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Running Shoe Price Comparison and Alerts

Hacker News

Running Shoe Price Comparison and Alerts

Hey HN, I’m a guy who runs a lot and is prone to spending too much money on running shoes - so I made a site to find deals and alert me when shoes on my rotation are on sale. I built the site with Elixir & Phoenix with LiveView and couldn’t be happier with the tech stack. A really nice feature of using this setup is that everything runs in a single logical app with no other languages or infrastructure: background & scheduled jobs, long running web scraping and ETL tasks, backend APIs, and even the frontend. I’d love to get feedback from others who love running and/or getting a good deal. Thanks! https://runningshoescore.com

Visit product View on Hacker NewsJan 16, 2024

Actual performance

3points

4comments

Did not reach leaderboard

Launch Intel predictions

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84%84% 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: single, tasks, using · Missing: mac, agents, macos

59%59% predicted probability of success on Product Hunt, 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

48%48% 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 · Missing: mobile apps, ios, personal

27%27% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

26%26% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

17%17% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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