Do
Docusend for Explainers/Video Content
Hacker NewsDocusend for Explainers/Video Content
We made a site to control who sees our explainer video while raising (the video showed critical UX insights). Would this be useful for anyone here? - Fresh link generator for any person/group/purpose - Video can't be downloaded (can be screen recorded of course) - Ability to turn on/off the link, ban IPs, and see how many time people watch it (we've shut a few links off that got >100 views within a couple days) What it looks like (very simple): https://imgur.com/a/pLCdNvT
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TrustMRRFits verified-revenue profile · Strong signals: video · Missing: mobile apps, ios, personal65%65% predicted probability of success on TrustMRR, 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 · Missing: plus, platform, intuitive58%58% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: plain · Missing: mac, agents, macos44%44% 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: ide · Missing: https docs, excited, just released42%42% 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, revenue20%20% 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, crypto2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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