This repository contains the Udacity's nanodegrees' second project completed by me.

In this project, I will analyze a business problem in the mail-order catalog business. I am tasked with predicting how much money my company can expect to earn from sending out a catalog to new customers. This task will involve building the model and applying the results in order to provide a recommendation to management.

You recently started working for a company that manufactures and sells high-end home goods. Last year the company sent out its first print catalog, and is preparing to send out this year's catalog in the coming months. The company has 250 new customers from their mailing list that they want to send the catalog to.

Your manager has been asked to determine how much profit the company can expect from sending a catalog to these customers. You, the business analyst, are assigned to help your manager run the numbers. While fairly knowledgeable about data analysis, your manager is not very familiar with predictive models.

You’ve been asked to predict the expected profit from these 250 new customers. Management does not want to send the catalog out to these new customers unless the expected profit contribution exceeds $10,000.

The costs of printing and distributing is $6.50 per catalog. The average gross margin (price - cost) on all products sold through the catalog is 50%. Make sure to multiply your revenue by the gross margin first before you subtract out the $6.50 cost when calculating your profit. Write a short report with your recommendations outlining your reasons why the company should go with your recommendations to your manager.

Your project should include:

A description of the key business decisions that need to be made. Note: Clean data is provided for this project, so you can skip the data preparation step of the Problem Solving Framework.

Build a linear regression model, then use it to predict sales for the 250 customers. We encourage you to use Alteryx to build the best linear model with your data.

Note: For students using software other than Alteryx, if you decide to use Customer Segment as one of your predictor variables, please set the base case to Credit Card Only.

However, feel free to use any tool you’d like. You should create your linear regression model and come up with a linear regression equation.

Once you have your linear regression equation, you should use your linear regression equation to predict sales for the individual people in your mailing list.

Once you have your predicted or expected profit, write a brief report with your recommendation to whether the company should send the catalog or not. Hint We want to calculate the expected revenue from these 250 people in order to get expected profit. This means we need to multiply the probability that a person will buy our catalog as well. For example, if a customer were to buy from us, we predict this customer will buy $450 worth of products. At a 30% chance that this person will actually buy from us, we can expect revenue to be $450 x 30% = $135.

After conducting an analysis on the data and applying the regression formula to the new dataset, the value for the expected profit will be approximately $21,987.96. So,I would recommend that the company send out the catalog to these 250 customers as there is a greater than $10,000 profit.