The need to understand people lies at the core of any product design, and currently there are two standard ways to measure that understanding: big datasets and small research studies—aka "thick data." Most organizations favor big over thick, but in doing so they miss the larger picture. In this report, author Pamela Pavliscak outlines a way to use data of all kinds to understand the relationship between people and technology.
Big data shows traces of interactions that people leave behind, but it doesn't reveal the whole story. By adding user stories, you can go beyond the "what" to discover why people behave as they do. Up until now, there hasn’t been much information on how to combine quantitative big data with qualitative thick data. That's where this report can help.
- What to consider when using data to understand people
- Key differences between big data and small research studies
- Why organizations should combine big and thick data to understand human behavior, emotion, and language
- Which data sources or research methods work best in combination
- How to categorize and combine data effectively in metrics
- Methods for infusing design documents with data
- How to work across teams to understand customers
This report is ideal for product designers and developers, data scientists, design researchers, and business strategists.
Table of contents
- 1. Does Design Need Data?
- 2. Designing with All of the Data
- 3. Data and Innovation
- 4. Data to Improve Product Design
- 5. Using Data to Measure
6. A Hybrid Approach
- Step 1: Frame the Question
- Step 2: Start with Data on Hand
- Step 3: Add Social Listening
- Step 4: Consider a Deep-Dive Study
- Step 5: A/B Test Alternatives
- Step 6: Track It
- Step 7: Conclude with More Questions
- 7. The Future of Data and Design
- Title: Data-Informed Product Design
- Release date: June 2015
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781491931288
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