Title

Coffee Shop Sales Analysis Report

Introduction

This report provides a visual summary of coffee shop sales data for a business presumably owned by Hemil Shah. It includes metrics such as total sales, footfall (customer traffic), average bill value, average order value, product category distribution, sales by location, and sales by month.

Data Summary

• Total Sales: $698,812.33
• Footfall: 149,116
• Average Bill Per Person: $4.68
• Average Order Per Person: $1.44

Data Visualization

• Coffee Shop Sales Analysis By Hemil Shah: This section provides an overview of key performance indicators (KPIs) such as total sales, footfall, average bill value, and average order value. It seems like Hemil Shah is the owner or manager of the coffee shop, and this section summarizes the performance of the business during the time period covered by the data.
• Quantity Ordered Hourly: This section shows the quantity of products ordered by hour of the day. This data can be used to understand customer buying patterns and staffing needs throughout the day. For example, the busiest hours might require more staff to handle the customer influx and ensure efficient service.
• CATEGORY % DISTRIBUTION BY SALES: This section shows the percentage distribution of sales across different product categories, such as bakery, tea, and coffee. This data can be helpful in understanding which product categories are the most popular and generate the most revenue. This information can be used to inform inventory management, marketing efforts, and product development.
• Transactions Per Day: This section shows the number of transactions (sales) that occurred per day. This data can be used to identify trends in customer traffic and sales volume over time. Daily transaction data can be helpful in understanding seasonal trends and fluctuations in customer demand.
• Total BIL VS Product Type: This section compares the total bill amount for different product types, such as iced coffee, hot coffee, and espresso. This data can be used to understand which product types are more profitable and drive higher sales.
• Total Sales by Location: This section shows the total sales for each store location, presumably for the coffee shop chain. This data can be used to compare the performance of different locations and identify areas for improvement. Analyzing sales by location can help identify underperforming stores that might require additional marketing efforts or changes in product offerings to improve sales.
• FootFall: This section shows the foot traffic or customer count for each store location. By comparing footfall data with sales data, the coffee shop can assess how effectively it is converting customer traffic into sales. This data can be used to evaluate the effectiveness of marketing campaigns and identify opportunities to improve conversion rates.
• Total Bill per Month: This section shows the total bill amount for each month. This data can be used to identify seasonal trends in sales and foot traffic. Monthly sales data can help with budgeting and resource allocation throughout the year.
• Total Sales Per Size of Cup: This section shows the total sales for different cup sizes, such as small, medium, and large. This data can be used to understand customer preferences for cup sizes and inform inventory management decisions.
• Total Bill per Product_Name: This section shows the total bill amount for each product name, such as Americano, Latte, and Cappuccino. This data can be used to identify the most popular and profitable coffee drinks. This information can be used to optimize pricing, promotions, and product placement.