20k users in 3 weeks for monetized Instagram competitor

Hacker News

I co-founded a startup called Belacam (www.belacam.com). It's just like Instagram, except every "like" is a microdonation of real money. It provides the fastest way for content creators, charities, and everyday people to raise money just by posting a photo. In 3 weeks, Belacam has 20k+ users with a strong early foothold in Africa and East Asia - for example, Belacam is the 4900th most popular site in Nigeria. Come join us! WE ARE HIRING. IF YOU ARE AN Angular4 and/or Django dev and want to work with a rapidly growing startup, email me now - tanner@ambiafund.com

Visit product View on Hacker NewsAug 10, 2018

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3points

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, email · Missing: mac, agents, macos

56%56% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

TrustMRRFits verified-revenue profile · Strong signals: users, way · Missing: mobile apps, ios, personal

55%55% 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, podcasting

54%54% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

31%31% 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

22%22% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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