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Analyzed the dataset of an ecommerce store , identified the most purchased items ,the customer base of the store, the geography of the customers and overall spending pattern.

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Ecommerce-Store-Data-Report

Conducted analysis of an ecommerce platform Virnda stores using the dataset provided by Rishab Mishra(http://linkedin.com/in/rishabhnmishra/?originalSubdomain=in)

Steps I followed: 🔷 Data Cleaning: Checked for null values, spelling mistakes in the dataset

🔷 Data Processing: Created an age group consisting of teenager, adult, senior from age column and extracted month from date column.

🔷 Data Analysis: Created pivot tables which presented specific data in a tabular format making it easy to insert visualizations.

🔷 Data Visualizations: Added clustered columns, bar charts, pie charts and slicers which made it easy to draw insights from.

Key Insights: 🌎Top 3 States with the most sales are Maharashtra, Uttar Pradesh and Tamil Nadu.

📅Most amount of sales and orders recorded in the month of March.

🛒Amazon and Flipkart contributed to most amount of sales.

🥻Set, Western wear and top were among the most purchased items.

👩‍💼Women of the Adult age group are more likely to buy.

Suggestions based on the data:

1)Coduct marketing campaings targeted to women of ages 22-31 showcasing the most purchased items like the top and western wear.

2)Have sales on all your on all your ecommerce sites but if you need to cost cut and have a few sales then prioritize having them on Amazon and Filpkart.

3)To meet the supply and demand of your top 3 states, I suggest setting up a your manufacturing units in Maharastra and UP.

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Analyzed the dataset of an ecommerce store , identified the most purchased items ,the customer base of the store, the geography of the customers and overall spending pattern.

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