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Spark – Shopify for Microschools

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Spark – Shopify for Microschools

In 2018 I started a Microschool (a school with under 100 students). Fast forward it now serves ~100 students. It wasn't a straightforward process and involved a lot of false starts. We built Spark to help more people avoid our mistakes and start a high-quality Microschool from day one. In a post school choice world, we think education shifts from a centralized system of big schools to a decentralized network of small schools. The platform has limited functionality, but you'll get the idea. After the funding goal is reach we provide a six-week training program, curriculum, and an OS to run their microschool. Reach out if you have any ideas or would like to chat about starting a Microschool. I'm @michaelaolaya on X.

Visit productView on Hacker NewsDec 19, 2023
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2points
1comments
Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Strong signals: mistakes, started · Missing: supports, reddit linkedin, podcasting
90%90% 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: 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.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: education · Missing: mobile apps, ios, personal
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
33%33% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: training, shopify · Missing: arr, mrr, revenue
25%25% 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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