Project Objective
"A new product is being planned, and due to its higher unit price compared to most products, it is expected to use past sales data to understand the correlation coefficient between price and sales volume, and predict potential sales volume at a specified price.
Data Ingestion
The data is sourced from the company's sales records.
Data Processing
Convert 'net_qty' and 'asp_usd_sales' from text format to numeric format.
Since only the total sales amount is available, divide it by 'net_qty' to obtain the product unit price.
Divide the data into three groups: '', '2022', and 'all'.
Transform the sales data into a pivot table categorized by 'Model Name' and calculate the total sales volume and average selling price for each model.
Analysis Methods
Since the prediction involves finding the correlation between two variables, should apply linear regression analysis.
Presentation
Present the data in a scatter plot.
The predicted value of y when x is $999 is: 1921pcs.
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