SpellReach
Product HuntOptimize your Reddit post using AI + Reddit post performance
Share cardActual performance
188upvotes
27comments
Made the leaderboard
Traction signals
Makers1
Launch Intel predictions
Analyze your own launch →Product HuntOn track for Day 1 leaderboard · Strong signals: using · Missing: mac, agents, macos72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal57%57% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting51%51% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto28%28% predicted probability of success on BetaList, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Correct prediction on native model
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