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I spent a few weeks building a private label brand for Amazon – AMA

Hacker News

I spent a few weeks building a private label brand for Amazon – AMA

Hey there HN! So for the last few weeks I decided I wanted to learn more about selling on Amazon and FBA - so I did what any normal hacker would do. I bought a website - https://www.chargeduck.com - Wrote some funny copy (Well I think its funny, but I suppose thats subjective) and then I went a step further. I called up suppliers, had samples made, designed packaging and even through some of that cheeky copy on the box. As I've been talking to people over the last week or two - especially other entrepreneurs its become apparent that this is a world a lot of people don't understand all that well or even at all. So I figured why not Show you guys what I did and open it up to questions if you're interested. I'll hang around for the next few hours and if you're interested I'll even tell you about what my plans are for the future with this and other products! Looking forward to seeing what you all have to say

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
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best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: entrepreneurs · Missing: mobile apps, ios, personal
55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: open · Missing: mac, agents, macos
52%52% 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, intuitive
32%32% 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
12%12% 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.

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