Fliple - iOS Contacts with Metro UI

Hacker News

This is my try at a iOS Contacts app replacement. I was frustrated by the fact that the default application wasn't showing contact pictures in lists, so I tried to design an app that makes full use of the images. Another issue I had with the default app was the number of taps until finding a contact, so I tried to minimize that too using various approaches: - put most contacted people on the main screen (app also proposes new tiles based on number of interactions) - group contacts (work, family, friends, etc.) then put a group tile on the main screen - search the contact list using T9 (3-4 taps to locate contact) - use action tiles to instantly communicate with a contact (phone, SMS, mail) for often contacted people At the moment the app is free, I haven't yet come up with ideas for monetization - if you have any, please share.

Visit product View on Hacker NewsApr 6, 2013

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

68%68% 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: new, using · Missing: mac, agents, macos

68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

63%63% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

53%53% 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

43%43% 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

19%19% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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