Review Chaser

An AI-powered tool designed to help businesses analyze their website presence, generate authentic-sounding customer reviews, and manage review request campaigns via email.

Features

• Onboarding Flow:
  • Guides users through initial setup: business name, website URL.
  • Performs website analysis to extract key information (product name, description, features, target audience, industry, unique selling points).
  • Detects presence and profile URLs for major review platforms (Trustpilot, Capterra, Google, G2, Yelp) found on the site.
  • Allows refining context and configuring review generation parameters (tone, count).
  • Generates initial review suggestions.
  • Optionally allows sending a first review request.
• Dashboard:
  • Central hub for managing review generation and requests.
  • Displays website preview using Screenshot Machine.
  • Shows overview of website analysis data (product name, industry, features, USPs, detected platforms).
  • Allows editing and saving core business profile details (analysis data, platform URLs, additional AI context).
  • Provides controls to generate new review suggestions based on tone and desired count.
  • Lists generated review suggestions with details (rating, content, author, date).
  • Allows sending individual review requests via a dialog.
  • Provides options to manually update the status of a review request (e.g., New, Received).
• AI Review Generation:
  • Uses website analysis results and configurable parameters (tone, count, additional context).
  • Leverages AI to generate realistic customer reviews based on specified tone and website data.
  • Can incorporate synthetic reviewer personas for added authenticity.
  • Returns reviews with content, title, rating, author name, location, and date.
• Email Review Request Sending:
  • Sends formatted review request emails to customers via a dialog initiated from the Dashboard or Onboarding.
  • Allows selection of specific generated reviews to include.
  • Allows selection of target review platforms (with configured URLs) to include as links.
  • Provides options to customize the email template (From Name, Subject, Content, Incentive) before sending.
  • Includes variable insertion helpers ({customerName}, {productName}, etc.) for personalization.
  • Integrates with Resend for email delivery.
  • Updates review suggestion status to "Requested" upon successful sending.
  • Logs request details to a Supabase database (optional).
• AI Email Content Generation:
  • Generates email templates (subject, content, incentive) using AI.
  • Accessible within the email sending dialog for quick regeneration.
  • Takes product name and context as input.

Usage Example

Tech Stack

• Frontend: React.js, Material UI, React Router
• Backend: Node.js, Express.js
• Core Logic:
  • Website Fetching/Parsing: axios, cheerio
  • AI Analysis/Generation: OpenAI API (openai library, e.g., GPT-4o)
  • Website Screenshot: Screenshot Machine API
  • Email Sending: Resend (resend library)
  • Data Storage & Auth: Supabase (@supabase/supabase-js)
  • Fake Data Generation: @faker-js/faker (optional, for review generation)
• Development: concurrently, react-scripts

Getting Started

Prerequisites

• Node.js (v18 or later recommended)
• npm or yarn
• Access keys for OpenAI, Resend, Screenshot Machine, and Supabase.

Installation

1. Clone the repository:

   git clone <repository_url>
   cd review-chaser

2. Install dependencies:

   # Install root, backend, and frontend dependencies
   npm install
   cd backend && npm install && cd ..

   (Or use yarn install in each directory)

3. Set up environment variables: Create a .env file in the root directory. Add the following variables, replacing placeholders with your actual keys:

   # OpenAI API Key (Required for analysis, review generation, email content generation)
   OPENAI_API_KEY=your_openai_api_key
   
   # Resend API Key (Required for sending review request emails)
   RESEND_API_KEY=your_resend_api_key
   
   # Email Sender Details (Required for sending review request emails)
   FROM_NAME="Your Company Name"
   FROM_EMAIL=noreply@yourdomain.com
   
   # Supabase Credentials (Required for storing profile data, reviews, auth)
   REACT_APP_SUPABASE_URL=your_supabase_project_url
   SUPABASE_SERVICE_ROLE_KEY=your_supabase_service_role_key # Ensure this key has appropriate table permissions
   REACT_APP_SUPABASE_ANON_KEY=your_supabase_anon_key
   
   # Screenshot Machine API Key (Required for website previews in Dashboard/Onboarding)
   REACT_APP_SCREENSHOT_MACHINE_API_KEY=your_screenshot_machine_api_key

   Note: Ensure your Supabase database has the business_profiles table (and potentially review_requests if logging separately) set up according to the application's needs.

Running the Application

1. Ensure Ports 3000 & 3001 are free: Stop any previous instances if necessary.
2. Start both backend and frontend:

   # From the root directory
   npm run dev

3. Open your browser and navigate to http://localhost:3000. You should be redirected to the login/signup page or the dashboard if already logged in.

API Endpoints (Backend - localhost:3001)

• POST /api/analyze-website: Analyzes a website URL.
  • Body: { "url": "string" }
• POST /api/build-context: (Potentially deprecated if analysis handles full context) Refines context based on analysis.
  • Body: { "analysisResult": object, "additionalContext": "string" }
• POST /api/generate-reviews: Generates AI reviews based on website data and parameters.
  • Body: { "websiteUrl": "string", "reviewCount": number, "tone": "string", "additionalContext": "string", "analysisResult": object, "productName": "string" } (Structure might vary slightly)
• POST /api/generate-email-content: Generates specific email parts (subject, content, incentive).
  • Body: { "type": "subject"|"content"|"incentive", "productName": "string", "context": "string", "reviewContent"?: string, "reviewRating"?: number }
• POST /api/send-review-request: Sends a formatted review request email.
  • Body: { "reviewRequest": object, "emailData": object } (See src/api/reviewRequests.js or backend route for detailed structure)

Contributing

1. Fork the repository
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