Discount Strategy Dashboard

An interactive business intelligence dashboard built with Quarto and Shiny with Python that serves as a sophisticated decision-making tool for optimizing discount strategies based on complex business logic and price elasticity analysis.

Overview

This dashboard transforms complex sales data into actionable discount optimization insights. It enables businesses to make data-driven decisions on discount strategies by analyzing multiple dimensions including price elasticity, customer segments, regional performance, and historical trends.

Live Dashboard

Access the live decision-making tool here: https://sajjadahmadi-discount-strategy-dashboard.share.connect.posit.cloud/

Architecture & Technology

Core Framework

• Quarto: Modern publishing system for analytical dashboards
• Shiny for Python: Interactive web application framework
• Custom CSS and JavaScript: Enhanced UI/UX

Basic Operation

1. Select the target year using the year filter
2. Choose the region for analysis (All Regions or specific region)
3. Set company strategic goals
4. Select customer priority segments
5. Review the generated discount strategy recommendations

Data Source

• dataset provided in /dataset/sample_-_superstore.csv

Code Structure

• dashboard.qmd - Main dashboard with table rendering
• components/table_logic.py - Data processing logic
• components/table_visual.py using great table to visualize the table
• Custom CSS/JS for enhanced functionality in the navbar-filter.lua and styles.css

Table Methodology

The main table uses Great Tables library with:

• Conditional formatting based on business rules
• Dynamic filtering based on user inputs
• Custom styling for better readability

Setup Instructions

1. Clone the repository
2. Install Quarto CLI
3. Install Python dependencies: pip install -r requirements.txt
4. Run the dashboard locally: quarto preview dashboard.qmd
5. Open your browser to the local server address

Deploy on Posit Cloud

1. For deploying on https://connect.posit.cloud/
2. Run quarto render --output-dir _build
3. Select shiny server
4. Choose app.py in _build folder as main python file