100 upvotes, 18k views, 900 users… all from one Reddit post.
I've been building nivaas.info , a tool to help people decide where to buy a home, not just find listings.
Yesterday I shared it in a couple of Pune-related subreddits.
Results after ~24 hours:
👍 100+ upvotes
👀 18,000+ views on the post
🌐 ~900 unique visitors
⚡ 25,000+ requests to the app
💡 70+ feature requests
💼 1 consulting inquiry from a company building something similar
The interesting part wasn't the traffic.
People absolutely tore apart my assumptions.
They pointed out:
Incorrect price estimates in some areas.
Better ways to visualize locality data.
Missing government infrastructure overlays.
How I should validate data using official sources instead of relying only on listing sites.
Some comments called it "AI slop."
Initially, that stung.
Then I realized they were criticizing the quality of the data, not the idea itself.
That's incredibly valuable feedback.
I could have spent another three months polishing the product in isolation and still missed these issues.
Instead, I got a free roadmap from hundreds of potential users.
My biggest takeaway:
Don't wait until your product is "ready."
Ship it, let people break it, and use that feedback to build the version they actually want.
Now it's back to fixing the data and shipping the next version. 🚀
The number that will tell you if this worked is next week's: how many of the 900 come back once the criticism cycle ends. Local subreddit traffic is unusually high-intent for a launch (actual Pune homebuyers rather than fellow builders), so returning users are a real demand signal, not vanity. And on the "AI slop" data complaints, the durable fix in a data product is provenance in the UI: every estimate linking its official source. People forgive wrong numbers with visible sources far more readily than right numbers without them.
900 users and 70+ requests gives you a lot of evidence very quickly, but also a lot of ways to interpret it.
You concluded that people were rejecting the data quality rather than the underlying idea. What did you see in their actual behavior or feedback that gave you confidence in that distinction?