In

Innovation Partnership Primer - free e-book for students and startups

Hacker News

Innovation Partnership Primer - free e-book for students and startups

I'm writing e-book curricula for business students and startup teams to learn about innovation partnership concepts, such as joint ventures, technology transfers, company analysis, and the like. The goal is quick easy introductions to many common topics, with summaries by ChatGPT for simplicity. Constructive feedback welcome. The e-book is free on GitHub and pay-what-you-wish on Gumroad. https://github.com/sixarm/innovation-partnership-primer

Share card

Actual performance

3points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
52%52% 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
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.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
38%38% 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
27%27% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: chatgpt · Missing: mac, agents, macos
18%18% predicted probability of success on Product Hunt, 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 · Strong signals: chat · Missing: web3, crypto, cryptocurrency
5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

I
I wrote a book about startups. And dragons. NBD.75%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I wrote a book about startups. And dragons. NBD.

Hacker News3
VentureProof
VentureProof76%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Structural diagnostic for startups and innovation products

Indie Hackers1$600/moanalytics
I
I wrote a book about Elasticsearch and I'm making it free for students74%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I wrote a book about Elasticsearch and I'm making it free for students

Hacker News4
Bo
Book About Underdog Innovation and Thinking Outside the Odds56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Book About Underdog Innovation and Thinking Outside the Odds

Hacker News4
Lo
Loading Indicator Innovation44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Loading Indicator Innovation

Hacker News14
Th
The Innovation of Loneliness47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

The Innovation of Loneliness

Hacker News1
Xe
XeniaPenn - A craigslist for Penn students kicked out bc of Coronavirus30%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

XeniaPenn - A craigslist for Penn students kicked out bc of Coronavirus

Hacker News3
Vo
Volunteer mentors/tutors for students affected by COVID-1935%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Volunteer mentors/tutors for students affected by COVID-19

Hacker News5
Zu
Zuckerbergs Coursemash for Michigan Students31%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Zuckerbergs Coursemash for Michigan Students

Hacker News1
BellaTech Insights
BellaTech Insights72%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Exploring startups, AI, and the future of digital innovation

Indie Hackers