Sales Analysis Using Python

The main purpose of sales analysis is to turn sales data into insights that can be used to improve a bottom line of a business. By analyzing sales data, companies can identify trends, understand what's working and what's not, and make data-driven decisions to boost sales and grow revenue.

Data Analysis

I have done the data cleaning, analysis and visualization using Python. The dataset for this analysis has been collected from different sources month-wise for a year. Then those datasets were merged using the Pandas library.

Data Questions

My objective was to collect the data from different sources and perform required analysis, and answer the following questions:

• What was the best month for Sales? How much was earned that month?
• What city had the highest number of sales?
• What time should we display advertisements to maximize likelihood of customer's buying product?
• What product was sold the most? What was the reason behind it?

IMPORTANT INSIGHTS

1. What was the best month for Sales? How much was earned that month?

December consistently achieves the highest sales compared to all other months, with total sales reaching approximately $4 million. This surge in sales can be attributed to the festive Christmas season, which significantly boosts business activity.

2. What city had the highest number of sales?

San Francisco (CA), Los Angeles (CA), and New York City (NY) account for approximately 53% of total sales, making them the top three cities in this metric.

3. What time should we display advertisements to maximize likelihood of customer's buying product?

The number of orders increased by approximately 14% around the 12th and 19th hours. Therefore, rolling out advertisements at 10-11 hours and again at 17-18 hours could significantly boost order numbers.

4. What product was sold the most? What was the reason behind it?

Together, AA Batteries (4-pack) and AAA Batteries (4-pack) are the top-selling items, contributing approximately 15% of the total sales.

CONCLUSION

To maximize the bottom line, several key strategies emerge from the sales analysis:

• Capitalize on December Sales: Focus on the festive season, especially December, which generates around $4 million in sales.

• Target Top Cities: Prioritize marketing efforts in San Francisco, Los Angeles, and New York City, as they account for 53% of total sales.

• Optimize Ad Timing: Roll out advertisements at 10-11 AM and 5-6 PM to leverage the 14% increase in orders around the 12th and 19th hours.

• Promote Best-Sellers: Highlight AA and AAA Batteries (4-pack), as they contribute 15% to total sales.

Implementing these strategies will enhance sales performance and drive revenue growth.