Wed.Dec 20, 2017

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Recap of 2017 Predictions & Trends for User Experience Design & Research

Userzoom

At the start of 2017 I made several predictions about UX design and research. Let’s see how I did. Happy December! Hopefully you had a great 2017 and (soon) a very happy 2018! It’s been an exciting and productive year for us and I hope it has been for you as well. A quick recap for UserZoom – in early 2017 we redesigned the entire UserZoom product and have consistently improved it throughout the year, and will continue to do the same in 2018.

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How Automattic is sustaining the perception of presence in its distributed team

Miro

How Automattic is sustaining the perception of presence in its distributed team Here at RealtimeBoard, we set out on a mission to build a universal whiteboarding tool that helps companies to embrace digital transformation, manage remote teams and think visually in order to speed up internal processes and delight their customers. That’s why we are […].

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A year in review: productboard’s top 10 posts from 2017

ProductBoard

At productboard we aim to bake best practices of product management straight into the interface, so you can improve the way you manage your products right out of the box. In the meantime, we’ll continue publishing thoughts and ideas we’ve learned from great product managers here. Read on for our top posts from 2017! Still prioritizing features in a spreadsheet?

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Looking Back to Look Forward in 2018

Rahul Abhyankar

The year is winding down. Perhaps you have a crackling fireplace going. Perhaps there is a beautifully decorated tree in the corner with boxes of gifts around it, all waiting to be opened.

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Beyond the Basics of A/B Tests: Innovative Experimentation Tactics You Need to Know as a Data or Product Professional

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

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How do you define and source an audience for user testing?

DISQO

Continually sourcing users is one of the core challenges for product teams that want to rapidly experiment and validate product decisions. To be effective in most enterprise contexts, you’ll need procedures to mitigate bias and a streamlined technology in order to define and source an audience for ongoing testing. For product teams just beginning to make the shift to data-driven practices, it’s common to simply get feedback from family, friends, or patrons of a nearby Starbucks.

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How do you define and source an audience for user testing?

DISQO

Continually sourcing users is one of the core challenges for product teams that want to rapidly experiment and validate product decisions. To be effective in most enterprise contexts, you’ll need procedures to mitigate bias and a streamlined technology in order to define and source an audience for ongoing testing. For product teams just beginning to make the shift to data-driven practices, it’s common to simply get feedback from family, friends, or patrons of a nearby Starbucks.

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A year in review: productboard’s top 10 posts from 2017

ProductBoard

At productboard we aim to bake best practices of product management straight into the interface, so you can improve the way you manage your products right out of the box. In the meantime, we’ll continue publishing thoughts and ideas we’ve learned from great product managers here. Read on for our top posts from 2017! ?? Still prioritizing features in a spreadsheet?

article thumbnail

How do you define and source an audience for user testing?

DISQO

Continually sourcing users is one of the core challenges for product teams that want to rapidly experiment and validate product decisions. To be effective in most enterprise contexts, you’ll need procedures to mitigate bias and a streamlined technology in order to define and source an audience for ongoing testing. For product teams just beginning to make the shift to data-driven practices, it’s common to simply get feedback from family, friends, or patrons of a nearby Starbucks.