Files

andrei 0e2e1bddba Add xlsxwriter-based Excel generation scripts with openpyxl implementation

- Created create_excel_xlsxwriter.py and update_excel_xlsxwriter.py
- Uses openpyxl exclusively to preserve Excel formatting and formulas
- Updated server.js to use new xlsxwriter scripts for form submissions
- Maintains all original functionality while ensuring proper Excel file handling

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

2025-09-22 13:53:06 +00:00

2.3 KiB

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Retail Media Business Case Calculator

This application helps retail media professionals generate business cases by collecting key metrics and calculating potential reach and impressions across different channels.

Features

Clean, user-friendly form for collecting retail media data
Automatic calculation of key metrics:
- Potential reach in-store (digital screens and radio)
- Unique impressions in-store
- Potential reach on-site
- Unique impressions on-site
- Potential reach off-site
- Unique impressions off-site
Results saved to a JSON file for reporting
Thank you page with confirmation message

Installation

Clone the repository
Install dependencies:

npm install

Running the Application

Start the server:

npm start

For development with auto-restart:

npm run dev

The application will be available at http://localhost:3000

Project Structure

index.html - Main form interface for collecting user data
thank-you.html - Confirmation page after form submission
server.js - Express server handling form submissions and routing
index.js - Business logic for calculating retail media metrics
config.json - Configuration file with constants and coefficients
results.json - Output file where calculation results are stored
public/ - Static assets directory

How It Works

Users fill out the business case form with their retail media data
The form validates input and submits data to the server
Server processes the data using formulas in index.js
Results are saved to results.json and user is redirected to thank-you page
Retail media specialists follow up with the user with a customized business case

Technologies Used

Node.js and Express for the backend
HTML/CSS/JavaScript for the frontend
TailwindCSS for styling
Vanilla JavaScript for form validation and interactions

Configuration

The application uses a config.json file that contains constants and coefficients for the formulas. You can modify these values to adjust the calculation logic.

Development Notes

Form styling uses a clean white design with accent colors
Form validation ensures complete and accurate data collection
The server includes error handling for form submissions
Calculations are based on industry-standard formulas for retail media

2.3 KiB Raw Blame History