Quantitative Research for Qualitative UX Researchers: Triangulate Your Way to Holistic Insights and Stronger Storytelling

1-day in-person workshop
March 27 2024, 9:00am-5:00pm ET

Many UX researchers often rely on familiar qualitative methods such as interviews and usability testing, overlooking the potential benefits of combining these with quantitative methods through triangulation. Depending solely on one set of tools can result in blind spots, limiting researchers’ ability to provide comprehensive insights. This workshop aims to address these challenges by offering insights into:

  1. When and how to apply quant methods for generative and evaluative research.
  2. How to supplement qual with quant and triangulate different data sources and methodologies to build a holistic story.
  3. The power of collaboration between researchers and data scientists, and how it can help drive a more data-driven culture across the organization.

Target Audience
Qualitatively-focused UX researchers

Take-aways

  • Know when to use quant or mixed methods for a business problem
  • Use quant data to supplement qual findings and tell a stronger story
  • Converse easily with data science teams and drive conversations for clearer, deeper and more impactful insights

Agenda

Introduction and discovery (20 minutes)
  • Activity: set up canvas – icebreaker to get to know one another + goal for the day
  • Speakers and our stories
  • Agenda for the day
  • Participant introductions
  • Activity: Landscape of methods – mapping familiar territory and unknown terrain.
  • Discussion: Challenges of triangulation and applying quantitative methods in UX Research.
Orientation to the qual-quant collaboration framework (30 minutes)
  • Framework Overview: Leveraging qual and quant insights for informed product decisions.
  • Identifying when quantitative methods are applicable.
  • Utilizing data sources, collaborating with cross-functional teams, and aligning on common goals.
  • The power of collaboration: effective communication with product analysts and data science colleagues to scope research and synthesize insights.
  • Cultivating a data-driven culture.
Break (10 minutes)
Generative research – methods to define the problem well (30 minutes)
  • Using quant data to scope qual research – drawing boundaries around the problem from cross-functional data (20 mins)
    • Types of data and insights that can be derived (customer feedback, market research and behavioral analytics) to map knowns and unknowns
    • Collaboratively writing blue sky research questions or hypotheses
  • Group discussion and Q&A (10 mins): what types of data are available to you?
Study design and synthesis (60 mins)
  • Overview of how to mix qual and quant methods for discovery (with group discussions on examples)
    • Activity: Design a mixed methods research approach for a business problem
    • Resource sharing on how-tos and tooling for quant analyses in generative research
Evaluative research – methods to confidently recommend solutions (40 minutes)
  • Overview of how to mix quant and qual methods (30 mins)
    • Activity: Design a research approach for a business problem. What data would you look for?
    • Group discussion and Q&A
Lunch break (45 minutes)
Study design and synthesis (45 mins)
  • Synthesizing insights from qual and quant data
  • Activity: Infer insights from qualitative and quantitative data for a business scenario
  • Resource sharing on how-tos and tooling for quant analyses in evaluative research (5 mins)
Working with data science (60 minutes)
  • Strengthening insights: collaborating with data science partners for deeper understanding.
  • Effective terminology, communication, and goal alignment.
  • Group discussion: questions to ask data science partners in your organization.
  • Enhancing data science methods with qualitative insights.
  • Resolving discrepancies between qual and quant Data.
Break (10 minutes)
Compelling Data-Driven Storytelling (40 mins)
  • Practical tips for combining qual and quant data to tell impactful stories.
  • Addressing sensitive and challenging results.
  • Identifying triangulation blind spots: limitations, biases, and implications.
  • Activity: Discussing blind spots and limitations from earlier exercises.
Group discussion (30 minutes)
  • Open discussion on topics covered and not covered as yet:
    • Exploring Common Business Problems Presented to Researchers.
    • Current Challenges in Applying Quantitative Methods.
Closing (5 minutes)
  • Feedback Collection.
  • Resource Sharing.
  • Thank You and Conclusion.