I sold digital products before I ever wrote code. Now I've built the platform I wish existed back then.

I think this is a great idea starting new myself

Selling before coding is a great signal, and the zero-fee promise is compelling. One metric layer I’d add early is listing impressions → qualified product-page visits → checkout starts → purchases, with each seller able to see their own referral/source breakdown. That separates useful discovery from leaderboard curiosity and gives you a clear product roadmap. I’m also testing a free fee checklist for digital sellers—disclosure: I made it: https://payhip.com/b/FIY1B

A practical way to separate distribution from vanity traffic is to score each channel or audience 1-5 on pain, budget, authority, and urgency. Pain means the problem is already articulated, budget means there is existing spend, authority means the person can act, and urgency means there is a deadline. Track qualified conversations, repeat visits, and a concrete next step, not raw clicks. For a marketplace, start with one narrow buyer and seller niche, interview 5 of each, and expand only when both sides have a repeatable path to a first transaction. That makes the customer signal easier to read before adding more categories.

The chicken-and-egg framing is spot on. Transparent paid placement may solve the initial visibility problem, but I’d watch the separation between paid reach and earned proof: repeat visits, qualified clicks, and downstream activation are stronger signals than impressions alone. A small “why this is shown” label plus a simple quality floor could help buyers trust the leaderboard without turning it into another opaque feed. How are you distinguishing a placement that gets curiosity clicks from one that actually finds product-user fit?

I can offer the seller's side. I make a desktop app and have submitted it to a few dozen directories and marketplaces over the past year, so I have seen a lot of listing pages from the supply end. The thing that decided whether a directory was worth my time was never rank. It was whether the category matched what a buyer actually types when they have the problem. A great slot in a vague category sent me curiosity clicks that bounced. A plain slot in a narrow, intent-matched category sent a trickle that converted. So before selling placement, I would invest in category structure: narrow, job-shaped categories are what make paid ranking worth paying for, because rank inside a vague category is rank in front of the wrong people.

On the dashboard metrics already being discussed here, one detail decides whether sellers believe the numbers: let each listing pass a tracking parameter through to the seller's own destination. A platform-reported click count is something I have to take on faith at renewal time, and marketplaces have trained sellers not to. A number I can see in my own analytics is something I will happily pay against, and it costs you a query string.

Are you planning per-listing referral tracking that sellers can verify on their own side, or does that wait until the catalogue is bigger?

The pay-to-rank transparency is an interesting differentiator. Most platforms bury the algorithm so sellers can't see what they're competing against. Making the bid structure visible changes the game — you're not chasing a black box, you're making a real business decision about what visibility is worth to you.

Low hundreds in early revenue + 18 listings is a reasonable start for something this new. The distribution chicken-and-egg you described from KDP is the exact same one Gumroad sellers hit, so you've clearly found a real pain.

Curious what the buyer conversion looks like on the listed products so far — are purchases happening through the platform or are people mostly browsing and then buying direct?

Your revenue model and your sellers' success point in opposite directions: you get paid when someone buys rank, not when someone buys a product, so the business can grow while nothing actually sells. I would take a small cut of sales instead, because it forces you to solve buyer traffic and it hands you the one number that would make this thing spread. The story of the coloring books with zero traffic is your real asset here, so what is bringing buyers to the leaderboard this week?

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Will you provide any other metrics except traffic/eyes count (on each listing) on some dashboard, like for example user clicks on elements or external redirections, and so on?

Free listing solves the seller side, but a marketplace usually dies on the buyer side, and that is the part I would worry about. A creator with no audience lists, buys the top slot, and the only people browsing are other sellers. Where does buyer traffic come from today, and what brings back someone who is not selling anything themselves?

This hits home. I'm a solo dev selling Windows tools on Gumroad and Whop — discovery is my biggest bottleneck too. Nobody finds you without an audience.

The transparent pay-to-rank leaderboard is a fresh take. Just checked out dropanda.xyz — will list my tools and see how it goes. Good luck with v2!

The low-hundreds in revenue is the strongest signal here. Are sellers who pay for ranking actually getting meaningful traffic or sales from the visibility, or are they mainly paying for the promise of being seen?

Selling before coding is a great reminder to validate demand first. The zero-traffic problem on marketplaces is real—distribution deserves as much attention as product quality.