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I built an easy to browse map of all Amazon Lockers in the U.S.

Hacker News

I built an easy to browse map of all Amazon Lockers in the U.S.

Amazon Lockers are really useful for getting Amazon orders while on the road. Unfortunately, the search function on Amazon's site only lets you search around a particular address. This makes it hard to find lockers if you're in a rural area or on the move. So I scraped all the lockers and put them on a map. Pretty simple, but very helpful for road trippers, RVers, van lifers, etc. Ideally this should already exist, but it didn't.

Visit product View on Hacker NewsSep 23, 2022

Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

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

73%73% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

52%52% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

48%48% 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

47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

36%36% 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

15%15% 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

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

Incorrect prediction on native model

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