1. Purpose
2. Quick Overview
3. Data Exploration
4. Data Preparation
5. Data Analysis
6. Customer Segmentation
7. Conclusion

The dataset that we have is one of the superstore's transaction datasets. So we gonna analyze to answer this kind of question:

• How much total sales in each year?
• How much total sales, average sales, and standard deviation of sales your company make in 2017?
• Which Segment has the highest profit in 2018?
• Which top 5 States have the least total sales between 15 April 2019 - 31 December 2019?
• What is the proportion of total sales (%) in West + Central in 2019?
• Find top 10 popular products during 2019-2020 in term of total number of orders / total sales / and time since last order

And the last section, we gonna grouping our customer (customer segmentation) by their behavior to use for designing promotions for each customer group to increase the effectiveness of the promotion because the customers have different behaviors, we cannot use the same promotion.. so I gonna use RFM Analysis to group the customers

R - Recency : Time since last order

F - Frequency : Total number of orders

M - Monetary : Total sales

And the last question:

• In our store which customer segment that we have the most?
• Some use case exmaple by using RFM analysis

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