Fi

Find travel destinations based on your preferences and budget

Hacker News

Find travel destinations based on your preferences and budget

Key Features: - A vast database with 3000+ cities, 950+ islands, and 190+ countries. - Rankings in categories like cost, attractions, safety, and infrastructure. Tools for personalized travel planning: - Preference Filter: Tailor your search to fit your desires, from weather to food preferences > https://theworldtravelindex.com/en/filter/results/?query=# - Budget Filter: Find destinations that match your financial plans > https://theworldtravelindex.com/en/budget-tool#find-destinat... - Destination Budget: Calculate the budget for your chosen location > https://theworldtravelindex.com/en/budget-tool#calculate-bud... - Compare Locations: Not sure where to go? Compare and contrast potential destination > https://theworldtravelindex.com/en/compare/cities That's just for the start, and would love to get your feedback.

Visit product View on Hacker NewsDec 3, 2023

Actual performance

3points

4comments

Did not reach leaderboard

Launch Intel predictions

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

46%46% 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.

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

46%46% 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

41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: 000, io · Missing: https docs, excited, just released

29%29% 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 · Missing: arr, mrr, revenue

10%10% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

8%8% predicted probability of success on Product Hunt, 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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