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Pomo – Manage your Stripe promo codes without code

Hacker News

Pomo – Manage your Stripe promo codes without code

Hi Everyone, I just launched an entirely free tool - usepomo.com Pomo - Create, manage, and track unique batch promo codes in Stripe without bothering your development team. Pomo was created to address a past pain point: the inability to batch create unique promo codes (with a predetermined prefix) using the Stripe Dashboard. The only options were to work with your tech team to manually create those promo codes via API or to have them build a tool for it (which can also be done using Retool or Bubble). I developed Pomo so that any team member with no coding experience can simply sign up, enter their Stripe API keys, and batch create hundreds of promo codes with just a few clicks. You can then export these promo codes if needed for your growth campaigns. Feel free to give it a try if you encounter the same issues I did. I welcome any feedback. Thanks, everyone, and happy Friday!

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Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
78%78% 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: stripe, using, coding · Missing: mac, agents, macos
70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
48%48% 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
29%29% predicted probability of success on AppSumo, 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
22%22% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Strong signals: growth · Missing: arr, mrr, revenue
18%18% 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.

Correct prediction on native model

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