AudioDiary, an AI-supported mental health diary

Hacker News

I have posted this before, but I've added so many new features since, plus I posted a comment recently on HN about it which was pretty well-received, so I thought I'd make another post! This has been launched since last May and a lot of users love it! I'm a solo founder, and recently have somewhat steadily been getting enough income to just about cover my living expenses without any marketing. I have about 12k users so far, and It’s fulfilling and great to see people use and love a product I’ve built. I’m obviously highly motivated to grow so it keeps me busy. P.S. I've gotten some feedback here on HN last time around making the pricing more transparent on the landing page.. I haven't actioned this yet as I'm not sure how to go about it because there are different prices depending on region, and slightly different prices due to how iOS and Android work... I thought putting "About USD$30 for an annual subscription" on the landing page but that seemed a bit strange. It is about $30 for an annual sub in the US and there's a monthly option for about $6 per month. Would love if someone had advice for how they approached this problem.

Visit product View on Hacker NewsMar 7, 2024

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Actual performance

2points

Did not reach leaderboard

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

84%84% predicted probability of success on Indie Hackers, 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 · Strong signals: user, new · Missing: mac, agents, macos

66%66% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: ios, month, monthly · Missing: mobile apps, personal, entrepreneurs

58%58% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

42%42% predicted probability of success on Acquire.com, 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

37%37% 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: plus, users · Missing: platform, intuitive, reviews

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: audio · 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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