I built a tool that tells you if your startup idea has real demand — before you write a line of code
Most ideas die in Notion. Not because they were bad, but because founders skip the one step that would have told them whether anyone actually cares.
I kept seeing the same pattern: months of building, a ProductHunt launch, and then silence. The problem wasn't execution — it was that nobody validated demand before writing line one of code.
So I built spark.
How it works:
- Describe your idea in one sentence
- spark generates a live landing page in under 60 seconds
- You share it — Reddit, Twitter, Slack, wherever your audience is
- Real people sign up (or don't)
- Unlock the AI analysis for $19: verdict, next steps, top risk, full email list
The insight I kept coming back to: there's a fundamental difference between an AI telling you your idea sounds promising and 14 strangers leaving their real email address. One is a simulation. The other is evidence.
What you get from the analysis:
- Conversion rate benchmarked against thousands of tested ideas (cold traffic average is 3–7%)
- AI verdict: Build / Pivot / Drop
- Your next 3 concrete steps
- The top risk to watch
- Full email list + CSV export
- Page extended from 7 to 30 days
Zero signups? You owe nothing. That's also signal.
Would love feedback from this community — especially anyone who's validated (or killed) ideas before building. What's your current process for testing demand?
→ usespark.net
An upvote on product Hunt would be appreciated
→ https://www.producthunt.com/products/spark-validate-your-startup-idea?utm_source=other&utm_medium=social
The framing of "14 real emails beat any AI verdict" is sharp, and I think it points to something deeper: writing about an idea can make you feel like you've stress tested it when you've mostly just rehearsed it.
The fastest pre-build signal I've found is asking one person in my target market to say the problem back to me in their own words, not "does this sound good" but "when did you last feel this?" If they can answer that naturally, the idea has roots. If they can't, the idea might be more interesting to me than to them.
One thing I use to catch ideas before I lose them: DictaFlow. I dictate the raw impulse the moment it hits, before I have time to polish it into something that sounds impressive but no longer has the original conviction. Reviewing cold dictations a few days later is a surprisingly honest test, does this still feel urgent, or did I just like how I wrote it?
nteresting framing, agree that 14 real emails beat any AI verdict.
Curious about the methodology side: when spark gives the Build/Pivot/Drop verdict, what's it actually weighing? Is it purely conversion rate against the 3-7% benchmark, or are you also factoring things like time-on-page, traffic source quality (Reddit vs cold ads vs warm Slack share would tell very different stories), or self-reported intent from signups?
Also wondering how you handle the noisy cases like 50 signups but all from one Reddit thread that just liked the idea entertainment-wise vs actual buyers. That false-positive risk feels like the hard part of demand validation.
This is quite wonderful….I have learnt to realize a problem then build a solution, instead of creating a solution and looking for problems or customers.
How are you currently handling pushing your product to the market Saya?
I would surely give an upvote at product hunt
Thank you — that means a lot.
On distribution: mostly organic right now. Sharing in communities where founders already talk about ideas — Reddit, Indie Hackers, Twitter. The product is self-distributing to some extent because every spark page has a public URL that people share themselves to collect signups.
Would genuinely appreciate the upvote . Here's the link: https://www.producthunt.com/products/spark-validate-your-startup-idea?utm_source=other&utm_medium=social
The useful part here isn’t idea validation.
It’s compressed demand proof.
Most founders don’t need more idea feedback.
They need faster evidence.
That’s the real product:
not “validate your startup idea”
but “get proof before you build the wrong thing”
spark is clean, but still sounds early and lightweight for that job.
If this becomes the default pre-build demand layer, the name likely needs more weight.
Exirra.com fits that better.
Stronger signal, more durable, less MVP-coded.
spark works for a quick test.
Exirra works if this becomes the system founders trust before committing months of build time.
"Compressed demand proof" is a better frame than what I'm using — genuinely stealing that.
On the name: spark is intentional. The lightness is the point. Heavy names signal commitment before you've earned it. If this becomes the default pre-build layer, I'd rather grow into the weight than start with borrowed credibility.
Exirra sounds like enterprise software. That's a different bet.
That’s fair.
The real question is not whether Spark is wrong.
It’s when the product stops being “light enough to try” and starts needing to feel “serious enough to trust.”
Spark is doing the first job well.
It gets weaker the moment the product stops being:
“quick validation”
and starts being:
“evidence I’d trust before spending 3 months building”
That’s usually the inflection point.
Not a better name now.
Just a heavier one when the product earns it.
Agreed. And that inflection point is exactly the one worth building toward — not naming toward.
Really like the focus on actual validation signals vs AI-generated “this sounds promising” — that distinction is spot on.
One thing I’d be very curious about though:
how are you seeing the conversion from “people signing up on the generated page” → actually paying the $19 for analysis?
Because from a user perspective, the core value already happens at the moment of:
“people left their email → there is demand”
So the paid step might feel slightly secondary unless the value of the analysis is extremely clear and immediate.
Also wondering:
before someone shares the page, is it obvious what kind of result they’ll get after?
Feels like small clarity + expectation gaps here could have a big impact on conversion.
Happy to take a closer look at the flow if helpful — this is a really interesting space.
Really appreciate this — you're pointing at something real.
On the paywall: you're right that "people signed up = demand confirmed" could feel like the job is done. The bet is that signups create urgency rather than satisfaction — you can see the count but the emails are blurred, the verdict is locked. That tension is what's supposed to drive the $19. Whether it actually does, I'll know soon.
On expectation setting before sharing — that's the sharper critique and I think you're right. There's a gap between "your page is live" and "here's exactly what you'll learn when people sign up." Working on making that more explicit.
Would genuinely take you up on the fresh eyes — feel free to run an idea through it and tell me where it breaks.
Makes sense — the “blurred value creates tension” approach is interesting, I can see the logic behind it.
I tried to look at it from a first-time user perspective, and one thing that stood out:
before sharing the page, I’m not fully sure what kind of decision I’ll be able to make after the analysis.
Right now it feels like:
“you’ll get a verdict”
but not fully clear:
“what will I actually do differently after I see it?”
For example:
– will it tell me why people didn’t sign up?
– will it suggest how to improve the idea or positioning?
– is it more like validation or iteration guidance?
I think making that part more concrete before the sharing step could increase both:
→ motivation to share
→ and willingness to pay after
Happy to run a real idea through it and give you a more structured breakdown of where the flow feels strong vs where it drops.
This is the clearest articulation of the gap I've heard so far — thank you.
You're right. "You'll get a verdict" is too abstract. The question people actually need answered before they share is: "if this works, what will I know that I don't know now?"
The analysis does answer the iteration question — it tells you specifically what held people back, whether the problem is the idea or the positioning, and gives you 3 concrete next steps. But none of that is visible before you share. That's the fix.
Taking you up on the structured breakdown — run a real idea through and tell me exactly where the motivation to share drops. That's the most useful thing I could get right now.
Got it — I ran a quick test flow with a real idea, and I can already see where the motivation to share starts to drop.
The main point isn’t the tool itself — it’s the moment right before sharing.
Right now it feels like:
“I’m about to send people to a page… but I’m not fully sure what I’ll get back that justifies asking for their attention”
A couple of moments where friction shows up:
– before sharing, the outcome still feels a bit abstract (“verdict” vs a clear decision I can act on)
– I don’t fully know what kind of insight I’ll get beyond “there is / isn’t demand”
– so the emotional push to actually share isn’t as strong as it could be
I think if that part becomes more concrete and outcome-driven, it could significantly increase both sharing and conversion after.
Happy to map this out properly — this feels like one of those flows where small changes can have a big impact.
The conversion rate benchmark is what makes it useful — knowing whether 5% is good or bad on cold traffic is something most people have no reference point for.
Exactly, most people don't understand the difference between this website, and a regular landing page builder, the thing is, this website isn't a landing page builder at all, the page is the bait. The real product is what happens after: real strangers see your idea and either sign up or don't.
You get a conversion rate + AI verdict based on actual humans, not AI guessing if your idea sounds good.
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