Tripnly Lisboa City Pass – 5 Days for 1€

Hacker News

We’ve been building a fully digital city pass for Lisbon that you can use right away without downloading an app. You can explore 50+ attractions, museums, tours and local experiences with a single pass. For December, I set the price to 1€ for 5 days so people can try it without friction. Promo code: TRIPNLY-LOVES-YOU What’s different about this project: – It works entirely in the browser, no signup barriers. – It’s built to serve both tourists and locals, not only visitors. – It combines a city card, discounts, and a loyalty system in one tool. – My goal is to experiment with how digital passes can improve city exploration and support small local businesses. I’d really appreciate feedback from the HN community — on the UX, the idea itself, the onboarding flow, or anything that feels confusing. Happy to answer questions and discuss the technical side as well.

Visit product View on Hacker NewsNov 26, 2025

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Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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

67%67% 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.

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

50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Strong signals: single, using, code · Missing: mac, agents, macos

43%43% 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

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

13%13% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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