Ho

How did we do after 1st week of our launch?

Hacker News

How did we do after 1st week of our launch?

I just wanted to share with other fellow HN follower regarding how we did after 1st week of our launch of http://www.jackpotbuddy.com. Here are some Google analytic numbers: Date Range: 6/24/2012 to 7/1/2012 Visits: 522 Page View: 3875 Page/Visit: 9.02 Avg. Duration: 6:31 Bounce Rate: 13% We have not spent a single dime on advertisement, this is all Facebook/Twitter driven traffic. How do you think we did in our first week? Can others share their numbers? Thanks,

Share card

Actual performance

1points
1comments
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
73%73% 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: io · Missing: https docs, excited, just released
49%49% 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: google, single · Missing: mac, agents, macos
35%35% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: google · Missing: mobile apps, ios, personal
32%32% 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
31%31% 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
16%16% 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
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

Wh
What did you get done this week?68%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

What did you get done this week?

Hacker News1
To
Today I launch What did you get done last week reminder49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Today I launch What did you get done last week reminder

Hacker News2
The Urgency Journal
The Urgency Journal28%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

What did you get done this week?

Product Hunt+7
WT
WTFDYUM: Why the f*** did you unfollow me?62%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

WTFDYUM: Why the f*** did you unfollow me?

Hacker News7
UC
UChicago admissions asked me to find Waldo. I did.63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

UChicago admissions asked me to find Waldo. I did.

Hacker News149
Di
Did you ever stuck between two dresses?53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Did you ever stuck between two dresses?

Hacker News1
L3NS.ai
L3NS.ai76%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

1st 𝗔𝗜 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗠𝗮𝗿𝗸𝗲𝘁𝗲𝗿

Indie Hackerscommitment-full-time
Op
Opinion on website before launch? What did you understand?46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Opinion on website before launch? What did you understand?

Hacker News2
What did you do last week?
What did you do last week?23%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Evaluates your 5 bullet points

Product Hunt+9
To Did List
To Did List49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Track what you did, and not your almost dids'

Indie Hackers