landlords.lol
TrustMRRA Monopoly board where every square is real, buyable ad space. Claim a square from $1 and your logo goes on the board. Roll the dice and wherever you land, it sends you to that square's owner, so rent
A Monopoly board where every square is real, buyable ad space. Claim a square from $1 and your logo goes on the board. Roll the dice and wherever you land, it sends you to that square's owner, so rent is paid in clicks, not cash. Anyone can outbid you for $1 more and take your square. The board is the leaderboard.
Share cardActual performance
2customers
$949MRR/mo
Did not reach leaderboard
Traction signals
Domain Rating2
MRR growth 30d-19.3%
Launch Intel predictions
Analyze your own launch →
BetaListSuited for BetaList early-adopters · Strong signals: paid · Missing: web3, chat, crypto64%64% predicted probability of success on BetaList, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting35%35% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal34%34% predicted probability of success on TrustMRR, 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, revenue31%31% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos25%25% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Correct prediction on native model
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