How to Coach Enterprise Experimentation
Summary
In this talk, Alyssa Briggs shares her experience coaching enterprise experimentation, emphasizing that experimentation is a mindset for problem-solving by validating assumptions through small, fast tests. She highlights that executives often support experimentation in theory but struggle to embed it into daily work. Using Intuit as a case study, Briggs illustrates how simply training and embedding experiment coaches within teams transformed the company’s culture, enabling tens of thousands of experiments annually that generate millions in revenue. She describes three essential practices for experiment coaches: collaboratively planning experiments using an experiment grid, helping teams embrace and learn from failures by facing data honestly and conducting quick customer research, and catalyzing organizational change by spreading the coaching role and uncovering new opportunities for experimentation beyond product design. Briggs walks the audience through a live experiment about a name memory trick to demonstrate how to develop hypotheses and validate assumptions quickly. She also recounts a story where a small sales experiment disproved executives’ skepticism about a new product tier, leading to significant business impact and wider cultural adoption of experimentation. Briggs encourages everyone to adopt the experiment coaching mindset and start running small experiments to shift team behaviors and company culture.
Key Insights
-
•
Embedding experiment coaches within existing teams is key to sustaining a culture of experimentation.
-
•
Experimentation thrives on embracing small failures to avoid costly large ones.
-
•
Executives often support experimentation top-down, but real change happens when coaches integrate experiments into daily workflows.
-
•
The experiment grid is a powerful yet simple tool for collaboratively planning experiments by unpacking assumptions and defining testable hypotheses.
-
•
Most teams fail their first experiment, and coaches must help them face the data and learn rather than become discouraged.
-
•
Quick, informal customer research after an experiment helps uncover root causes and increases team engagement.
-
•
Consistently planning follow-up experiments builds momentum and prevents the 'one-and-done' pitfall.
-
•
Experiment coaching is not a full-time role but can be integrated as 10-20% of a team member’s responsibilities.
-
•
Experiments can test not just products but internal processes and business assumptions, unlocking broader innovation.
-
•
Demonstrating successful experiments with quantitative data can transform executive skepticism into enthusiastic support, driving significant business impact.
Notable Quotes
"If you’re afraid of failure, that’s okay. With experimentation, you’re going to fail—but in little tiny ways that don’t really matter."
"Executives get experimentation but often it doesn’t stick when people go back to their normal teams."
"The simple thing that worked at Intuit was training and embedding experiment coaches in teams."
"An experiment coach spends about 10 to 20 percent of their time helping the team change mindsets and actions."
"The most important tool is not for running experiments, but for planning them—the experiment grid."
"If we do X, then Y percent of people will do Z—that’s how you frame hypotheses to learn from both success and failure."
"It’s better to run lots of quick, cheap experiments to remove doubt than to wait for the perfect, statistically significant test."
"Nine out of ten teams fail their first experiment, which is normal but can be demoralizing."
"Helping your team face the data honestly and then diving into customer conversations helps uncover what went wrong."
"You know you’ve succeeded as a coach when you put yourself out of a job by giving away the role."
Or choose a question:
More Videos
"Change is the only constant, so designing insight sharing with self-directed learning is critical."
Jerome “Axle” BrownHow to Use Self-Directed Learning to Ensure Your Research Insights are Heard and Acted Upon
March 11, 2021
"We’re showing people how to collaborate like crazy and how to fail gracefully."
Phil GilbertA Consistent Culture of Design
May 14, 2015
"Participants themselves need to be real humans at the end of the day to get unique insights."
Kate Towsey Basel Fakhoury Oren Friedman Graham GardnerParticipant Recruitment and Management Tools
March 12, 2026
"Human behavior is complex and machine learning models need to understand those nuances."
Sohit KarolDesigning Delightful Listening Experiences: Mixed Methods Research in the Age of Machine Learning
March 31, 2020
"Psychological safety comes from having hard conversations upfront and requires demonstration from leadership."
Christopher Taylor Edwards Valerie RoskeDesign as a Team Practice, A Practical Guide to Cross-functional Collaboration
September 30, 2021
"Systems thinking requires constant engagement with stakeholders; working in isolation will not lead to successful outcomes."
Sheryl CababaExpanding Your Design Lens with Systems Thinking
February 23, 2023
"You need to come up with your own definition of design maturity based on your team’s understanding and context."
Francesca Barrientos, PhDYou Need Your Own Definition of Design Maturity
June 8, 2022
"I’ve onboarded 80% of the design and CX department, and it really shapes their trajectory and connection to culture."
Allison SandersOperating with Purpose
January 8, 2024
"We had to make everybody feel safe to participate in this exercise."
Saara Kamppari-Miller"Prototype" vs "Prototype"--Breaking Down and Rebuilding Our Understanding of What We Do
October 24, 2019
Latest Books All books
Dig deeper with the Rosenbot
What does a successful healthcare UX career look like in terms of accumulating influence and aligning with clinical/business goals?
What features does Rosenbot offer to help UX learners deepen their knowledge through follow-up prompts?
How can play help overcome the ‘messy middle’ between research insights and decision-making in organizations?