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https://github.com/ankita-selokar/tata-data-visualisation-empowering-business-with-effective-insights


https://github.com/ankita-selokar/tata-data-visualisation-empowering-business-with-effective-insights

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# Data Transformation and Revenue Insights for TATA Retail Store



## Introduction:

This project involves analyzing transactional data from a retail store to generate insights that assist the CEO and CMO in decision-making. The dataset includes columns like InvoiceNo, StockCode, Description, Quantity, InvoiceDate, UnitPrice, CustomerID, and Country, with some missing or erroneous values, such as negative quantities, zero unit prices, and missing customer IDs. Using data transformation techniques, the bad data was cleaned to ensure an accurate analysis for key business questions.



## Problem Statement:

The retail store aims to understand seasonal revenue trends, identify top revenue-generating countries and customers, and assess product demand across regions for future growth and expansion. The analysis focuses on providing insights to both the CEO and CMO by answering the following business questions:



### Question 1: Revenue Trends and Seasonality (For CEO)

The CEO is interested in understanding the seasonal trends in the store’s revenue for the year 2011, with a granular month-by-month breakdown. This analysis will help forecast next year’s sales and strategize around seasonal fluctuations.



![Alt text](https://github.com/Ankita-Selokar/Tata-Data-Visualisation-Empowering-Business-with-Effective-Insights/blob/main/Visuals/q1.jpg)



#### Insight:



* The first eight months of 2011 showed steady revenue, averaging around $685,000 per month.

* A sharp increase in revenue started in September, with a 40% rise over the previous month, peaking in November at approximately $1.5 million. This indicates that the last four months are highly influenced by seasonal trends, likely due to holiday shopping.

* The incomplete December data restricts further analysis for that month.



#### Recommendations:



The CEO can use this information to focus on ramping up marketing and inventory management in the last quarter of the year, which has proven to be the peak sales season.



### Question 2: Top Revenue-Generating Countries (For CMO)



The CMO wants to identify the top 10 countries generating the highest revenue (excluding the United Kingdom) and understand the correlation between quantity sold and revenue to identify high-potential markets.



![Alt text](https://github.com/Ankita-Selokar/Tata-Data-Visualisation-Empowering-Business-with-Effective-Insights/blob/main/Visuals/q2.jpg)



#### Insight:



* Countries like the Netherlands, Ireland, Germany, and France stand out as the highest revenue contributors.

* These countries also show high unit sales, suggesting consistent demand for the products in these regions.



#### Recommendations:



The CMO should focus marketing efforts and product offerings in these countries to capitalize on the existing demand and drive further growth. With high sales volume and revenue generation, these markets show great potential for expansion.



### Question 3: Top Revenue-Generating Customers (For CMO)



The CMO is interested in identifying the top 10 customers by revenue to prioritize customer retention strategies for high-value clients.



![Alt text](https://github.com/Ankita-Selokar/Tata-Data-Visualisation-Empowering-Business-with-Effective-Insights/blob/main/Visuals/q3.jpg)



#### Insight:



* The top 10 customers do not show a significant difference in purchasing volume, with the highest customer generating only 17% more revenue than the second highest.

* This spread indicates that revenue generation is well-distributed among key customers, minimizing dependency on any single client.



#### Recommendations:



Customer retention efforts should target all top 10 customers equally, as each contributes significantly to the revenue stream. Personalizing product offerings and maintaining customer satisfaction will be key to securing continued revenue from these high-value customers.



### Question 4: Product Demand Across Regions (For CEO)



The CEO seeks insights into product demand across different regions (excluding the UK) to identify areas for potential expansion.



![Alt text](https://github.com/Ankita-Selokar/Tata-Data-Visualisation-Empowering-Business-with-Effective-Insights/blob/main/Visuals/q4.jpg)



#### Insight:



* The highest demand regions outside the UK are the Netherlands, Ireland, Germany, France, and Australia, where revenue generation is high.

* Most sales are concentrated in Europe, with minimal sales in the Americas and no noticeable demand in Africa, Asia, or Russia.



#### Recommendations:



The CEO can use these insights to develop a targeted expansion strategy, focusing on Europe, with secondary attention to unexplored regions like Asia and the Americas. Penetrating these new markets could drive substantial future revenue growth.



## Conclusion:

The analysis provides valuable insights for TATA’s leadership, allowing them to understand seasonal revenue trends, identify top-performing markets and customers, and explore new opportunities for regional expansion. With this data-driven strategy, the store can refine its operations, marketing efforts, and customer retention tactics, ensuring continued growth and profitability.



## Completion Certificate:



![Alt text](https://github.com/Ankita-Selokar/Tata-Data-Visualisation-Empowering-Business-with-Effective-Insights/blob/main/Visuals/Tata%20Group_Data_Visualisation_certificate_page-0001%20(1).jpg)