Live training: Establishing Optimizely as the Source of Truth for Experimentation Results (EXP)

Instructor: Mike Chu, Staff Software Engineer, Experimentation
Audience: Developers, Data/Analytics Engineers, and Technical Program Managers involved in experiment analysis or reporting

Explore how Optimizely measures experimentation results and how its methodology compares to general-purpose analytics tools. This session covers common sources of data discrepancies with tools like GA4 and practical validation techniques including A/A tests. Walk away with frameworks for strengthening your team's data-driven decision-making and communicating results clearly to leadership.

Agenda:

• Understanding Data Discrepancies (how Optimizely and GA4 measure differently — and what each is optimized for)
• Aligning Tracking & Attribution (conversion counting, attribution windows, session vs. visitor models)
• Validating with A/A Tests (how to run them, what to expect, how to interpret)
• Communicating Experiment Results to Leadership (frameworks for clear, confident reporting)
• Q&A