FaangSupport – Easing Access to FAANG Customer Support

Hacker News

Hi HN! I'm building it. It's not uncommon to see complaints on HN about users being locked out of their Faang/Fortune 500 accounts, primarily by automated systems at these companies, and yet the provided support channels do not help. In Fact, one of these days, HN has become an unofficial support channel for FAANG. But what about those that don't know about HN? Enter FaangSupport. FaangSupport connects you and me to verified (via email) Faang Volunteers. When complete, the main interface will be an Inbox like layout, through which you can create tickets and correspond with a Faang employee. So my fellow HNers, would this work? Yes Faang Support is broken but would the solution look like this? Thanks HN.

Visit product View on Hacker NewsJul 27, 2023

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

78%78% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

70%70% predicted probability of success on Indie Hackers, 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 · Strong signals: interface, users · Missing: plus, platform, intuitive

46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal

40%40% 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

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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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