ReelDrop.io

ReelDrop.io

TrustMRR

I built ReelDrop because running Instagram takes five tools that don't talk to each other. It's the only one where DM automations attach to a post while you schedule it, live the second it publishes:

I built ReelDrop because running Instagram takes five tools that don't talk to each other. It's the only one where DM automations attach to a post while you schedule it, live the second it publishes: verified follow gates, timed follow-ups, message rotation. One idea becomes a themed 10-slide carousel in 30 seconds, and captions come from AI that watches your actual footage. Everything runs through the official Instagram API. Free plan; Creator is $29/mo or $149/yr.

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Actual performance

18customers
$256MRR/mo
Did not reach leaderboard

Traction signals

Domain Rating13
MRR growth 30d-35.4%

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
56%56% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
45%45% 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, intuitive
40%40% 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, revenue
27%27% 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, crypto
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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