My

My first SaaS app - Selfstream.io

Hacker News

My first SaaS app - Selfstream.io

Hi Hacker News, I have just launched my first SaaS application - Selfstream - http://www.selfstream.io . It is targeted at event organisers with small budgets, who want to extend the reach of their events, and easily stream them live on the internet. I have been producing managed live webcasts for a long time, so I decided to automate the process. I also wanted to build a SaaS product from scratch, as well as register a company, process online payments and all related administrative bits. Basically have a framework for any future idea. Now that the app is online, what would you recommend for acquiring early adopters and therefore validate my idea? For my next project, I will definitely validate my idea first, rather than dive into development! I would really appreciate any advice and feedback! Thank you!

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Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
67%67% 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 NewsStrong engagement from HN community · Strong signals: hacker news, ide, io · Missing: https docs, excited, just released
52%52% 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: new · 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 · Missing: mobile apps, ios, personal
33%33% 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
23%23% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue
14%14% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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