20
2048bid.lol – Rank your product by playing 2048
Hacker News2048bid.lol – Rank your product by playing 2048
As the title suggests, this is inspired by outbid.lol, but instead of bidding money, rank your product by playing the 2048 game. It also happens to be a game I spent an alarming amount of my first year of my PhD on, so this gave me a nice excuse to go back to it lol. A similar take on the idea is flappybid.lol (not affiliated).
Share cardActual performance
3points
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting44%44% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos36%36% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide · Missing: https docs, excited, just released36%36% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue26%26% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive24%24% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal17%17% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
Similar products
A
A toy for playing around with cubic Bézier curves58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
A toy for playing around with cubic Bézier curves
Hacker News1Pl
Playing with Generics and atomics in Go 1.1951%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Playing with Generics and atomics in Go 1.19
Hacker News6outbid lol56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Try an outbid lol alternative where websites pay to rank.
Indie HackersIm
Imprecise.lol36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Imprecise.lol
Hacker News2Sh
Shoutouts.lol36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Shoutouts.lol
Hacker News8
BidTube13%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Outbit.lol For Youtubets
TrustMRRMarketing
outbidders.lol14%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Sit at #1 or get outbid.
TrustMRROtherge
getoutbid.lol13%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
TrustMRROther
Designerbid.lol10%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Pay to rank in Design Directory
TrustMRRMarketplaceAu
Author Rank21%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Author Rank
Hacker News2