6-1 Milestone three.docx - 6-1 FINAL PROJECT MILESTONE THREE Roberto Soto II DAT 220 Fundamentals of Data Mining 6-1 Final Project Milestone Three

6-1 Milestone three.docx - 6-1 FINAL PROJECT MILESTONE...

This preview shows page 1 - 3 out of 5 pages.

6-1 FINAL PROJECT MILESTONE THREE 1 Roberto Soto II DAT 220: Fundamentals of Data Mining 6-1 Final Project Milestone Three Southern New Hampshire University
Image of page 1
FINAL PROJECT MILESTONE THREE 2 Analysis Organization Cluster analysis was used to separate the customer population into individual groups of customers with similar qualities. This was done for qualities such as age, income, marital status, and spend rate. This technique is used to separate the customers for the of developing ad campaigns for certain customers that might be more useful than targeting everyone in the area. Different sections of the customers were found by using all the available qualities. Customer groups made by separating the population for amount spent at the restaurant showed that the more a customer spends at the restaurant, more than likely they manage to spend online when they make a web purchase. With these results they be used target certain groups of customers which have a higher return ability on advertising. One drawback to this analysis is that I used only used a single variable to separate customers. For the cluster analysis techniques which use more than one variable may more effectively separating customers. Linear regression was used to calculate web store spend. If the correct model can be developed to calculate spend rate at any of the store types, the model can then be used to estimate how different customer qualities affect the amount spent. Knowing this Bubba Gump can then target certain customers which will spend the most or research how they can change their stores to attract to customer which do not spend large amounts. I started by using all
Image of page 2
Image of page 3

You've reached the end of your free preview.

Want to read all 5 pages?

  • Summer '16

  • Left Quote Icon

    Student Picture

  • Left Quote Icon

    Student Picture

  • Left Quote Icon

    Student Picture