Problem

A retail company, was struggling to optimize their sales during the Diwali season. They had a vast amount of sales data but were unable to extract meaningful insights from it. The lack of accurate data analysis led to poor inventory planning and customer targeting.

We needed to find a way to analyze the data effectively and provide actionable insights that would help our client optimize their sales strategy for the upcoming Diwali season.

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Solution

I utilized Python libraries such as pandas, Matplotlib, and seaborn to perform thorough exploratory data analysis (EDA) on the Diwali sales data. We cleaned and manipulated the data to ensure accuracy before diving into detailed EDA.

We identified top-performing products and demographics that were driving sales during the Diwali season. This allowed us to enhance customer targeting by tailoring marketing campaigns specifically towards these demographics. Additionally, I optimized inventory planning by ensuring that sufficient stock was available for high-performing products.

Impact

Increased sales revenue.
Improved inventory planning resulted in reduction in stock outs
Enhanced customer targeting led to increase in conversion rates

Team

Rushikesh Choudhari - Data Analyst
- Cleaned and manipulated data to ensure accuracy
- Performed thorough EDA using Python libraries
Rushikesh Choudhari - Marketing Strategist
- Analyzed demographics to enhance customer targeting
- Identified top-performing products for strategic inventory planning

Optimizing Diwali Sales with Data Analysis