Tr

Travel Guide Tool – Personalized Recommendations and Itineraries

Hacker News

Travel Guide Tool – Personalized Recommendations and Itineraries

Built a simple tool for travelers. Input your city and preferences, get back a list of recommendations or a detailed itinerary. Includes non-touristy spots, practical tips, and Google Maps links for every place mentioned. No signups required. Recommendations: Includes attractions, rentals, local tips, hidden gems. Example: Café La Biela. Itineraries: Detailed plans considering your preferences. Give it a try. Also live on Product Hunt: https://www.producthunt.com/posts/trip-bespoke Looking for feedback or any thoughts on how to improve.

Share card

Actual performance

12points
9comments
Made the leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
56%56% 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 HuntUnlikely to reach the leaderboard · Strong signals: google · Missing: mac, agents, macos
47%47% 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
44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: personal, google · Missing: mobile apps, ios, entrepreneurs
36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
30%30% 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.
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

Similar products

Km
Kmote, personalized product & travel recommendations45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Kmote, personalized product & travel recommendations

Hacker News1
Pe
Peloton Personalized Recommendations37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Peloton Personalized Recommendations

Hacker News5
KINPEN
KINPEN14%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Travel app to get recommendations from locals.

Indie Hackers2travel
TasteLanc
TasteLanc47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

An app providing personalized dining and nightlife recommendations in Lancaster, PA.

TrustMRR15$750/moArtificial Intelligence
Arbeitr
Arbeitr17%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Personalized job recommendations that go beyond the paycheck

Indie Hackers2ai
Lorekeep
Lorekeep42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Personalized book recommendations

Product Hunt+1
Pe
Personalized book recommendations with Librarian AI41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Personalized book recommendations with Librarian AI

Hacker News150
Gustar
Gustar30%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Personalized Meal Recommendations

Indie Hackerscommitment-side-project
Guide pro
Guide pro35%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Travel

Indie Hackerscommitment-full-time
Ti
Tired of Netflix recommendations? Televisor57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Tired of Netflix recommendations? Televisor

Hacker News1