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I developed a comprehensive project in Excel, creating multiple dashboards and tables to analyze the data. This process involved several stages, including data preprocessing, data cleaning, and data visualization.

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Excel-Data-Analysis-projec

Project Objective

The Store wants to create an annual sales report for 2022. So that, the owner of the Vrinda store can understand their customers and grow more sales in 2026 & 2027.

Dataset used

Questions (KPIs)

  • Compare the sales and orders using single chart.

  • Which month got the highest sales and orders?

  • Who purchased more - Men or Women?

  • What are different order status in 2022?

  • List top 10 states contributingto the sales?

  • Relation between age and gender based on number of orders.

  • Which Channel is contributing maximum to the sales?

  • Highest selling category?

  • Percentage of Total Orders delivered

  • Dashboard Interaction View Dashboard

Process

  • Verify data for any missing values and anomalies, and sort out the same.
  • Made sure data is consistent and clean with respect to data type, data format and values used.
  • Created pivot tables according to the questions asked.
  • Merge all pivot tables into one dashboard and apply slicer to make dynamic.

Dashboard

Screenshot (495))

Project Insight

  • Women customers are more likely to buy products compared to men (~65%).
  • The states of Maharashtra, Karnataka and Uttar Pradesh are the top 3 product buyers.
  • The adult age group (30-49 yrs) is max contributing (~50%) and buys the most products.
  • The maximum number of products customer orders from Amazon, Flipkart and Myntra channels.
  • More than 90% of the products delivered

Final Conclusion:

To improve the sales of the Store, a strategic marketing plan focused on women aged 30-49 years residing in Maharashtra, Karnataka, and Uttar Pradesh should be implemented. This demographic represents a key consumer segment, as they often make significant household and lifestyle purchases. The approach should include targeted digital marketing campaigns and personalized promotions to capture their attention.

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I developed a comprehensive project in Excel, creating multiple dashboards and tables to analyze the data. This process involved several stages, including data preprocessing, data cleaning, and data visualization.

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