Thanks for the hunt, @_jacksmith! We had some fun putting this little side project together.
There are a bunch of great "Best of" and "Top" leaderboards using Product Hunt data, but not a lot of focus on the bottom. We think there's a lot to be learned from projects that didn't reach their potential for one reason or another. That's why we tried to pack in so much info to the leaderboard (i.e. headline, maker/hunter count, comment count, category). You can do a bit of analysis on some of these projects and try to piece together what might have gone wrong. Was the headline too blind/clever? Did the Maker not engage enough? Was the project not explained or presented clearly with the assets provided? - So it can be a bit of a learning tool.
Plus, it's interesting to browse some of projects on this list. Some are great, some are ridiculous, some are fantastically terrible. Hopefully this is a chance to see some projects that you never would have noticed otherwise.
The idea came up a few months ago when our first project was hunted, but we didn't find out about it until 8 days later. That project currently has a whopping 6 upvotes (*including* one vote from me, and one from my wife!), and I was convinced we had to be one of the lowest performing projects on Product Hunt. I couldn't find a way to find out - so Product Runt was born. Unfortunately, it turns out that that project wasn't even "featured" so we wouldn't qualify for this list anyway, but whatever - we wear our failures with pride! :)
Thanks for checking us out.
We hope you find this little project useful!
Great idea and good insight behind it. Is it just a straight binary count?
I'm sure timing and lack of initial pickup could leave a great product down the timeline.
Would be interesting to use some algorithmic magic to try and predict the ones that nearly got away.
@nickobennett Thanks! Yes, in terms of tracking upvotes over time. Because there are so many projects with the same upvote counts, it's ordered by projects that were first to hit the specific upvote #. In other words, older projects with the same upvote count are higher on the list.
Algorithmic analysis would be cool, but there's a lot of subjectivity to factor in. That'd be a real challenge I bet.
@omicaustin OK, makes sense, thanks for the note. Agree with you, it's difficult to make the calls on any algorithmic bias. Ultimately it's down to individuals decisions on upvote# - but post-time and key node pick up are often factors that trigger network effect. I was thinking you could find a way to map the popular patterns of post-time/network-activity and place a compensation factor on the products in the bottom 100 that fell on the troughs in that map. That way 'potentially' applying a second chance pick up factor to the ones that slipped through. Possibly a little complex, but could be fair. 🤓
At least 10% of the bottom 100 are trump related. I'm guessing we've hit peak trump now. Might as well cancel those next couple of trump products.
My actual thought is, now that people can see the bottom 100, how many of them will get upvoted past the bottom 100? Someone did something like this a while back for Pandora or Spotify where they created a feed of music that hadn't ever had one listen, just to get those songs one play.
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How ironic it would've been if Product Runt also hit the bottom. Would they've added themselves to the list?
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So the real bottom is the 101st position from the bottom :D So bad products that they are not even bad enough :D
I'm thinking of developing a site that only shows products related to Donald Trump, but I can't think of an appropriate word that rhymes with Hunt and Runt. Oh, wait, got it.
Product Runt
I Code Dis
Fika
Product Runt
Fika
Product Runt
data.world
Fika
Slackstarters
Slackstarters
Book Your Sales
Product Runt