http://52wins.com

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http://52wins.com

My friend and I, while working on an employee feedback application, worked on this productivity application in spare time. This application will allow users to set 5 goals for the year and then ask two questions every week per goal. Q1. What did you do to inch closer to this goal this week? Q2. What lessons did you learn for this goal this week? Since we are working full-time on another startup (which is in closed private beta), we are giving this app to be used free of charge to 10,000 users in the world. I have put together a very basic page where we can gauge the interest of a person in their productivity by asking their goals. Can you suggest if I can do something else as well?

Visit product View on Hacker NewsDec 17, 2014

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Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: 000, io · Missing: https docs, excited, just released

61%61% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

60%60% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: users · Missing: mobile apps, ios, personal

53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: user · Missing: mac, agents, macos

44%44% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

28%28% 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

13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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