A while ago I got into CS2 skin trading casually. I wasn’t trying to become a full-time trader — I was mostly curious about how prices move and whether small arbitrage opportunities actually exist.
What surprised me wasn’t the market itself, but how messy the workflow was.
Every time I wanted to evaluate a single skin, I had to open multiple marketplace tabs, manually compare prices, calculate fees, and still never be completely sure if something was truly profitable.
It felt less like trading and more like repetitive admin work.
My first “solution”: spreadsheets
Before writing a single line of code, I tried solving the problem with Excel.
I built several spreadsheets to:
track prices manually
calculate ROI after fees
monitor potential profit margins
For a while, this worked.
But the more I used them, the more obvious the limitations became:
data had to be updated manually
I still missed opportunities
the workflow was slow and error-prone
At some point I realized I was spending more time maintaining spreadsheets than actually analyzing the market.
That’s when I decided to automate it.
Building the first version
I started developing a small desktop tool just for myself.
The goal was simple:
See all relevant market data in one place and instantly understand profitability.
The first version was extremely basic, but it already solved a major problem — it removed the need to constantly switch between tabs and manually calculate margins.
Once I started using it daily, something interesting happened.
It began to snowball.
How it grew into a full system
Every time I ran into a new frustration while trading, I added a feature to solve it.
Over time the tool evolved to include:
live price tracking across multiple markets
automatic ROI calculations after fees
arbitrage opportunity detection
historical price trend analysis
inventory value tracking
customizable analytics dashboards
What started as a simple automation script slowly turned into a full analytics terminal for CS2 skin trading.
The unexpected challenge: support as a solo dev
Once I shared the tool with friends and other traders, I realized another problem:
Support.
As a solo developer, I couldn’t realistically be available 24/7 to answer questions.
So I built an AI support system on Discord that can handle common user questions and guide new users even when I’m offline.
This turned out to be one of the most important decisions for keeping the project sustainable.
Privacy-first by design
Another decision I made early was to keep the tool privacy-friendly.
MulMarket runs locally on the user’s machine and doesn’t collect personal data.
This also meant avoiding ad-based monetization models.
Free vs Pro version
I released a free version so users could try the tool without commitment.
The Pro version exists mainly to help cover infrastructure costs like servers, hosting, and ongoing development — since I’m working on the project alone.
Lessons learned
Building this project taught me several important things:
Real problems make the best project ideas.
Spreadsheets are often the first step before automation.
Solo development requires thinking about sustainability early.
Support systems are just as important as the product itself.
Final thoughts
It’s been fascinating watching something that started as personal frustration and a few Excel sheets gradually evolve into a full analytics tool used by other traders.
If you’re curious, you can check it out here:
I’d love to hear feedback or discuss similar experiences — especially if you’ve ever turned a simple workaround into a real project.
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