https://github.com/maiserry/shopping_company_report

to interact with report
https://github.com/maiserry/shopping_company_report

dax powerbi powerquery xlxs

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• Host: GitHub
• URL: https://github.com/maiserry/shopping_company_report
• Owner: MaiSerry
• Created: 2025-04-11T17:46:25.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2025-04-11T20:02:34.000Z (about 1 year ago)
• Last Synced: 2025-05-07T17:20:03.656Z (about 1 year ago)
• Topics: dax, powerbi, powerquery, xlxs
• Homepage: https://app.powerbi.com/view?r=eyJrIjoiZjZkNzQxYWEtZWM0Ny00ZDNkLWI3ZTktMjliNzBhN2JlNjc3IiwidCI6ImVhZjYyNGM4LWEwYzQtNDE5NS04N2QyLTQ0M2U1ZDc1MTZjZCIsImMiOjh9
• Size: 30.3 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Shopping_Company_Report 

### 📊 **Key KPIs:**

- **Total Sales**: **256M**

- **Total Quantity Sold**: **220K**

- **Average Product Price**: **23.03 EGP**

- **Top Performing Employee (Sales)**: **Amgad – 29.1M EGP**

- **Top Outlet (Sales)**: **ماركت حسن – 6M EGP**

- **Sales by Outlet Type**:

  - Retail (تجزئه): **230M (89.73%)**

  - Wholesale (جمله): **26M (10.27%)**

- **Top Selling Product**: Likely **Detergent 1L discounted**, followed by **Detergent 50ml**

---

### 📌 **Key Insights:**

#### 🛍️ **Sales Performance**

- **Detergents dominate** sales (~172M EGP), followed by **soap (~75M)** and **shower gels (~9M)**.

- A **few top products** account for a large portion of sales, especially in detergent and soap categories.

- There's a noticeable impact from **discounted products**, which likely drive higher volumes.

#### 📍 **Outlet Insights**

- Retail outlets (تجزئه) are the primary sales channels.

- **Top outlets** collectively contribute over **23M EGP** in sales with relatively **low volume**, suggesting high-value transactions or repeat bulk buyers.

  

#### 👥 **Employee Performance**

- Strong concentration of sales among **top 5 employees**, each generating **24M–29M** EGP in sales.

- Distribution of sales per employee shows some disparity; sales training or incentive focus could be useful.

#### 🗓️ **Temporal Trends**

- **Monday** is the strongest sales day (~47M), while **Friday** is the weakest (~2M).

- Regular weekly trends could inform **promotions and staffing**.

#### 🧭 **Warehouse & Logistics**

- **DB3 and DB1** handle the highest number of products (53K and 38K, respectively).

- Visits are highest in **Delta**, indicating it’s the most active region.

- Average **visit duration** is **23 seconds**, suggesting fast transactions or minimal in-warehouse customer interaction.

---

### 🚀 Recommendations:

1. **Focus on retail channels**, as they’re the largest contributors.

2. **Leverage discount strategies** for soaps and detergents to boost volume.

3. **Boost underperforming weekdays** like Friday with offers or campaigns.

4. **Recognize top-performing staff** and consider mentoring models.

5. **Optimize warehouse operations** based on product and visit distribution.