Validate your startup idea before coding – MVP It

Hacker News

The validation playbook we all know: - Make a landing page - Get interested users' contacts - Reach out to potential customers - Collect feedback and pricing info - Build once you have 5-10 interested users I turned this process into one simple tool: https://mvpit.co Instead of using multiple tools, MVP It gives you: - Quick landing page creation - Smart contact collection + pricing feedback - Real interest tracking (beyond email signups) - Know exactly when (and what) to start building $45 lifetime access (no subscription) Built this because I needed it myself. Would love your feedback.

Visit product View on Hacker NewsFeb 18, 2025

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Actual performance

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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

59%59% 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.

AppSumoStrong fit for a featured deal · Strong signals: lifetime access, users · Missing: plus, platform, intuitive

56%56% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntOn track for Day 1 leaderboard · Strong signals: user, email, using · Missing: mac, agents, macos

50%50% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal

27%27% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

20%20% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Strong signals: subscription · 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 · Strong signals: smart · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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