In your own recent experience, what are the top 1-3 things people should keep in mind for a Product Hunt launch. I am making this post hoping the comments and discussions cut through the "noise" of what's important.
It seems like the Product Hunt platform is changing and there are new special launch days like Alpha Day, to be aware of. It would be awesome to get fresh perspectives on what works well right now for planning and executing a successful launch.
Everyone says to test demand before you build. We didn t. We built the product first, like a lot of people do, and only afterward found a fast way to test the part we d skipped.
What we re testing now isn t really the idea - it s the positioning: Does someone landing on our page understand what the product is? Does the offer make sense? Does the pricing feel right? We use a paid research panel (Prolific, though there are others like Wynter, PickFu and Lyssna) to put the page in front of people who match our audience. They read it and answer a short questionnaire: What do you think this does? Do you understand it? Does the price seem fair? You pick the audience, they review, you pay per response. A few hours to prepare, results back the same day.
It's been most useful for catching where people misread the offer - something our existing users can t really tell us, because they already understood it well enough to sign up. We ll use this approach for landing page changes from now on, and we ll run these tests before building the next thing rather than after.
How do you test whether people understand your product or your idea before you commit to it?
I started timing every interruption I labeled a "quick question." Slack messages, DMs, taps on the shoulder. Anything that felt like it would take two minutes.
The average was 11 minutes. The longest was 40. Most of them required context I had to rebuild from scratch because I had been in the middle of something else.
I keep digging into what actually gets a product mentioned in ChatGPT or Perplexity answers, and the data keeps pointing somewhere that makes me question the whole "GEO/AEO" hype.
Ahrefs looked at 75k brands and found branded mentions correlated with AI visibility way more than backlinks 0.664 vs 0.218. It's correlation, not causation, so take it with salt. But the gap is big enough that I can't ignore it.
Which makes me wonder if we're overcomplicating this. Maybe AI visibility isn't a new discipline at all. Maybe it's just the old thing: be genuinely talked about in the right specific places.
I tested locally for two days. Everything worked. I deployed, and within an hour three users reported the same issue.
The difference was environment variables. One flag was set in development and not in production, and the code had a silent fallback that made it look like it worked when it didn't.
It's a really weird feeling having a decent number of signups on paper but having zero clue what your actual ideal customer looks like. You look at your analytics and see one group living inside your app daily while another batch signed up months ago and never came back. When you're trying to design features for two completely different types of users at the same time you end up satisfying nobody.
Looking back do you wish you had niched down right from day one or is it better to cast a wide net early on just to see who sticks around?
Chipmaker Nvidia announced this week it will be investing up to $100 billion (with a B) in OpenAI to help it build out its computing power. This follows OpenAI s move earlier this month to buy $300B in computer power from Oracle.
