RIVANT
Indie HackersReal profit & CAC analytics for e-commerce and SaaS
I built RIVANT because businesses often see their revenue but struggle to understand their real profit. It brings revenue, ad spend, fees, and other costs together to make profit and CAC easier to track
Share cardActual performance
Did not reach leaderboard
Launch Intel predictions
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Acquire.comFits revenue-generating acquisition profile · Strong signals: revenue, profit, saas · Missing: arr, mrr, profitable57%57% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released51%51% predicted probability of success on Hacker News, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos37%37% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto23%23% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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