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We provide solutions for developers to ship out websites to clients with dashboards that contain information about micro-interactions (user clicks and mouse movement) on their websites. Team members: Peter Larcheveque, Eric DiMarzio, David Naymon, Saw Naing

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Pie Chart Icon

OS Analytics

OS Analytics is a powerful and easy-to-use tool designed to monitor user interactions on websites. By integrating a custom clickTracker hook, developers can capture and visualize user activity data in real-time. This data helps developers better understand user behavior, optimize their apps, and make informed decisions based on analytics. With a robust dashboard that filters and exports data, you can track, manage, and visualize user interactions effectively.

ReadME For Incorporating AI

Please read the README for detailed instructions on incorporating AWS Bedrock into your dashboard.

🛠️ Tech Stack

React JavaScript TypeScript Node.js Express.js AWS MUI Chart.js React Flow AWS Bedrock AWS Cognito JWT PostgreSQL Crypto Jotai CSS Passport Google OAuth Dagre (React Flow) HTML to Image UUID Vite GitHub Axios Puppeteer Framer Motion

What we offer

Feature Status
Integration of clickTracker hook to monitor user clicks and interactions
Real-time data collection and visualization in the OS Analytics dashboard
Filters and export functionality added to the dashboard for reporting and the ability to drill down into specific user interactions and activities based on detailed, custom metrics for enhanced analysis capabilities
Secure data tracking using JWT authentication
Ability to configure multiple websites for tracking in the dashboard
Implemented AWS Bedrock for generating user activity reports
Fully documented API for developers to integrate and manage the tracking tool

Key Features

Dashboard Overview

The dashboard provides a clear and intuitive layout for monitoring click analysis data, with charts and metrics that track user interactions and website performance over time.

dashboard-one

AI-Generated Reports

This feature allows users to generate and save AI-driven reports that provide detailed insights and actionable recommendations based on the collected click data.

dashboard-Ai

Heatmap Visualization

This heatmap visualizes click data by overlaying signatures on a website, highlighting areas of high activity and helping identify key user behavior patterns.

Heatmap

Click Data Playground

The React Flow playground provides a tree diagram and frequency chart to visualize click data, allowing users to easily identify where clicks occurred most frequently on their site.

Playground

Securing Your Credentials

Your AWS credentials are securely stored in our database using encryption, ensuring they remain protected and accessible only to you.

Getting Started

  1. To get started, visit os-analytics and create an account. After account creation, you will be directed to an onboarding page which will guide you through the steps below.

  2. Install the OS Analytics package in your React application:

    NPM install os-analytics:

    npm install os-analytics
  3. Integrate the clickTracker hook into your application:

    Import clickTracker in your main React component:

    import clickTracker from 'os-analytics';

    Initialize the tracker with your API key and website at the top level (App):

    const apiKey = '<your-api-key>';
    const website = '<your-website-url>';
    
    clickTracker(apiKey, website); // Start tracking clicks and interactions
  4. Run your application:

    Once you've integrated the clickTracker and set up the environment variables, run your application as usual. The clickTracker will automatically start tracking user interactions on your website.

  5. View Tracked Metrics:

    After interacting with your website, visit your OS Analytics Dashboard to view the tracked metrics in real-time. You can filter, analyze, and export the data as needed.

Tracked Metrics

  • Click events
  • Referrer events
  • Page views per website
  • Website views per account
  • Heatmap
  • Other event tracking: OS/Browsers

The team

Eric

Eric DiMarzio

GitHub | LinkedIn
Peter

Peter Larcheveque

GitHub | LinkedIn
David

David Naymon

GitHub | LinkedIn
Saw

Saw Yan Naing

GitHub | LinkedIn

About

We provide solutions for developers to ship out websites to clients with dashboards that contain information about micro-interactions (user clicks and mouse movement) on their websites. Team members: Peter Larcheveque, Eric DiMarzio, David Naymon, Saw Naing

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