Gifter, an app I made to simplify gifting

Hacker News

So while working as a freelancer (self-employed) I wanted to create an app. The key incentive that drove me to create this app was that whenever it's time to gift stuff in my family we either buy funny but not useful stuff, things that you like (but maybe not the person you're gifting it to), or we just ask the other person what they want. So my app does the following: allows you to add wishes, organize them with occasions (Christmas, Birthday, etc.) and share them with your family and friends. It's completely free and monetized with ads and currently only available on Google Play. Now I'm wondering is this something that people would actually use like I do? I found other apps on Google Play, but none of them really hit the core of the issue, or were just buggy and not really working. What are your thoughts on it? If the app is useful what's the best way to reach out to people that would use it?

Visit product View on Hacker NewsSep 16, 2023

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Product HuntOn track for Day 1 leaderboard · Strong signals: google, apps · Missing: mac, agents, macos

72%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.

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

59%59% 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

44%44% 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 · Strong signals: apps, google, way · Missing: mobile apps, ios, personal

44%44% 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

32%32% 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.

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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