Sh

ShipIT – From Customers to Product

Hacker News

ShipIT – From Customers to Product

Hello Startup School community. My name is Federico Pérez and I'm a SW Engineer from Argentina. If someone on your team is making software using GitHub, this tool is for you. ShipIT is a lightweight project management tool for that focuses on customer feedback and translating it into finished product. If you have a GitHub account check my MVP on: https://ship-it-app.herokuapp.com This tool already has 2 users that work with software and ship new features every week. And a new version is coming soon. Thanks for reading! Any feedback is valuable.

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: user, new, project management · Missing: mac, agents, macos
70%70% 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.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
49%49% 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: lua, io · Missing: https docs, excited, just released
42%42% 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 · Strong signals: soon, users · Missing: plus, platform, intuitive
38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal
32%32% 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
15%15% 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
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

Novaseed
Novaseed21%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Find customers already asking for your product

Indie Hackers
btw
btw

Delight your customers

BetaList
Id
Identifying, Segmenting and Contacting our Customers51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Identifying, Segmenting and Contacting our Customers

Hacker News11
Ou
Our first three featured customers57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Our first three featured customers

Hacker News3
On
Onva – how do your customers feel about your product?41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Onva – how do your customers feel about your product?

Hacker News1
Overlead
Overlead75%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Find customers who are literally asking for your product

Product Hunt+146Marketing
Au
Auto-ship product to your customers49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Auto-ship product to your customers

Hacker News5
Sc
Scholtz – Find customers and users that want your product51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Scholtz – Find customers and users that want your product

Hacker News5
Cu
Customers are your best advertisers51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Customers are your best advertisers

Hacker News9
Suggested
Suggested22%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Build a better product for your customers

Indie Hackers7b2b