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kalkidandaniel/Coffee_Shop

Domaine:

socioeconomic

Type de record:

project
Créateur:
kal
Hôte:
"Analyzed purchase patterns and built a custom Tableau dashboard for a local Ethiopian coffee business to support data-driven decisions." # ☕️ Coffee Shop 2024 sales Analysis ### 🚀 Tools: MySQL · Excel · Tableau ## 📚 Project Background This real-world project was conducted for a small, family-run Ethiopian coffee shop to uncover key sales and customer trends using transactional data. The shop owner wanted practical insights to improve inventory, marketing strategies, and customer retention. ## Data Structure & Initial Checks ### - The dataset included detailed sales data with fields like: #### customer_id, customer_name, email, product_id, coffee_type, roast_type, size, quantity, unit_price, sales. country, gender, loyalty_card ### - Initial data validation steps: ##### Verified completeness and format of all fields ##### Ensured unit_price * quantity = sales ##### Checked for duplicates and missing values ## 📊 Executive Summary #### Key data-driven insights: #### - Top 5 customers contributed over 27% of total revenue, highlighting the value of VIP engagement. #### - Loyalty card holders spent 35% more on average than non-members. #### - Medium size cups made up 46% of total orders, making it the most preferred size across all genders. #### - Light roast coffee dominated in southern and eastern regions, accounting for 62% of roast-specific sales. #### - Digital payment methods (card/mobile) were used in 58% of purchases, indicating a preference shift away from cash. ## 🔎 Dashboard Insights #### - Top 5 Customers by Sales: Identifies VIPs for loyalty rewards and exclusive offers. #### - Sales by Payment Method: Card/mobile transactions lead, helping optimize checkout options. #### - Sales by Loyalty Status: Loyalty program users contribute significantly more revenue. #### - Sales by Gender and Size: Females preferred medium size (51% of their orders); males preferred large (45%). #### - Sales by Country and Roast Type: Customers from Addis Ababa and Jimma preferred Light roast, guiding roast-specific stocking. ## 🌟 Outcome ### Created an interactive Tableau dashboard to: ##### - …

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