Oil has powered industries for over a century now; however, it is time for change.
The very end product of oil is fumes consisting of anthropogenic gases that contribute to global warming as a result of the depletion of the ozone layer. Therefore, there had to be a change that both boomed the economy of the world and was very eco-friendly and available everywhere for easy access.
This is how I used data to fuel and drive innovation in sales on my sales analysis project.
The purpose of the project was to identify trends in sales data, top selling products and revenue metrics for optimal business decision-making. Excel, PowerBI, Mathematics and statistics were used as major tools for the project.
At the end of the refinery, these are some of the invaluable discoveries:
Firstly, the top net profit is 1.0058%, which is equal to 0.347k after a year, In other words, this is the profit margin of the products sold. Calculating the profit margin is crucial for evaluating the financial performance of products or services. However, this is how you can go about it as an emerging data analyst:
Gross profit = revenue - cost of goods sold (COGS).
Secondly, I discovered that the top three selling products are the MacBook Pro, iPhone, and ThinkPad laptops in terms of merit. To find that, calculate the total revenue generated by each of the top-selling products. This involves multiplying the unit price of each product by the quantity sold. Analyze the profitability of each top-selling product by comparing their revenue to the associated costs, including the cost of goods sold and any additional expenses related to marketing, distribution, or fulfillment. Then, use the previously mentioned steps to calculate the gross profit margin for each top-selling product. This helps determine how much profit each product generates relative to its revenue.
Thirdly, whereas batteries and wired headphones made the least of sales. In order of merits, the cities that patronized more products are San Francisco, Los Angeles, and New York City. The highest sales were thus recorded in the month of December, in the fourth quarter of the year.
To add to that, the highest number of products (maximum of sales) sold generated the highest sales, with over 3.40k, whereas the reverse is 2.99k.
Lastly, the coefficient of variation is 1.68, indicating that there will be a drastic increase in the series of fluctuations in sales and revenue.
Recommendations
the recommendations will be shared in part 2 of the blog post.