Ne
Need feedback on the design and copy
Hacker NewsNeed feedback on the design and copy
Can you guys please critique this home page design and content for an upcoming product. Please feel free to be honest. All kinds of comments are welcome. I am here to learn. There are some dummy images in the testimonial and mobile app section which are used for representation purpose only since we did not have access to actual screens. Here is the link - https://www.dropbox.com/s/2acilcmgigxpdbf/New-FabMath.jpg?dl...
Share cardActual performance
1points
Did not reach leaderboard
Launch Intel predictions
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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting77%77% 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.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: new · Missing: mac, agents, macos31%31% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released26%26% 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 · Missing: arr, mrr, revenue13%13% 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, crypto1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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