A creator refused to endorse my product. Here's what I fixed because of it.
Four months ago I posted here at $0 revenue, three near-quits in. Since then: shipped a Chrome extension, integrated live web cross-referencing, still $0.
The useful thing that happened wasn't a feature. It was a rejection.
I reached out to a creator who covers scams for a living and asked her to try TruthScore. She did, and she told me straight, no hedging: she couldn't put her name behind it. Not because the concept was bad—because she had no way to independently check where a score's claims actually came from. If a flag said "Reddit reports say X," that was just text. She couldn't click it, couldn't read the original post, couldn't verify a single thing before recommending it to an audience she's built specifically by being skeptical.
That's the correct objection. A tool built to help people not trust things blindly was itself asking to be trusted blindly.
So I fixed exactly what she named:
Every source a scan cites is now a real, clickable link to the actual page — not a domain name I'm asking you to take on faith.
There's now a public page showing exactly how the score is calculated: the three signals, their weights, and where the method can get it wrong.
Revenue is still $0. I'm not going to dress that up. Cold outreach mostly went nowhere, one lead asked for a write-up and went quiet, another is asking hard questions before deciding — I don't know yet where that lands.
If you tried TruthScore before and the reason you didn't pay was "I can't tell if this is real" — that's the thing that changed. Worth a second look: truthscore.online
If you're still not paying after that, I'd rather hear the real reason than nothing at all.
Two observations. First, go back to the same creator with the fixed version — a skeptic who flips after seeing her objection addressed is worth ten paid endorsements, and her audience is literally the trust-paranoid segment you're trying to reach. Second, clickable sources and a public methodology page are credibility table stakes, but they don't solve distribution: nobody discovers a trust tool at the moment they need it. The version of this that compounds is publishing your own public scorecards — score the 50 most-searched scams and put the results where Google can find them. That turns your methodology from something users take on faith into something they can inspect before they ever install.
A Reddit claim can be perfectly linked and still be weak or coordinated. I’d consider an evidence card showing the source type, retrieval date, independence, and exactly what the source supports versus what TruthScore inferred. Are you measuring whether people actually open the evidence before deciding the score is credible?
that's a great rejection to get because she told you the exact thing to fix. we had a smaller version with our first testers, where nobody complained and nobody came back, and silence is so much harder to act on than a specific objection like hers. clickable sources feels like it should be the default for any tool whose whole pitch is trust. did she say she'd take another look now that it's fixed?
Link, since I kept it out of the post: https://bigideasdb.com. The TrustMRR section is where this came from. If you want to try the chat nobody uses, ask it for the revenue split in your own category and see whether the X pattern holds there. I'll run any cut someone asks for in the comments.
This is great work — reminds me of some of the calls I've had to make building Xstream4K. What would you do differently if you started over?
This is a great example of a rejection being the most useful feedback. "A tool that asks you not to trust blindly shouldn't ask to be trusted blindly" is a sharp insight. Making the method public is exactly what would get a skeptical creator to look twice. Did you go back to her after the changes?
The creator who turned you down is now the warmest lead you have, since she named the exact objection and you fixed exactly that — going back to her beats every cold outreach still on your list.
The creator's objection is the same one that separates useful AI tools from demos: show your work or get out. We built an SEO audit tool that scans 100+ ranking factors and the hardest design decision was identical — do you show a score and ask trust, or show the evidence trail and let people verify?
Iteration speed matters here. Recent model upgrades mean rebuilding a page component takes one pass instead of three or four debugging rounds because the model reads the actual error trace now. When a rejection names the exact fix, you can ship it in hours not weeks. That compresses the feedback loop enough that a single honest no becomes more valuable than ten polite yeses.
Revenue at $0 with a working product and a clear iteration signal is better than $0 with neither. The trust layer you just added is the foundation everything else stands on.
Have prospects responded differently since adding source-level verification, or are they still stopping at the same trust objection despite being able to verify the claims?