GitHub Repo Link

Building an AI-Powered Shopping Assistant: DealDetectiveAI

Introduction

In today’s fast-paced digital world, online shopping has become a daily activity for many. With countless retailers, fluctuating prices, and a vast selection of products, finding the best deals can be overwhelming. To address this, I developed DealDetectiveAI, an AI-powered shopping assistant that simplifies the online shopping experience by integrating personalized recommendations, price comparisons, and AI-driven insights.

In this blog, I will walk you through the inspiration, core features, tech stack, and development process behind DealDetectiveAI.

Why I Built DealDetectiveAI?

Online shopping can be frustrating when:

• Prices vary across different retailers.
• There are too many options to choose from.
• Finding personalized recommendations is difficult.

DealDetectiveAI was created to solve these issues by:

• Comparing prices across multiple e-commerce platforms.
• Providing AI-powered recommendations based on user search history and browsing behavior.
• Tracking price changes so users can make informed purchase decisions.

Key Features

🛒 AI-Powered Product Recommendations

Using OpenAI’s GPT-4, DealDetectiveAI generates personalized product recommendations based on the user’s past searches and browsing history. This ensures that each user gets tailored shopping suggestions that match their needs and preferences.

💰 Price Comparison Across Retailers

DealDetectiveAI fetches prices from multiple sources such as Amazon, Walmart, and Best Buy using APIs and web scraping techniques. Users can see side-by-side price comparisons to ensure they get the best deals.

🔍 Smart Search with AI Assistance

The app features an intelligent search function that helps users quickly find relevant products while filtering out irrelevant or outdated listings.

📊 Real-Time Price Tracking (Future Feature)

One of the planned enhancements is price tracking, where users can set alerts to get notified when a product’s price drops.

Tech Stack Used

🎨 Frontend: React.js

• Why? Fast, component-based UI development with seamless API integration.
• Used React Router for smooth navigation and Axios for fetching data.

🔧 Backend: Node.js + Express

• Handles API requests, AI interactions, and database queries.
• OpenAI API powers the recommendation engine.

🗄 Database: PostgreSQL

• Stores user browsing history and price data.
• Optimized queries to quickly fetch relevant shopping information.

🛠 Additional Tools & Libraries

• Axios: For API communication.
• Cheerio & Puppeteer: For web scraping price comparisons.
• Redis (Future Feature): To cache price data for faster responses.

How I Built DealDetectiveAI

Step 1: Setting Up the Backend

• Built an Express.js server.
• Connected to PostgreSQL for storing user data.
• Integrated OpenAI API for smart recommendations.

Step 2: Developing the Frontend

• Created a sleek UI using React.js.
• Implemented a dynamic search bar and results page.
• Integrated an interactive price comparison UI.

Step 3: AI & Price Comparison Logic

• Used OpenAI GPT-4 to generate personalized product suggestions.
• Implemented price comparison APIs and web scraping to fetch real-time product prices.

Step 4: Enhancements & Optimizations

• Optimized API calls to ensure fast performance.
• Improved AI prompts for better recommendations.
• Designed a clean UI/UX for seamless shopping.

Challenges & Lessons Learned

Developing DealDetectiveAI came with challenges:

• Fetching accurate price data: Some retailers have strict anti-scraping policies, so using official APIs was necessary.
• Optimizing AI recommendations: AI responses had to be fine-tuned for accuracy and relevance.
• Balancing performance and scalability: Using efficient queries and caching mechanisms was key.

Through these challenges, I deepened my understanding of AI, backend optimizations, and API integrations.

How You Can Use or Contribute?

If you’re interested in learning how to build an AI-powered shopping assistant, feel free to check out DealDetectiveAI on GitHub: 👉 GitHub Repository

Ways to Contribute:

• Improve AI prompts for even better recommendations.
• Add support for more retailers.
• Optimize price tracking with real-time alerts.
• Enhance the UI/UX with a more intuitive design.

Final Thoughts

Building DealDetectiveAI was an exciting journey that combined AI, data scraping, and full-stack development. I hope this project inspires other developers to explore AI-powered shopping assistants and build innovative solutions that improve user experiences.

If you have any questions, feel free to connect with me on LinkedIn or leave a comment below. Happy coding! 🚀