I created my first digital download, you can have it for free!

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Hey HN, I created my first digital download, a printable dual timeline calendar for 2014. In an effort to create more products this year I'm sharing this in some of my favourite web places in the hope I'll get valuable feedback and learn from these experiments. While the end product may not be technical, the type of product and delivery method are areas I'm really interested in. The calendar layout was something I've used myself in pen & paper form and has been more recently inspired by bulletjournal.com, the GTD method and quantified self movement. It may be of use to those of you interested in design, analog note-taking & tracking metrics/data. I use it to split work from home, track calories in/out & for income/expenses... You can also use it as a couples calendar, a single line journal, track your mood, your run times - whatever data you'd like to collect over the coming year! Use the code hn2014 to make it a free download. Feedback is really appreciated as it will help me to improve my ideas & products. CalCal - A simple printable calendar - http://gum.co/IEMpg Thanks guys, hope you'll find it useful!

Visit product View on Hacker NewsJan 3, 2014

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

65%65% 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: single, code · Missing: mac, agents, macos

64%64% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal

52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: lua, ide · 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.

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

36%36% 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

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

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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