Data-Driven Product Research and Design
2h 20mGeneral2024-01-11
Authors
Shanae Chapman
Course details
Data-driven research and design are vital to modern product teams, but how do you find out which processes and tools will work best for your team? In this course, tech expert Shanae Chapman guides you through the tools and workflows for creating a data-driven product roadmap. Learn how to identify and collect challenges and questions for research efforts. Find out how to plan, recruit for, and schedule research sessions using common tools. Explore inclusive recruiting and interviewing processes and best practices. Go over design discovery using shared tools, as well as ways you can collect, collate, and present data findings to your team and stakeholders. Plus, discover tools that can help you manage the process of design research across your team.
Skills covered
Google DocsFigmaDecision-MakingBusiness AnalyticsProduct and Industrial DesignGoogleProjectProduct and ManufacturingData ScienceProfessional DevelopmentLeadership and Management
Concepts
0. Introduction
- 01 - Integrate data into product research and design
1. Planning Your Roadmap
- 02 - Identifying questions for research and design
- 03 - Gathering priorities from stakeholders
- 04 - Identify barriers to usability, accessibility, and inclusion
- 05 - Visualizing your roadmap
2. Product Analytics Discovery
- 06 - Integrating data analytics discovery to learn user behavior
- 07 - Using Heap for product analytics discovery
- 08 - Using Pendo for product analytics discovery
3. Customer Discovery
- 09 - Selecting the right research method
- 10 - Inclusive participant criteria and recruiting
- 11 - Survey design basics
- 12 - Interview basics
- 13 - Incentives and scheduling
4. Design Discovery
- 14 - FigJam brainwriting
- 15 - FigJam for journey mapping
- 16 - FigJam for design studio
- 17 - FigJam for card sorting
- 18 - Creating wireframes in Figma
- 19 - Inclusive design practices
5. Generative and Evaluative Testing
- 20 - Generative testing
- 21 - Evaluative testing
6. Reporting and Communication
- 22 - Synthesizing data
- 23 - Knowledge sharing
Conclusion
- 24 - Taking data, research, and design further