How I Built a Smart Shopping Tracker That Saves Users Money

Why i created Salespy: Solving the Smart Shopping Problem Programming is awesome, but I’ve always wanted to go all the way – from an idea to a working product that actually brings value. That’s how Salespy was born – a service for tracking discounts on Amazon, Walmart, Target, and The Home Depot. At first, I thought one marketplace would be enough, but it turned out users needed more powerful features to enhance their shopping experience. The workload grew a bit more than I expected – no killer features, no way forward. Competitor analysis: How Salespy stands out There are already several well-known price tracking tools on the market, but each comes with significant drawbacks: Keepa – A powerful tool with a massive price history database, but its interface is outdated and difficult to navigate. Plus, it only supports Amazon and is not available in all countries. CamelCamelCamel – Similar to Keepa, but some users report price history manipulation, which raises trust issues. Honey – Primarily focuses on coupon savings rather than full-scale price tracking. What problems did i want to solve? Modern and user-friendly interface – No clutter, only the features you actually need. Multi-marketplace support – Tracks discounts across Amazon, Walmart, Target, and The Home Depot. Global availability – Works in all countries where these marketplaces operate. Browser extensions & mobile apps – Seamless tracking, anytime, anywhere. Advanced features for more accurate and efficient price tracking. Salespy isn't just another price tracker - it's a smarter, faster, and easier way to save money! How Salespy works: Tech stack and architecture To start, I chose: Next.js (it was a SPA at first, but SEO let me down) TypeScript NestJS – in my opinion, the best framework Redis + BullMQ + MySQL Nginx And in the future, I’ll need: Python Dart + Flutter At the beginning, I made a mistake. I decided to go with SPA + Helmet, thinking it would be fine for the early stages, but SEO was terrible. I had to quickly rewrite the public pages in Next.js, and that really helped. Want a breakdown of the tech stack and architecture details? Drop a comment – I can write a separate post! First mistakes and promotion There were more tasks than I could handle on my own, and as a result, I lost 7 registrations due to a poorly tested release. It’s hard to attract users without a trial period. Had to add that. Marketing takes more time than coding. It's something new and a challenge. I’m still actively working on the project. Upcoming Features: What’s Next for Salespy? New marketplaces A new price update mechanism – faster, more accurate, and scalable Plugins, mobile app Real savings: One of the users saved $226.03 just by receiving a timely notification from Salespy.

Feb 27, 2025 - 14:36

How I Built a Smart Shopping Tracker That Saves Users Money

Why i created Salespy: Solving the Smart Shopping Problem
Programming is awesome, but I’ve always wanted to go all the way – from an idea to a working product that actually brings value. That’s how Salespy was born – a service for tracking discounts on Amazon, Walmart, Target, and The Home Depot.

At first, I thought one marketplace would be enough, but it turned out users needed more powerful features to enhance their shopping experience. The workload grew a bit more than I expected – no killer features, no way forward.

Competitor analysis: How Salespy stands out
There are already several well-known price tracking tools on the market, but each comes with significant drawbacks:

Keepa – A powerful tool with a massive price history database, but its interface is outdated and difficult to navigate. Plus, it only supports Amazon and is not available in all countries.
CamelCamelCamel – Similar to Keepa, but some users report price history manipulation, which raises trust issues.
Honey – Primarily focuses on coupon savings rather than full-scale price tracking.

What problems did i want to solve?

Modern and user-friendly interface – No clutter, only the features you actually need.
Multi-marketplace support – Tracks discounts across Amazon, Walmart, Target, and The Home Depot.
Global availability – Works in all countries where these marketplaces operate.
Browser extensions & mobile apps – Seamless tracking, anytime, anywhere.
Advanced features for more accurate and efficient price tracking.

Salespy isn't just another price tracker - it's a smarter, faster, and easier way to save money!

How Salespy works: Tech stack and architecture
To start, I chose:

Next.js (it was a SPA at first, but SEO let me down)
TypeScript
NestJS – in my opinion, the best framework
Redis + BullMQ + MySQL
Nginx

And in the future, I’ll need:

Python
Dart + Flutter

At the beginning, I made a mistake. I decided to go with SPA + Helmet, thinking it would be fine for the early stages, but SEO was terrible. I had to quickly rewrite the public pages in Next.js, and that really helped.

Want a breakdown of the tech stack and architecture details? Drop a comment – I can write a separate post!

First mistakes and promotion

There were more tasks than I could handle on my own, and as a result, I lost 7 registrations due to a poorly tested release.
It’s hard to attract users without a trial period. Had to add that.
Marketing takes more time than coding. It's something new and a challenge.

I’m still actively working on the project.

Upcoming Features: What’s Next for Salespy?

New marketplaces
A new price update mechanism – faster, more accurate, and scalable
Plugins, mobile app

Real savings: One of the users saved $226.03 just by receiving a timely notification from Salespy.