Daze – Online returns without leaving home

Hacker News

Disclaimer: we’re currently live in Finland (Helsinki, Espoo, Vantaa). We hope to open other cities soon. Hey HN! Both me and my co-founder have had some terrible returns experiences in the past. There’s little to no customer interface in online returns. You have to do variations of: - finding boxes - taping - printing labels - Googling obscure logistics partners - commuting to a dropoff and back Why is this? Well, you can’t do reverse logistics through forward logistics infrastructure. Especially the ”first-mile” part of the return journey is traditionally viewed as a cost sink rather than a value driver. Daze picks up returns from your front door. We handle everything from that point onwards. You don’t even need packaging or labels. You'll receive tracking information as soon as we have shipped the item. Let me know what you think, whether you’re in Finland or not. Happy to hear from potential issues you encounter. And those of you near Helsinki, you can use promo code HN50 at checkout for -50% off. Please try us out!

Visit product View on Hacker NewsNov 11, 2023

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best fitHighest predicted score across all platforms for this description.

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

47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: code, open · Missing: mac, agents, macos

41%41% 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: io · Missing: https docs, excited, just released

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

nativeThis product was originally launched on this platform.

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

28%28% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

15%15% 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

2%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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