{"id":29748048,"url":"https://github.com/devanshsahu47/customer-sales-dashboard","last_synced_at":"2026-02-08T10:33:02.447Z","repository":{"id":300521461,"uuid":"1006386284","full_name":"devanshsahu47/customer-sales-dashboard","owner":"devanshsahu47","description":"Interactive Tableau dashboard analyzing customer sales trends by age, gender, region, product category, and discount behavior. 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By combining traditional BI tools with **AI assistants like PowerDrill**, the project showcases how automated analysis can enhance business decision-making.\n\n---\n\n## 📌 Objective\n\nTo generate fast, reliable, and explainable sales insights using GenAI tools and visual storytelling. This includes:\n\n- AI-powered exploration of large transactional datasets\n- Prompt-based segmentation and pattern discovery\n- Interactive Tableau visualisation for key business questions\n\n---\n\n## ⚙️ AI-Powered Workflow\n\n- 🔍 **EDA with PowerDrill (GenAI Tool)**: Used natural language prompts to generate summaries, correlation patterns, and detect outliers or segment-specific trends.\n- 💬 **Prompt Engineering**: Crafted structured prompts to auto-generate analysis on customer segments, discount impact, and category-wise performance.\n- 📊 **Visualisation**: Insights from AI were translated into human-readable dashboards via Tableau for stakeholder-ready storytelling.\n\n---\n\n## 📈 Dashboard Insights\n\n### 🔹 Month-Wise Revenue\n- Revenue peaked in **October 2020 ($57.7M)** and **April 2021 ($36.7M)**.\n- Dips in **February 2021 ($4.4M)** and **July 2021 ($19.0M)** suggest seasonal or operational shifts.\n\n### 🔹 Revenue by State\n- Top states:  \n  **Texas ($15.5M)**, **California ($13.9M)**, **Florida ($11.4M)**\n\n### 🔹 Age-Wise Sales\n- Dominant segments:  \n  - **30–40** age group – $44.8M  \n  - **60–70** – $41.1M  \n  - **20–30** – $39.9M\n\n### 🔹 Regional Revenue Distribution\n- **South** – 38.37%  \n- **Midwest** – 26.93%  \n- **West** – 17.60%  \n- **Northeast** – 17.10%\n\n### 🔹 Gender-Category Behaviour\n- **Males** prefer: Computing, Men’s Fashion, Entertainment  \n- **Females** prefer: Women’s Fashion, Others, Entertainment\n\n### 🔹 Quantity vs Discount Trend\n\n- Most orders occur at **\u003c20% discount**.\n- Some high-quantity orders at higher discounts indicate **price sensitivity** in selective segments.\n\n---\n\n## 📦 Dataset\n\n`sales_06_FY2020-21.csv` – Contains customer purchase records with:\n\n- Order Date, State, Region  \n- Age, Gender, Category  \n- Quantity, Revenue, Discount %\n\n---\n\n## 🧠 Tools \u0026 Technologies\n\n| Tool           | Purpose                          |\n|----------------|----------------------------------|\n| PowerDrill     | GenAI-driven EDA and summarisation |\n| Tableau        | Visual storytelling \u0026 dashboarding |\n| Excel/Sheets   | Light data cleanup     |\n| GitHub         | Version control and publishing     |\n\n---\n\n## 🔍 Key Business Takeaways\n\n- **Texas and California** are highest-performing states.\n- Customers aged **30–70** drive most revenue.\n- **Entertainment and Fashion** dominate sales categories.\n- **South region** outperforms others in total revenue.\n- Discounts don't significantly drive volume, except in certain outlier cases.\n\n---\n\n## 📌 AI + BI Value Add\n\nThis project demonstrates how **GenAI tools can accelerate and scale data analysis**. With minimal coding, high-level insights were derived using structured prompting, allowing the analyst to focus more on decision-making than manual query writing.\n\n---\n\n## 📝 License\n\nOpen-source under the **MIT License**.\n\n---\n\n![Customer Analysis](https://github.com/user-attachments/assets/9b865f95-f811-47a7-bb2b-28dbd7135a49)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdevanshsahu47%2Fcustomer-sales-dashboard","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdevanshsahu47%2Fcustomer-sales-dashboard","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdevanshsahu47%2Fcustomer-sales-dashboard/lists"}