An

Android Material Google Location Suggest

Hacker News

Android Material Google Location Suggest

Share card

Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: google · Missing: mac, agents, macos
63%63% 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 · Strong signals: google · Missing: mobile apps, ios, personal
60%60% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
45%45% predicted probability of success on BetaList, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
33%33% predicted probability of success on Indie Hackers, 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
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.
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.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
27%27% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

Ma
Material SPA in Lisp with 500ms TTI and 11k gzipped50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Material SPA in Lisp with 500ms TTI and 11k gzipped

Hacker News12
Ma
Material for MkDocs 640%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Material for MkDocs 6

Hacker News1
An
Angular Material with ngRoute34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Angular Material with ngRoute

Hacker News5
AnyCoord
AnyCoord46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Spoof location for iphone & android

Product Hunt+4
Lo
LocationManager – Location Library for Android39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

LocationManager – Location Library for Android

Hacker News1
An
Android App: Google's material design concept. It is fun to work with31%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Android App: Google's material design concept. It is fun to work with

Hacker News1
Sh
Show HN:Elephant Is a Based on Material Design PHPHub Unofficial Android Client39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Show HN:Elephant Is a Based on Material Design PHPHub Unofficial Android Client

Hacker News1
An
Android LiveData Location Provider37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Android LiveData Location Provider

Hacker News1
Po
Pokemon Sniffer – Rarest Pokemon Location56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Pokemon Sniffer – Rarest Pokemon Location

Hacker News1
La
LazyScout - Zipcar for location scouting44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

LazyScout - Zipcar for location scouting

Hacker News3