Made some improvements to our site, would love your thoughts

Hacker News

Hi guys, We created getinspired365.com a month ago and have made some big improvements based on the comments you made. Today is a big day for us - we are trialing our new 'tribute' page, with a dedicated slideshow for someone/event. We are really excited about it. The tribute page works in much the same way but it provides a user with a great slideshow effect. Within this slideshow there are many quotes, pictures and lots of useful information about that person or subject. We'd love to hear your feedback and how we can improve it. We are very much focused on inspiring people but also feel there is a bit of a market in creating these types of tribute pages - which we don't think have been done (in this way) before. thanks

Visit product View on Hacker NewsMar 8, 2013

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Did not reach leaderboard

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

82%82% 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.

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

77%77% 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: excited, ide, io · Missing: https docs, just released, exist

48%48% 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: month, way · Missing: mobile apps, ios, personal

44%44% 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

42%42% 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

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.

Correct prediction on native model

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