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Static e-shop and stripe checkout

Hacker News

Static e-shop and stripe checkout

Hi I did some major updates to the shop editor (WIP), you can play around with the live demo here: https://shop.listws.com/v2/store/demo/editor/demoshop.listws.app/default/ I still need to improve a lot the UX and the navigation between the form editor, the preview pages and the html code, but I am constantly working on this. Now you can deploy the result to a CDN, but I am working on integrate this to a Wordpress instance Let me know any feedback!

Visit product View on Hacker NewsJan 14, 2022

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Product HuntOn track for Day 1 leaderboard · Strong signals: stripe, code · Missing: mac, agents, macos

72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal

53%53% 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 · Missing: https docs, excited, just released

43%43% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

32%32% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

31%31% 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

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

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

Incorrect prediction on native model

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