Blocs.me
TrustMRRBlocs is a website that creates habit building widgets and integrations for the productivity app Notion. On the website we sell the widgets for a lifetime or on a per widget basis. We would charge the
Blocs is a website that creates habit building widgets and integrations for the productivity app Notion. On the website we sell the widgets for a lifetime or on a per widget basis. We would charge the customer during checkout based on their selection.
Share cardActual performance
2customers
$4MRR/mo
Did not reach leaderboard
Traction signals
Domain Rating31
MRR growth 30d-42.3%
Launch Intel predictions
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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRFits verified-revenue profile · Strong signals: widgets · Missing: mobile apps, ios, personal65%65% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto49%49% predicted probability of success on BetaList, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released44%44% 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, intuitive38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Incorrect prediction on native model
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