Review my startup: AtticTV, MusicTV (MTV) for the Youtube Generation

Hacker News

Link to website: http://www.attictv.com AtticTV is a music video site that focuses on providing a super "kick back and relax" experience while watching music videos. We think it would be an excellent companion while you code :) Many people currently use Youtube as their primary source of watching music videos. But, it's hard for them to discover as they would need to know the name of the song + artist name. And it's a rather irritating experience to create a playlist and manage different types of playlist content Our big idea is to try to be the default way that people enjoy music and watch music videos while they work or are doing something else and want to have some music in the background, plus the ability to entertain themselves with a music video whenever they want to. The feeling you get when you leave MTV playing on a TV in the background while you're at the gym or getting some work done. The experience is very simple and straight forward where you load up the site, pick a genre you like, and enjoy the best music videos (we're still working very hard on this part to improve it) from all over the web for that particular genre. If you hear a song you like, you can always add it to your personal playlist for easy access. (you have to log in with Facebook to create your own playlist). We're still in beta and are making a lot of changes and have a lot of work to do but wanted to get some feedback.

Visit product View on Hacker NewsFeb 15, 2012

Share card

Actual performance

34points

29comments

Made the leaderboard

Launch Intel predictions

Analyze your own launch →

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

95%95% 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: code · Missing: mac, agents, macos

72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: plus · Missing: platform, intuitive, reviews

60%60% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

54%54% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

11%11% 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

Similar products

Review my Startup - Sqardius51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Review my Startup - Sqardius

Hacker News1

Review my startup - Biographid52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Review my startup - Biographid

Hacker News1

First Review of MakerBot Replicator 5th Generation38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

First Review of MakerBot Replicator 5th Generation

Hacker News3

Review my startup - Iphone meetups45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Review my startup - Iphone meetups

Hacker News1

Review my startup, Kiddom - made for kids56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Review my startup, Kiddom - made for kids

Hacker News9

Review Our Startup: Jobiki – Find Jobs with the Best Culture56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Review Our Startup: Jobiki – Find Jobs with the Best Culture

Hacker News23

Quiply 2.0 – Next generation company review app33%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Quiply 2.0 – Next generation company review app

Hacker News7

My first startup - So Yummy54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

My first startup - So Yummy

Hacker News3

Red Quintal - Not every startup is from the valley41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Red Quintal - Not every startup is from the valley

Hacker News1

startup to startup24%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

TrustMRRSoftware

Browse all products Analyze your launch