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Scale Your Research's Impact With Data Viz
Workshop: July 23 @ 12pm Central
All registrants get the recording!
The most effective qualitative research isn't over when a study is complete.
It's analyzed, visualized, and socialized across stakeholders—so the takeaways help guide your org or your customers.
Data visualization is a crucial (and often underutilized) way to ensure your research has the impact it deserves.
In this free remote workshop, we'll take you through how to validate and expand upon your findings—with publicly available tools for data visualization.
From DIY methods to working with data-viz pros, the presentation and worksheet will help you find and highlight the most meaningful findings from your research activities.
Get the Recording:
Meet the speakers
Nick Cawthon
Founder, Gauge.io
Nick leads human-centered strategy and research efforts for enterprise and technology companies seeking to better position their digital efforts.
Mixing his academic background with practical development skills, Nick uses data visualization to drive informed design and evidence-based strategy decisions.
Nick founded a small, boutique agency called Gauge in 2001 to better service corporations, agencies and startups here in the San Francisco Bay Area and beyond; these have grown to include Genentech, Adobe, Wells Fargo and many others.
Nick teaches Data Visualization for the MBA in Design Strategy curriculum at CCA.
Ben Wiedmaier
Research Evangelist, dscout
Ben is the research evangelist at dscout, where he spreads the “good news” of contextual research.
He has a doctorate in communication studies from Arizona State University, studying “nonverbal courtship signals”, a.k.a. flirting. (No, he doesn’t have dating advice for you.)
Curious about the world where design and research meet, Ben transitioned to the user-experience space.
Today, he leverages his doctoral training to create, organize, and deliver content focused on human-centered approaches to design and research.
What's covered
In this remote workshop, Nick:
- Introduces ways to approach and structure open-ended data
- Explores models for mapping, synthesizing, and/or making sense of those data
- Outlines strategies for working with data-centric teams or customers