My

My 4th failed startup (2nd due to user acquisition costs)

Hacker News

My 4th failed startup (2nd due to user acquisition costs)

Hello HN, Later today I'll be shutting down the servers and moving on. This is my 5th startup and the 4th failure. The reason is very simple: I understimated the cost of user acquisition. This is the second time this happened. The dozens of users actually love the software and are using it on a daily basis. I'm ruthless when it comes to coding and money. So, if you are building a startup: do not ignore how much money you will have to spend to get a user. If you are not able to find that number, something could be wrong with your model. Maybe someone smarter than me could write something elaborate about user acquisition costs. RIP https://www.condoly.com

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, user, using · Missing: mac, agents, macos
81%81% 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.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
60%60% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal
35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
32%32% 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
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: smart · Missing: web3, chat, crypto
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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