Our week long project - trying to do the wishlist better

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Hi guys, We have just built Ultimategiftlists.com My girlfriend keeps asking me what I want for Christmas. I also need to buy stuff for my nephew. So I wrote a list of stuff out for my girlfriend and sent her an email of links showing her the stuff I wanted. I found that my brother did exactly the same to show me what I should get my nephews. There had to be a better way to do this. Amazon wishlist exists but it doesn't do it as effectively as I wanted. Therefore my mate and I built our new site - www.ultimategiftlists.com - it's hopefully very simple to use and has a really cool feature called 'giftmark' which enables you to add items to your list on the move. We originally built it just for us, to solve the problem I describe above. But, we figured it could be useful to other people. We'd love any feedback you may have. Thanks in advance for looking at it.

Visit product View on Hacker NewsDec 1, 2012

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best fitHighest predicted score across all platforms for this description.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

61%61% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

58%58% 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: exist · Missing: https docs, excited, just released

45%45% 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 · Strong signals: way · Missing: mobile apps, ios, personal

39%39% 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

13%13% 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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