Ca

Calculation Formulas for Quarter Dates

Hacker News

Calculation Formulas for Quarter Dates

Share card

Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto
92%92% 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.
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
50%50% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
44%44% 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 released
42%42% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
31%31% 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, revenue
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

De
Depoch – Unix Epoch for Dates46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Depoch – Unix Epoch for Dates

Hacker News2
SlayyDate
SlayyDate52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Where Real Dates Begin

Indie Hackerscommitment-side-project
Mi
Milestone Dates Generator36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Milestone Dates Generator

Hacker News1
Ai
Airlist – A nested outliner with Omnifocus like dates/perspectives47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Airlist – A nested outliner with Omnifocus like dates/perspectives

Hacker News14
DatePop
DatePop43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Autofill Notion with dates.

Indie Hackers1calendar
Th
The Traveler – News between dates37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

The Traveler – News between dates

Hacker News2
Re
React Nice Dates48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

React Nice Dates

Hacker News17
Am
Amazon Alexa for Friendships and Dates24%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Amazon Alexa for Friendships and Dates

Hacker News1
#datefromhome
#datefromhome54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Better digital dates

Indie Hackers1b2c
Au
Autofill dates and time slots in Notion36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Autofill dates and time slots in Notion

Hacker News2