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https://github.com/samruddhi3012/rfm-sales-analysis

Hi there! In this project I have performed Sales Analysis (RFM Analysis) using SQL and Tableau.
https://github.com/samruddhi3012/rfm-sales-analysis

data-analysis data-visualization mssqlserver rfm-analysis segmentation tableau

Last synced: 20 days ago
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Hi there! In this project I have performed Sales Analysis (RFM Analysis) using SQL and Tableau.

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README 

        
# RFM Sales Analysis

RFM (Recency, Frequency, Monetary) sales analysis is a marketing technique used to evaluate and segment customers based on their purchasing behavior. 



This method helps businesses identify their most valuable customers and tailor marketing strategies accordingly.

![dead3-1_ohv1o0sljibjk6evwkvg5g](https://github.com/user-attachments/assets/94778fb4-289e-48c6-b062-606dfe06ecb9)



## :round_pushpin: Objectives

The goals of this project are to perform **RFM analysis** and **Segmentation analysis** on the given dataset and build an interactive Sales Analytics dashboard using Tableau.



## :round_pushpin: Tools Used

The [dataset](https://www.kaggle.com/datasets/kyanyoga/sample-sales-data) :desktop_computer: used in this project is obtained from kaggle.

* Tools : Microsoft SQL Server, Tableau

* Keywords: **RFM Analysis**, **Segmentation Analysis**, **Data Visualization**, Data Interpretation, Dasboard 

* Concepts: Common Table Expression, Window Functions, GROUP BY clause, Aggregate Functions, Various charts in Tableau



## :round_pushpin: Results

The key results from the analysis are presented as follows:

* _**Preliminary Analysis Results**_:

   1. The company generated total revenue of **$10,032,629**.

   4. There were **92** unique customers.

   5. **Classic Cars** and **Vintage Cars** are the highest-selling products.

   6. According to order status, **92%** of products were shipped, and 2% were canceled.

   8. Yearly Sales Change:

      1. Sales increased by **34.32%** from 2003 to 2004.

      2. Sales dropped by **62.08%** from 2004 to 2005.

   10. The top 3 revenue-generating countries are the USA, Spain, and France.

   11. The 4th quarter has the highest product sales, with **38.62%**.



* **_RFM Analysis Results_**:


  From **customer segmentation**, it was concluded that 15% of customers were loyal, 18% were potential churners, and **22% of customers were lost**.



## :round_pushpin: Description 

1. _**Preliminary Analysis**_


Conducted a comprehensive analysis to understand key sales metrics:



* Total Sales & Orders: 
   Analyzed total sales and order count across countries.

* Order Frequency & Unique Customers: 
   Identified the most frequent ordering country and unique customer count.

* Product & Deal Size Analysis: 
  Evaluated sales performance of products and various deal sizes.

* Order Status Distribution: 
   Assessed distribution of order statuses.

* Top Performance Metrics:

* Best selling year and month.

* Year-over-year revenue changes.

* Highest selling products in peak months and by city/country.

* Top revenue-generating countries and cities.

* Sales trends by territories, quarters, and yearly product performance.

* Yearly sales differences for specific products.

  

2. _**RFM Analysis**_


 Utilized RFM (Recency, Frequency, Monetary) analysis to segment and understand customer behavior:

* Best Customers Identification: 
  Identified top customers based on purchase patterns.

* Customer Segmentation: 
  Grouped customers into segments such as best, loyal, and at-risk customers.

* Segment Distribution: 
  Calculated the percentage of customers in each segment.

* Product Combinations: 
  Analyzed frequently bought together products for bundling opportunities.



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