The given data contains transaction and household level data for around 21 months. There is a group of 2,500 households who are frequent shoppers at a retail store. For certain households, demographic information as well as direct marketing/ campaign history is included.
Please use EDA to answer below questions. Analysis on any other point/category apart from questions mentioned below is always welcome.

1. How many customers are spending more over the time? Lesser over the time? Describe these customers.

2. Of those customers who are spending more over the time, which categories are growing at a faster rate?

3. Of those customers who are spending lesser over the time, with which categories are they becoming less engaged?

4. Which demographic factors (e.g. household size, presence of children, income) appear to affect customer spend? Engagement with certain categories?

5.  Is there evidence to suggest that direct marketing improves overall engagement?

6. Retail store is planning to send out a campaign for Nutritional Products and wants a list of potential customers who are more likely to buy in next three months. Use the available data to build a model which predicts if a customer is likely to buy a NUTRITIONAL product in next 3 months. A list of all 2500 household keys followed by prediction in 1/0 needs to be provided in an excel file. Use DEPARTMENT = “NUTRITION” to filter out the products.

Please provide proper analysis based on data and it should be backed up with relevant tables/graphs.