Lean Contact Management for Slackers

Hacker News

To be honest - I have been holding this off for too long. After several months of testing and iterating based on feedback (mostly from people I know in person) I'd like to get some public (and appreciated) feedback from you guys. I still see a lot of people missing accurate contacts in their phones and adding/modifying/deleting manually contact information on phones (including myself but to a much lower degree in the meantime - guess why). So I wanted to build something really simple which: a) would guarantee me the highest probability of having access to the really latest contact information of my contacts (no dups, no merging,... ) and b) would retrieve updates from my contacts onto my phone as fast as possible (read: seconds) without any manual intervention being required So here we go: https://leansync.com Some additional infos: - registration is possible with any email address (needs to be confirmed) - device sync is done via Google Contacts and therefore an existing Google account is required for device syncs (.. me praying to the quota gods...). The infrastructure for IPhone and Android apps (direct sync without the necessity for a Google account) is there already and the mobile apps are on the list. - a lot of time went into the copy and although it has been reworked many times I still feel there's room for improvement (any suggestions?) - aesthetics is important and I did as much as possible by myself (I'm not a designer) for the time being. In the rare case this could lift off a design/theme overhaul is on the list - this is a private effort and not backed by anyone else except me, myself and I

Visit product View on Hacker NewsFeb 11, 2013

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

91%91% 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: slack, google, apps · Missing: mac, agents, macos

72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: mobile apps, apps, month · Missing: ios, personal, entrepreneurs

62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, io · Missing: https docs, excited, just released

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.

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 · Missing: arr, mrr, revenue

24%24% 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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