A simple 'lost & found' side project

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I started foundcamera.com as a basic weekend project a little while back. I hoped to help a few people out and potentially facilitate some great success stories. I thought it improved upon what's out there already as it's super simple (no signup) and it puts the geographic element at the centre of helping people to find & return treasured photographs to their owners. It's recently picked up in popularity and I'm adding more lost and found items and seeing several hundred visitors each day. No successes as of yet. Any suggestions for getting more people to play detective and help return items? I want to get some green pins on the map! Are there any non-intrusive ways I could monetize it? Not to make a profit but at least to break even. How could I improve it for v1.1? Thanks

Visit product View on Hacker NewsAug 24, 2012

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

74%74% 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.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

50%50% 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: way · Missing: mobile apps, ios, personal

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

39%39% 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

39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: profit · 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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