I built a search engine that indexes 116,000+ e-commerce emails so marketers don't have to subscribe to hundreds of newsletters. Costs me $7.12/month to run
Hey IH 👋
I'm a full-time software engineer who's been building a side project on evenings and weekends for the past 5 months. I want to share what I've built, what I've learned, and where I'm stuck. Because honestly, the "getting people to find your thing" part is way harder than the building part.
I saw a post on LinkedIn on how tough it is to research competitor emails. Unlike most LinkedIn posts that don't stick, this one did. The problem was so simple and the solution so straightforward, I thought why not give it a go. Of all the other ideas I have been procrastinating on, I decided it's time to stop thinking and actually do something. So I started working on this.
Here goes the problem ->
If you've ever tried to study how e-commerce brands run their email campaigns, you know the drill:
There's no good way to search across e-commerce email campaigns. You can't easily see how a brand's messaging changes over time, what their send frequency looks like, or compare how competitors approach the same sale event. Tools like MailCharts and Really Good Emails exist, but I felt there was room for something more focused on e-commerce and more accessible.
I found Milled which kinda does the same thing but it's hella expensive.
Find That Mail indexes emails from 300+ e-commerce brands (think Calvin Klein, Zara, Ted Baker, H&M, and hundreds more). We process around 513 new emails every single day.
The platform lets you:
It's useful for two audiences: email marketers and agencies who need competitive intelligence.
That last number is the one I'm not proud of, but I think it's important to share. The product works. The data is there. The infrastructure is solid. But getting eyeballs? That's a completely different skill set from building software, and I'm learning it from scratch.
I started building this before LLMs were mainstream. So a lot of time was spent in email parsing, categorization, and data extraction. It was a LOT of effort.
Now I've integrated LLMs into parts of the pipeline, and they've made things easier, but not as plug-and-play as people think. You need serious guardrails to stop the model from hallucinating categories, going completely off the rails.
I am really proud to keep the cost as low as $7.12/month. Most people wont care about it. But I just do :)
The building part? I can do that all day. I'm an engineer, give me a problem and I'll code a solution.
But distribution is a different beast entirely. I'm currently at ~5 views per day and my goal is to get to 300. I'm diving deep into SEO, trying to understand how to create content that ranks, and experimenting with different channels to drive organic traffic.
I don't have a magic growth hack to share yet. But I plan to come back in a couple of months and share exactly what worked and what didn't, with real numbers.
I'd think about distribution from day one. I spent 5 months building before seriously thinking about how people would find this. Classic engineer mistake.
Right now the platform is completely free. I want to focus on getting users and learning what features they actually care about.
If you do email marketing, run an e-commerce brand, or just want to see how the big players structure their campaigns, I'd genuinely love for you to check it out:
And if you're an IH veteran who's cracked the "going from 0 to meaningful traffic" puzzle, I'm all ears. What worked for you?
Building in public, one evening at a time. Happy to answer any questions about the tech stack, the email processing pipeline, or how I keep costs at $7.12/month.