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I developed a detailed project in Excel, creating multiple dashboards and tables to analyze and interpret the data. The project included several key stages, such as data preprocessing, cleaning, and visualization, ensuring the data was organized, accurate, and effectively presented.
Tushaar8/Data-Analysis-Dashboard
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The Nexus Store wants to create an annual sales report for 2022. So that, the owner of the The Nexus store can understand their customers and grow more sales in 2023 & 2024.
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 InteractionView Dashboard
- 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.
- 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
To boost the sales of Vrinda Store, a strategic marketing plan targeting women aged 30-49 in Maharashtra, Karnataka, and Uttar Pradesh should be implemented. This demographic is a key consumer segment, as they frequently make significant household and lifestyle purchases. The plan should include targeted digital marketing campaigns and personalized promotions to attract their attention.
About
I developed a detailed project in Excel, creating multiple dashboards and tables to analyze and interpret the data. The project included several key stages, such as data preprocessing, cleaning, and visualization, ensuring the data was organized, accurate, and effectively presented.