Octolens, a social-listening tool for tech brands, spent a little over €600 on a ChatGPT ad campaign. After two weeks, one ad shown in the US had b...
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Hey Dan, I read your post about 200 ad clicks and zero signups. I'm a solo founder too and stuck on the same problem with my own tool, so I'm curious: is it more that the right people never see it, or that they see it and don't click?
Kevan, for this case neither option matches: the ads produced about 200 clicks, so people saw them and clicked through — what never happened was the signup. Whether the right people saw it, the numbers can't say; clicks don't come labeled by fit.
Impressions, clicks, and signups can fail for different reasons, and each points to a different fix. Which of the three is sitting at zero in your own numbers?
That’s a good way to break it down. For FounderPulse, the hardest part is getting the right founders to discover it in the first place. I’m trying to understand whether the bottleneck is visibility, interest, or conversion rather than assuming the product is the problem. Have you found anything that helped you distinguish between those three?
For FounderPulse, reaching founders isn't the same as reaching founders who are actively trying to find their next customer. Someone browsing AI tools can visit the same page for a very different reason. Signup numbers alone won't tell you whether to change the product or how you're reaching people.
I review stalled products and offers to help founders decide what to change, keep, or stop. My profile explains that work if it's relevant to the decision you're facing.
That’s an interesting angle. Finding the right people is only half the problem; founders also need to understand what to do with the feedback they get. Do you usually find that stalled products struggle more with positioning or with the product itself?
I can't say which is more common. "I don't understand what this does" and "I understand it, but I don't need it" can both look like weak interest.
For FounderPulse, are you looking to work this out yourself, or considering an independent review?
dan, this is the exact trap early-stage founders fall into, and your distinction between "this attempt didn't sell" and "this business can't sell" is the most important framing in indie hacking.
when you are bootstrapping with severe constraints (e.g., building entirely on a $150 phone), you cannot afford to treat marketing as a black box of "spend more until it works." you have to diagnose the specific friction point.
the octolens example perfectly highlights that trust and context are the actual currencies, not just impressions. a recommendation carries inherent credibility; a blind ad does not. that’s why constraint-driven founders often find more success in high-signal, organic communities (like dev.to or niche discords) than in broad paid campaigns. you aren't just testing an offer; you're testing the environment in which the offer is received.
fantastic, grounded perspective. diagnosing the specific gap between the customer's intent and the current offer is the only way to earn the right to iterate. 🐯📊
Harun, when money is tight, "spend more until it works" leaves very little room to learn from a failed attempt. You can end up paying for another campaign without getting any closer to knowing what to change.
The detail that would change the founder's decision is the one about the ten signups: those people were already inside a conversation about the problem when the product came up. An ad shows the offer to people who match a keyword; a recommendation shows it to people who match a situation.
The affordable test between "this attempt didn't sell" and "this business can't sell" is to reproduce the second condition on purpose. Write down the situation those ten were in (role, company size, what they were trying to do that week), count how many such people exist, and reach a hundred of them directly with the same offer. A hundred answers, even mostly no, is a diagnosis. Two hundred clicks from people whose situation you never learned is not. We build lists like that for teams, and the counting step alone usually settles whether the ad was the wrong route or the offer was.
Learning what those ten people needed would help. Reaching similar people directly could be useful, but it's a different test: now the seller is introducing the product, rather than ChatGPT recommending it during a conversation.