SmartGamer: SEO-Driven Amazon Gaming Deal Tracker

“Amazon has the strictest anti-bot detection. Making a seamless gaming deals platform around it wasn’t easy – but I pulled it off.”

🔧 Project Summary

SmartGamer.in is an SEO-first web app that tracks price trends, discounts, and trusted-seller listings of gaming-related products on Amazon India.

It was built to help gamers and PC builders discover real value deals:without falling for fake discounts or shady listings.

💡 The Idea

I wanted to create a no-BS place where Indian gamers could find Amazon deals from only trusted sellers: names like Clicktech, Dawntech, EZRetail, and Electronics Bazaar.

The idea was sparked while rebuilding my open-source Amazon scraper library, AmzPy. I thought: why not turn this engine into a powerful public tool?

🧱 Tech Stack

Layer	Tool/Service	Why I Chose It
Frontend	Astro + Svelte	Astro for static SEO; Svelte for hydration and reactivity
Styling	Tailwind + DaisyUI	Rapid, component-based styling
Backend API	FastAPI	Async speed and maintainability
Database	Supabase	PostgreSQL with SQL views and REST access
Scraper	AmzPy (custom lib)	Lightweight async scraping tailored to Amazon
Deployment	GitHub Actions + Vercel	Seamless CI/CD for backend and frontend

⚙️ Development Breakdown

1. Rewriting AmzPy for Performance

Rebuilt as a fully async scraper.
Supports both category pages and search results.
Fine-tuned headers and retries to bypass Amazon’s bot protection:no headless browser required.

📌 Challenge: Making it stable without using Puppeteer or Selenium. Lots of trial-and-error with headers, delays, and seller filtering.

2. FastAPI-Powered Backend

CLI-based job runner scrapes all product categories.
Central constants.py controls:
- Category URLs
- Max pages per scrape
- Trusted sellers list
Data filtered server-side → batched uploads to Supabase.
Scheduled scrapes feed trend tables automatically.

3. Precomputed SQL Views in Supabase

To keep the frontend fast, I used Supabase SQL views for trend aggregation:

trend_daily → 24h price changes
trend_weekly → 7-day lowest prices
trend_alltime → Historical lowest price

This made trend pages snappy and low-latency, even with large product datasets.

📊 Trend Pages Visuals:

Daily Price Change View

Weekly Lowest Price

All-Time Historical Low

4. Astro + Svelte Frontend: Fast + Crawlable

Astro handles:

Static category pages
SEO-optimized [...filters].astro routes
→ Generates thousands of crawlable URLs

Svelte handles:

Filter sidebar UI
Interactive trend sorting tabs
Product price chart rendering

Filtered Category View

Product Price Chart

🔍 SEO Boost: 25 categories × price/discount/rating filters = hundreds of unique, crawlable pages.

🚀 Key Features

✅ Trusted Sellers Only: No fake listings or shady vendors
📉 Trend Pages: Daily, weekly, and all-time price drop listings
📦 Product Detail Pages: Full price history with chart
⚡ Real-time Filters: Price, rating, Prime-only, discount %
🔍 SEO-Driven Pages: Auto-generated filter-based URLs

🧭 Roadmap

🔔 User Alerts: Subscribe to trend pages via email
❤️ Wishlist Tracking: Track specific products
🧠 PC Builder Tool: Suggest component builds based on drops
📣 Daily Digest: Curated deal alerts via email + Telegram

💭 Lessons Learned

Amazon scraping is possible without Selenium: with the right async setup and header game.
Supabase’s SQL views were key to keeping frontend fast and bandwidth light.
Astro + Svelte is an underrated stack for performance + SEO.
Filtering-based dynamic URLs = SEO treasure chest.

🔗 Live Project

👉 SmartGamer.in

AmzPy – Amazon Scraper Library