D2CPulse

AI-Powered Competitive Intelligence for D2C Brands

D2CPulse is an intelligent web application that provides comprehensive competitive analysis of Shopify-based D2C (Direct-to-Consumer) stores. Powered by AI and built with Next.js, it delivers actionable insights on pricing strategies, product positioning, and market analysis.

✨ Features

🤖 AI-Powered Analysis

• Conversational Interface: Natural language chat interface for store analysis
• Real-time Streaming: Instant AI responses with streaming support
• Memory Retention: Maintains conversation context across multiple queries

📊 Comprehensive Store Insights

• Pricing Strategy Analysis: Identifies luxury, premium, value, or penetration pricing
• Product Distribution: Analyzes budget, mid-range, premium, and luxury segments
• Promotional Strategy: Detects aggressive, selective, or premium no-discount approaches
• Variant Analysis: Evaluates product customization and options strategy
• Catalog Positioning: Determines niche specialist vs. broad generalist approach

🛍️ Shopify Store Intelligence

• Automatic product catalog fetching with pagination
• Collection and category analysis
• Pricing distribution and statistics
• Sale and discount detection
• Vendor and tag analysis

🚀 Getting Started

Prerequisites

• Node.js 18.x or higher
• pnpm package manager
• Access to LiteLLM API endpoint (or compatible AI service)

Installation

1. Clone the repository

   git clone <repository-url>
   cd d2cpulse

2. Install dependencies

   pnpm install

3. Configure environment variables

   Create a .env.local file in the root directory:

   LITELLM_BASE_URL=your_litellm_endpoint
   LITELLM_API_KEY=your_api_key
   LITELLM_MODEL=claude-sonnet-4-5

4. Run the development server

   pnpm dev

5. Open your browser

   Navigate to http://localhost:3000

💡 Usage

Analyzing a Store

Simply type natural language queries in the chat interface:

Analyze boat-lifestyle.com

Compare gonoise.com and nike.com

What's the pricing strategy for allbirds.com?

Example Prompts

• Single Store Analysis: "Analyze shopify-store.com"
• Pricing Insights: "What's the pricing strategy?"
• Comparative Analysis: "Compare these two stores"
• Product Strategy: "Tell me about their product range"

Understanding the Analysis

The AI provides detailed reports including:

• Overview: Total products, collections, price range
• Pricing Strategy: Average/median prices, distribution, positioning
• Product Strategy: Variant options, catalog breadth
• Strategic Insights: Promotional approach, market positioning

🏗️ Architecture

Tech Stack

• Framework: Next.js 16 with App Router
• Frontend: React 19 with Client Components
• AI Integration: @juspay/neurolink
• API: Next.js API Routes with streaming support
• Styling: CSS Modules

Project Structure

d2cpulse/
├── src/
│   ├── app/
│   │   ├── api/
│   │   │   └── chat/
│   │   │       └── route.js      # AI chat endpoint with streaming
│   │   ├── layout.js              # Root layout
│   │   ├── page.js                # Main chat interface
│   │   └── globals.css            # Global styles
│   └── lib/
│       └── shopify-analyzer.js    # Shopify store analysis logic
├── public/                         # Static assets
├── .env.local                      # Environment configuration
└── package.json

Key Components

/api/chat Endpoint

• Handles AI conversation with streaming responses
• Integrates Neurolink for LLM communication
• Automatically detects store URLs and triggers analysis
• Maintains conversation memory across requests

Shopify Analyzer (/lib/shopify-analyzer.js)

• Fetches products via Shopify's public API
• Handles pagination and rate limiting
• Calculates pricing statistics and distributions
• Generates strategic insights

Chat Interface (/app/page.js)

• Real-time message streaming
• Example prompt suggestions
• Responsive design with modern UI
• HTML rendering for formatted AI responses

🔧 Configuration

Environment Variables

| Variable | Description | Required | | ------------------ | -------------------------------------------- | -------- | | LITELLM_BASE_URL | LiteLLM API endpoint URL | Yes | | LITELLM_API_KEY | Authentication key for LiteLLM | Yes | | LITELLM_MODEL | AI model to use (default: claude-sonnet-4-5) | Yes |

Model Configuration

The application supports any model compatible with LiteLLM, including:

• Claude (Anthropic)
• GPT-4 (OpenAI)
• Custom models via LiteLLM proxy

📈 Features in Detail

Pricing Strategy Detection

The analyzer categorizes stores into:

• Luxury: Average price > ₹16,000
• Premium: Average price > ₹12,000
• Value: Average price between ₹2,400-₹12,000
• Penetration: Average price < ₹2,400

Price Distribution Analysis

Products are segmented into:

• Budget: < ₹4,000
• Mid-Range: ₹4,000 - ₹12,000
• Premium: ₹12,000 - ₹40,000
• Luxury: > ₹40,000

Strategic Insights

• Catalog Strategy: Niche specialist vs. broad generalist
• Pricing Consistency: Spread analysis across product range
• Promotional Strategy: Discount frequency and intensity
• Variant Strategy: Customization and option complexity

🛠️ Development

Build for Production

pnpm build

Start Production Server

pnpm start

Code Structure

• API Routes: Node.js runtime with dynamic rendering
• Client Components: Interactive UI with React hooks
• Streaming: Incremental response delivery for better UX
• Error Handling: Graceful degradation and user feedback

🤝 Contributing

Contributions are welcome! Please feel free to submit issues and pull requests.

📄 License

This project is private and proprietary.

🙏 Acknowledgments

• Built with Neurolink by Juspay
• Powered by AI models via LiteLLM
• Shopify public API for store data

📞 Support

For questions or support, please contact the development team.

Made with ❤️ for D2C competitive intelligence