Diwali Sales Analysis

About this project

About the Data:

The dataset contains the sales data of different products in India. This data has been taken from the Kaggle dataset. The dataset contains information regarding the age, state, product, occupation, marital status, amount of purchase, product ID, customer name, and Number of orders per user ID.

This analysis will be an exploratory data analysis and we will try to figure out some important insights from the data to make a data-driven decision.

Problem Statement:

Identify trends in Diwali sales data to apply insights to company X's marketing strategy.

Shareholders:

Following are the key stakeholders of the data

Company X's CFO and CEO Company X's marketing team

Research questions:

1. How can marketing teams leverage Diwali sales data to enhance sales strategies?

2. Which age groups exhibit the strongest affinity for Diwali shopping?

3. Does marital status play a significant role in Diwali purchasing decisions?

4. Which Indian states present the most favorable advertising opportunities for company X to maximize Diwali sales?

5. What product categories are most sought after by consumers during Diwali?

Process:

Python will be focused here due to the accessibility, amount of data, and the ability to create data visualization to share the results with stakeholders.

Conclusion:

• Gender Disparity in Purchasing Power: Females constitute the majority of buyers and demonstrate a higher purchasing power compared to males. This indicates a potential inclination towards certain products or marketing strategies tailored to the female demographic.

• Age Group Preferences: The age group of 26-35 stands out as the most active in terms of making purchases, contributing significantly (approximately 40%) to total sales. Moreover, within this age group, females seem to dominate the purchases related to Diwali products. Understanding this can help refine product offerings and marketing approaches for this age cohort.

• Inactive Buyer Segment: The older age group (55+) appears to be the least active in making purchases. This information could prompt strategies aimed at engaging or tailoring products/services to attract this demographic.

• Regional Sales Distribution: The regions of Uttar Pradesh, Maharashtra, and Karnataka drive the highest number of orders and sales. This insight could guide regional-specific marketing campaigns or efforts to better cater to the preferences of customers in these areas.

• Marital Status Impact on Sales: Unmarried females contribute the most to sales, followed by married females. This knowledge could inform targeted marketing strategies or product development tailored to these specific demographic segments.

• Professions of Buyers: The majority of buyers work in IT, Healthcare, and Aviation sectors. This understanding can be crucial in tailoring products or services that align with the needs or interests of professionals in these fields.

• Product Category Insights: The top three sales-generating product categories are Food, Clothing, and Electronics. Interestingly, while Clothing and apparel exhibit the highest number of orders, the Food category contributes the most to the total sales. This discrepancy suggests potential variations in pricing or purchasing patterns between these categories, indicating room for optimization in pricing strategies or marketing approaches.

Suggestions:

Given the findings highlighting the significant presence and purchasing power of the female demographic, it's highly recommended that the marketing team amplifies its campaigns with a focused approach toward engaging and appealing to this demographic. Understanding that females are not only the majority of buyers but also exhibit considerable purchasing power, tailoring marketing strategies specifically designed to resonate with their preferences and needs can yield substantial benefits. This targeted approach has the potential to enhance brand engagement, product adoption, and overall sales performance within this crucial consumer segment.