 0 and 1 (1 = frequently updated, 0 = not frequently updated)
  • PURCHASES : Amount of purchases made from account ONEOFFPURCHASES : Maximum purchase amount done in one-go
  • INSTALLMENTSPURCHASES : Amount of purchase done in installment
  • CASHADVANCE : Cash in advance given by the user
  • PURCHASESFREQUENCY : How frequently the Purchases are being made, score between 0 and 1 (1 = frequently purchased, 0 = not frequently purchased)
  • ONEOFFPURCHASESFREQUENCY : How frequently Purchases are happening in one-go (1 = frequently purchased, 0 = not frequently purchased)
  • PURCHASESINSTALLMENTSFREQUENCY : How frequently purchases in installments are being done (1 = frequently done, 0 = not frequently done)
  • CASHADVANCEFREQUENCY : How frequently the cash in advance being paid
  • CASHADVANCETRX : Number of Transactions made with “Cash in Advanced”
  • PURCHASESTRX : Numbe of purchase transactions made
  • CREDITLIMIT : Limit of Credit Card for user PAYMENTS : Amount of Payment done by user MINIMUM_PAYMENTS : Minimum amount of payments made by user
  • PRCFULLPAYMENT : Percent of full payment paid by user
  • TENURE : Tenure of credit card service for user
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