First week of Wall of a Million Names — honest numbers

I ran a full multi-channel sweep this month, about a dozen placements across Reddit, YouTube and X, and got a flat zero replies. What kept it useful was writing down per channel, before posting, what evidence would have counted as signal. A zero then reads as a falsified hypothesis about the channel instead of a verdict on the product. Week one cold traffic on a novelty item is close to the hardest test there is.

answering your actual question: cold traffic can convert on a novelty product, but not to an empty wall. what you're really selling is belonging, and at launch that value is basically zero because the wall looks dead. so cold clicks bounce not because they're cold, but because they land on something with no momentum to buy into.

your numbers kind of say this already. the english story creative hit 0.67% CTR, that hook is fine, people wanted in. 0 conversions across 25k impressions isn't a traffic problem, it's what they landed on. warm audiences convert right now because the story manufactures the momentum your product page can't yet.

so before buying more traffic i'd fake the momentum first: seed a few hundred names on the wall (comp them, friends, whatever), add a live counter and an 'X added today', throw in some scarcity (first 1000 get a mark). give a cold visitor a reason it looks alive and a reason to act now, then re-run that same english creative and see if conversion actually moves.

on the shorts, someone already made the cold-start point so i won't repeat it, but the other half is the video itself. a 'here's my project' short gives nobody a reason to finish it. names actually filling up a wall is a genuinely satisfying visual though, so i'd make the short that, not an ad. i build a tool in the youtube-analytics space and a first-15-seconds cliff like your 1100 to 8 is almost always the video not earning the next second, rarely the topic being wrong.

my bet: warm-first to fill the wall, then cold starts converting once it sells itself.

Pre-committing your kill thresholds before launch is the most useful thing in this post — most people set them after the numbers come in, which means they never kill anything. I run a small pipeline of micro-ventures with explicit go/no-go gates for the same reason, and the honest finding is the same as yours: shipping the thing is maybe 10% of it, and traffic that tells you why it's not converting is worth more than a quiet launch that tells you nothing. Respect for publishing the zeros — the survivorship-bias version of this post gets written every day, this one doesn't.

Posting real numbers with zero conversions is the useful kind of post, so thanks for it.

On the Shorts: 1,100 -> 555 -> 420 -> 19 -> 8 doesn't look like the algorithm dropping you, it looks like the first few getting a normal cold-start sample and then retention data coming back. Six videos is also not enough to have tested a format - it's enough to have tested one.

I've been screening small channels that badly outperform their subscriber count, to work out what actually travels. The thing separating them wasn't production quality, it was that the title was the exact sentence a specific frustrated person types into the search bar. The ones beating their own median 3x+ were all answering a question somebody already had. A novelty wall doesn't have a question attached to it - nobody is searching for it - so cold video is the wrong instrument no matter how good the creative gets.

Your own ad data already says this: the English personal-story creative got 5x the CTR of the AI character at a fifth of the cost per click. The story is the product. That's a warm-audience asset, not a cold-traffic one.

For what it's worth, I'm running my own honest-zero right now - a landing page on day 11 with 0 signups, thresholds pre-committed before launch so I can't move the goalposts afterwards. The thing I had wrong was assuming that shipping the page counted as distribution. It sat there for a week doing nothing at all. Yours at least has real traffic hitting it and telling you something.

The part that resonated most was separating AI adoption from workflow redesign.

A lot of teams seem to mistake adding AI for changing how work actually gets done.

That distinction feels much more durable than the usual "AI is replacing jobs" narrative.