How To A/B Test a Product

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A/B testing is a big part of product management. Knowing what to look for when comparing between different product options is important. Kevin Wei talks through how to successfully A/B test a product before launch and what your interviewer will expect of you in your product management interviews.
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Chapters -
00:00 - Introduction
00:47 - Hypothesis
01:10 - Methodology
02:07 - Metrics
02:43 - Trade-offs
03:20 - Impact
#productmanagement #pminterview #tech #productmanager #entrepreneurship #product #prodmgmt #exponent #execution

[@tryexponent]

Don't leave your product management career to chance. Sign up for Exponent's PM interview course today: bit.ly/3uteTzQ

[@shailysahoo4606]

Loved the detailed information.

[@severtone263]

Thank you. Great content!

[@nathnaeldereje5127]

Amazing, Clearly explained everything.

[@Valli_A_Youtuber]

Well explained within 5 minutes!!!

[@nitinrawat4790]

Love it... Just what I was looking for..

[@tryexponent]

Perfect!

[@user-zj1wp2ud7p]

nice

[@karlfleener4520]

Great content! Would love to see more of these targeted to product designers and the rest of the design process.

[@tryexponent]

Noted! If you know any product designers who'd like to sit down with us, let us know!
More product design videos already scheduled this month. Stay tuned!

[@damianrobinson196]

Hopefully you see this comment. Could this framework be used in other instances, or would you recommend a different video for that? Not just an interview.

[@ashishkatariya9090]

How do you decide that ( time) till when you want to run the experiment?

[@tryexponent]

This is entirely dependent on the project. Some projects may take weeks or months to roll out and others may take just a few days.
For context, Exponent regularly tests new thumbnails and titles for our content on TH-cam and our website to see how it impacts learning journeys. We usually let these tests run for about 2 weeks before we have enough statistically significant data.
Other tests, like changing a navigation element, may take 12 weeks to get enough data on because of the number of users who use the feature may be far less.
You run experiments until you achieve a statistically significant result with high-predictability of outcome. Sometimes that's done with a gut-check. Sometimes you use statistical modeling tools to tell you if your experiment needs more time.

[@vladislavstashek2063]

What about MRE, alfa, beta? Too superficial to be useful.