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A professional LinkedIn analytics tool for tracking post performance with deterministic metrics. 100% ToS compliant—no scraping, no automation. Built with Next.js, Tailwind CSS, and Firebase.

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Postlytic Logo

Postlytic

The Deterministic LinkedIn Post Performance Tracker

License: MIT Next.js TypeScript Tailwind CSS Firebase

View Demo · Report Bug · Request Feature


🚀 Overview

Postlytic is a professional-grade analytics tool designed for creators who want to track their LinkedIn post performance without risking their account. unlike other tools that use scraping (which violates LinkedIn's ToS), Postlytic relies on deterministic, manually entered data to provide 100% safe, transparent, and accurate insights.

Why Postlytic?

  • 🛡️ 100% ToS Compliant: No scrapers, no bots, no automated login attempts.
  • 📈 Deterministic Metrics: We track exactly what you see, calculating growth velocity and momentum with precision.
  • 🧠 AI-Powered Insights: Integrated research agents to analyze content DNA.
  • ⚡ Real-time Snapshots: Track the "Golden Hour" performance of your posts.

✨ Key Features

  • Advanced Dashboard: Visualise metrics like Engagement Rate, Velocity, and Momentum Score.
  • Content DNA Analysis: Analyze the structure, tone, and readability of your posts.
  • Growth Tracking: Record snapshots over time to generate growth curves.
  • Benchmark Comparison: Compare new posts against your historical averages.
  • Professional Reports: Export PDF briefs for clients or stakeholders.
  • Mobile Responsive: Fully functional mobile experience with a dedicated drawer navigation.
  • SEO Optimized: Built with advanced SEO practices including JSON-LD and Open Graph tags.

🛠️ Tech Stack

  • Framework: Next.js 14 (App Router)
  • Language: TypeScript
  • Styling: Tailwind CSS with a custom design system.
  • Backend/Auth: Firebase (Auth, Firestore, Functions).
  • Deployment: Vercel.
  • AI Integration: Custom agents for content analysis.

🏁 Getting Started

Prerequisites

  • Node.js 18+
  • npm or yarn
  • A Firebase project

Installation

  1. Clone the repository

    git clone https://github.com/tahsinmert/linkedin-post-analytics.git
    cd linkedin-post-analytics
  2. Install dependencies

    npm install
  3. Configure Environment Variables Create a .env.local file in the root directory:

    NEXT_PUBLIC_FIREBASE_API_KEY=your_api_key
    NEXT_PUBLIC_FIREBASE_AUTH_DOMAIN=your_project.firebaseapp.com
    NEXT_PUBLIC_FIREBASE_PROJECT_ID=your_project_id
    NEXT_PUBLIC_FIREBASE_STORAGE_BUCKET=your_bucket
    NEXT_PUBLIC_FIREBASE_MESSAGING_SENDER_ID=your_sender_id
    NEXT_PUBLIC_FIREBASE_APP_ID=your_app_id
  4. Run the development server

    npm run dev

Open http://localhost:3000 with your browser to see the result.


📂 Project Structure

├── app/                  # Next.js App Router pages
│   ├── app/              # Protected dashboard routes
│   ├── api/              # API routes
│   └── ...
├── components/           # Reusable UI components
│   ├── agents/           # AI analysis components
│   ├── analysis/         # Charts and dashboards
│   └── ui/               # Core design system (Buttons, Inputs, etc.)
├── lib/                  # Utilities and services
│   ├── firebase/         # Firebase config
│   ├── services/         # Business logic
│   └── utils/            # Helper functions
└── public/               # Static assets

🤝 Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

Please verify the CONTRIBUTING.md for detailed instructions.

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

📜 License

Distributed under the MIT License. See LICENSE for more information.


❤️ Acknowledgments

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A professional LinkedIn analytics tool for tracking post performance with deterministic metrics. 100% ToS compliant—no scraping, no automation. Built with Next.js, Tailwind CSS, and Firebase.

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