Time to give crowdshipping a go?

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TinyCarrier is a web service that connects travelers and people who have a need to send or receive things. It could be personal stuff like books and clothing, a product that you have someone buy for you because it is not available in your country. Transporting items for other people is not a new concept, we just make it safe, social and global. This is not a package/parcel service. Carries will be packing the items themselves in their own luggage. Carrier and requester are responsible for reporting goods in customs. The service will support this with communicate managed information about each location and the service will we ranking and testimonial based similar to AirBnB and Couchsurfing. We will eventually be providing an API to allow for blogs, apps and curator services to make use of it as well. For people thinking: commercialisation of drug mules, silk road, etc. In stead of thinking that everyone are criminals, try think that they are not (because their aren't) and think about the benefits.

Visit product View on Hacker NewsMar 12, 2014

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3points

2comments

Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

93%93% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

66%66% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntOn track for Day 1 leaderboard · Strong signals: apps, new, tiny · Missing: mac, agents, macos

60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: personal, apps · Missing: mobile apps, ios, entrepreneurs

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit

14%14% 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.

Incorrect prediction on native model

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