Ahaaa – notes at the right time

Hacker News

Hi people. I made little but useful application. It is primary for people who often call to somebody or for people who wants remind something before call. Has it happened to you that you finished a call and realized, you forgot to discuss something with the person? So with this app you will not forget anymore. Simply write a note in Ahaaa for a specific contact, and the next time this contact calls you or you call to it, your note will appear on the screen. The application allows you to choose a color for your notes so you will not overlook them. Other use case is if you have a lots of clients / customers, you can add some note to him and you immediately know who is who. App is free and without ads. Please let me know if you like it. Here is link to download it - https://play.google.com/store/apps/details?id=sk.spajdo.callernotes

Visit product View on Hacker NewsFeb 6, 2019

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2points

Did not reach leaderboard

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best fitHighest predicted score across all platforms for this description.

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

50%50% predicted probability of success on TrustMRR, 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

49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: google, apps, notes · Missing: mac, agents, macos

42%42% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

23%23% 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.

Correct prediction on native model

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