Fullexperience.co – We help get your things returned

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On my recent trip to Iceland, I lost one of my cameras. While I was lucky enough to get recommendations from the r/VisitingIceland community on Reddit to post in a Facebook Group, it made me realize how stressful it can be to lose personal items while traveling, especially when there's no direct way for someone to contact you if they find your belongings. I thought creating NFC + QR stickers would offer a digital touchpoint, making it convenient and quick for the finder. You can customize the look of the QR code with a background image of your choice without compromising its functionality, and when the stickers are scanned or tapped, lead to a public profile with information you're comfortable sharing. You can customize this profile with any links you want, including your email, phone number, Instagram, or anything else. Built with React, Supabase, Vercel Would love to hear your thoughts and if you have any suggestions!

Visit product View on Hacker NewsSep 25, 2023

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

94%94% 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: email, code · Missing: mac, agents, macos

54%54% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

46%46% 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

40%40% 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, including · Missing: https docs, excited, just released

25%25% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

19%19% 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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