InputKit
Indie HackersCustomer Feedback Software
We're working on InputKit to help business owners deal with an important but overlooked opportunity: after-sales follow-ups. It lets them easily follow up with their clients to get feedback, reviews, referrals and more.
Share cardActual performance
26followers
$60,000MRR/mo
Made the leaderboard
Launch Intel predictions
Analyze your own launch →Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting65%65% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos54%54% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released29%29% predicted probability of success on Hacker News, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: reviews · Missing: plus, platform, intuitive24%24% 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, revenue17%17% 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, crypto5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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