This project analyzes the sales data of a coffee shop, focusing on identifying sales trends, top product categories, and customer behavior patterns. The insights derived from this analysis will help in optimizing inventory, designing targeted marketing strategies, and improving overall customer satisfaction.
- Analyze total sales, total orders, and total quantity.
- Identify the top product categories and best-selling products.
- Examine sales patterns across different days of the week and hours of the day.
- Provide actionable recommendations for enhancing sales and customer experience.
- Data Sources: Sales transactions, product metadata, and customer purchase history.
- Data Description: The dataset includes daily sales figures, the number of orders, the quantity of products sold, and details of different product categories.
- Data Preparation: Data cleaning involved handling missing values and ensuring correct categorization of products.
- Analysis Techniques: Descriptive statistics, trend analysis, and product categorization.
- Tools and Technologies: SQL for data extraction, Power BI and Power Query for data cleaning and data analysis, and visualization.
- Total Sales: $157K, representing a 7.14% increase compared to the previous month.
- Total Orders: 33.53K, with a 4.18% increase month-over-month (MOM).
- Total Quantity Sold: 48.23K items, a 6.18% increase MOM.
- Food: Highest sales category with $62.65K.
- Hot Beverages: Second highest with $46.87K.
- Drinking: Significant contributor with $24.89K.
- Merchandise: Lower but steady sales with $11.22K.
- Others: Modest sales of $9.2K.
- Gourmet Flavored Coffee Beans: Highest selling product with 917 sales.
- Other top products include premium coffee blends, pastries, and specialized tea blends.
- Daily Sales: Observed consistent sales with spikes on specific days.
- Weekend vs. Weekday Sales: Weekend has less sales than weekday.
- Sales by Days/Hours: Peak sales hours were during the mornings and late afternoons, with noticeable sales during lunch breaks.
The analysis shows that food and hot beverages are the top-performing product categories, with weekends generating lower sales than weekdays. The most popular products include gourmet coffee beans and specialized pastries. Recommendations include optimizing inventory for high-demand products and considering the introduction of new items based on sales patterns and customer preferences. Additionally, targeted marketing campaigns during peak sales hours and weekends can further enhance customer engagement and sales growth.
- Sales Transaction Data
- Product Metadata Documentation.
- Customer Purchase History Reports.
