Netflix – Jump to location in seconds ?t=

Hacker News

Since I cannot post this as a TIL on Reddit (it violates a rule...) I thought I'd post it here as I don't have a personal blog and would like to share. Today I discovered jump to location in seconds in Netflix by ‪adding ?t= eg: http://www.netflix.com/watch/70140716?t=140 Bender heckling Elzar to knock it up another notch BAM! I thought to myself, since you can do ?t= in YouTube you should be able to in Netflix. I was right :) If you've got a subscription to Netflix try it out.

Visit product View on Hacker NewsJan 22, 2016

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Actual performance

3points

Did not reach leaderboard

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

69%69% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

61%61% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: subscription · Missing: arr, mrr, revenue

22%22% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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