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kunadusarpong/tasty_bites_analysis

Domain:

socioeconomic

Record type:

dataset
Creator:
kun
Host:
Sales and customer analysis for a growing restaurant in Accra using Excel, MySQL, and Power BI. # Tasty Bites Sales & Customer Analysis ## Project Overview This project analyses sales and customer data for Tasty Bites, a growing restaurant in Accra, Ghana. The analysis was conducted to understand sales performance, customer behaviour, menu performance, and factors associated with changes in restaurant performance. The dataset contains **243 daily records covering July 2024 to February 2025**. ## Business Questions * How did sales and customer traffic change over time? * Which menu items were most frequently recorded as the top-performing items? * How did weather conditions relate to sales and customer traffic? * Did promotional days perform better than non-promotion days? * Which menu items received the highest customer feedback? * What characteristics were associated with the restaurant's highest-sales days? ## Tools Used * **Excel** – Data preparation and initial analysis * **MySQL** – Data exploration and SQL analysis * **Power BI** – Data visualization and dashboard development ## Key Findings * Total sales during the period amounted to **GHS 1.32 million**, with **32,301 customers served**. * Average customer spend was approximately **GHS 40.96**, while the average customer feedback score was **4.53/5**. * Monthly sales increased from July 2024 and reached a peak of **GHS 189,000 in October 2024**, before declining in November. * **Rainy days recorded the highest average daily sales (GHS 5,865.75)** compared with cloudy and sunny days. * Promotion days recorded higher average daily sales and customer traffic than non-promotion days. * **Fufu & Light Soup** recorded the highest average daily sales when it was the top menu item. * **Banku & Fish** received the highest average customer feedback score of **4.79/5**. * The majority of the highest-sales days occurred on **weekends**, particularly Sundays. ## Recommendations * Schedule additional staff and increase inventory on busiest days – Saturday & Sunday. * Investigate the factors contributing t …

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