https://github.com/harshindcoder/ice_cream_customer_analysis

This project helps analyze ice cream sales and customer preferences using MySQL for data storage and Tableau for visualization. By examining flavor popularity, age demographics, and regional trends, businesses can make data-driven decisions to improve sales and customer satisfaction.
https://github.com/harshindcoder/ice_cream_customer_analysis

Last synced: 4 months ago
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This project helps analyze ice cream sales and customer preferences using MySQL for data storage and Tableau for visualization. By examining flavor popularity, age demographics, and regional trends, businesses can make data-driven decisions to improve sales and customer satisfaction.

• Host: GitHub
• URL: https://github.com/harshindcoder/ice_cream_customer_analysis
• Owner: harshindcoder
• License: mit
• Created: 2025-03-25T06:33:06.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2025-03-25T06:47:17.000Z (about 1 year ago)
• Last Synced: 2025-07-30T06:40:03.429Z (11 months ago)
• Homepage:
• Size: 212 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# 🍦 Ice Cream Customer Analysis

## 📌 Overview

This project aims to analyze **customer preferences for ice cream flavors** using a structured **data lifecycle approach**. The goal is to help an ice cream company understand customer trends and improve decision-making. The dataset was provided by the **manager**, and the analysis is based on real customer data.

---

## 📊 Data Lifecycle Process

### **1️⃣ Plan: Defining the Data Needs**

The company needs to understand its customers' ice cream preferences. To achieve this, we collect the following data:

- **Date & Time** – When the ice cream was purchased.

- **Flavor** – The type of ice cream bought.

- **Price** – The cost of the ice cream.

- **Reason** – If the customer provided a reason for their purchase.

- **Customer Age** – To analyze preferences by age group.

- **Customer Location** – Includes latitude and longitude.

- **Rating** – Customer rating (1-5) for the ice cream flavor.

**Expected Insights:**

✅ Popular flavors by season, age, and location.  

✅ Price impact on sales.  

✅ Customer satisfaction trends.

---

### **2️⃣ Capture: Collecting the Data**

- Data is collected at the point of sale.

- Customers are asked if they are willing to provide details.

- The location data is retrieved based on the store's location.

---

### **3️⃣ Manage: Storing and Securing Data**

- The data is stored in a **MySQL** relational database for structured querying.

- Secure access controls are implemented to protect sensitive information.

- Regular backups are maintained to prevent data loss.

---

### **4️⃣ Analyze: Extracting Insights**

- **Tools Used:** MySQL, Tableau.

- **Analysis Performed:**

  - Popular flavors among different age groups.

  - Trends in ice cream sales based on time, season, and location.

  - Customer satisfaction ratings and feedback.

  - Heatmap of ice cream purchases by region.

---

### **5️⃣ Archive: Managing Old Data**

- Data older than **3 years** is archived for historical reference.

- **Summarized reports** are generated for long-term insights.

- Older datasets are stored in **seperate Hard Drives** for cost-effective storage.

---

### **6️⃣ Destroy: Removing Unnecessary Data**

- Data is deleted if it is no longer needed for analysis.

- Personal customer details are **anonymized** before deletion.

- Secure deletion methods (e.g., data wiping) are used to ensure compliance with regulations.

---

## 📈 Data Analysis & Dashboard

We created a **Customer Rating Analysis Dashboard** in Tableau to visualize the findings.

**🔗 View the Dashboard Here:** [Ice Cream Sales Dashboard](https://public.tableau.com/app/profile/harsh.indoria/viz/IceCreamSalesDashboard_17428764631180/IceCreamDashboard)

### **Key Insights from the Dashboard**

- The **most popular ice cream flavors** based on location.

- **Which age groups eats most in which area**.

- **Heatmaps of sales locations** to identify high-demand areas.

- **Seasonal Trends** for flavors in different locations.

## 📢 Conclusion

This project provides valuable insights into **customer ice cream preferences** using a structured data analysis approach. The findings can help the company optimize flavors, pricing, and marketing strategies based on real customer behavior.

✅ If you found this project useful, **star this repo ⭐** and contribute with suggestions!