Surprised my wife with a QR code linking to our son's personalized site

Hacker News

Simple as that.. I made a site with a heartfelt message for her, our son’s birth date, and some photos of the three of us. The site generates a QR code, which I printed and placed in a photo frame on her desk. Curious, she scanned it and absolutely loved the gift! I decided to share the idea with other parents, and the reactions were amazing! Some sent it to grandparents ('Thank you for being such a loving grandparent') and even uncles and aunts! Anyway, just sharing this for anyone who enjoys unique and budget-friendly gifts, haha Especially with Christmas around the corner!

Visit product View on Hacker NewsDec 16, 2024

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

85%85% 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.

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

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: personal, way · Missing: mobile apps, ios, entrepreneurs

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

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

33%33% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

31%31% 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

21%21% 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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