Design practices and data science work toward the same goal, helping designers and product managers understand users so they can craft elegant digital experiences. In this practical guide, authors Rochelle King, Elizabeth F Churchill, and Caitlin Tan show you how to conduct data-driven A/B testing for making design decisions on everything from small tweaks to large-scale UX concepts.
Complete with real-world examples, this book shows you how to make data-driven design part of your product design workflow.
Author: Rochelle King, Elizabeth F Churchill, and Caitlin Tan
Date: April 2017
Audience: Data developers
Category: Data Science
- Understand the relationship between data, business, and design
- Get a firm grounding in data, data types, and components of A/B testing
- Use an experimentation framework to define opportunities, formulate hypotheses, and test different options
- Create hypotheses that connect to key metrics and business goals
- Design proposed solutions for hypotheses that are most promising
- Interpret the results of an A/B test and determine your next move
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