Crowdsourced viral Costco inventory tracker

Hacker News

I built KirkList after repeatedly seeing viral products on TikTok/Instagram, rushing to Costco, and leaving empty-handed. Costco's inventory varies wildly by location but their app only shows online stock. KirkList lets shoppers crowdsource what's actually on shelves. Spot something? Post it with location and price. Looking for that viral Biscoff Cheesecake or Stanley cup? Check what others have found nearby. Key design decision was optimizing for quick posting - users need to snap and share while actually shopping, not fill out forms later. Would appreciate feedback on UX and thoughts on scaling crowdsourced inventory tracking.

Visit product View on Hacker NewsSep 25, 2025

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

75%75% 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.

AppSumoStrong fit for a featured deal · Strong signals: users · Missing: plus, platform, intuitive

57%57% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

49%49% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

43%43% predicted probability of success on TrustMRR, 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.

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

17%17% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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