I have a project and I couldn't understand what I have to do because I am new to retail analytics.
They said "Our goal is to measure the effects of promotion on sales" and "Your goal is to model the effect of promotion on products and stores. In order to answer questions, you should divide products and stores into 3 clusters each. (High, Medium, Low)"
I have two datasets, let's say;
1 - data.csv -> Date, Store, Product, QuantityOfSales
2 - promotion.csv -> PromName, StartDate, EndDate
There are questions like that:
- What are your criteria for separating High, Medium, and Low Stores? Why?
- Which items experienced the biggest sale increase during promotions?
- Are there stores that have higher promotion reactions?
- What is the biggest effect explaining sales change during promotions?
- Is there any significant difference between promotion impacts of the High versus Low items?
Also, they gave me the same dataset but different time intervals to measure how well my model has worked on this new data.
Actually, I am stuck because I don't know what exactly I have to do. Can anybody show me the path I should follow or show samples?