Automating Recording Management for Scale
Timeline
2 months
Team
Product Managers (1)
Product Designer (1)
Developers (2)
QA (1)
My Role
Product Designer
Product Manager
Overview
Some problems don’t make a lot of noise—but they bleed time, cost, and efficiency every single day. Our Zoom recording system was one of them. What seemed like a minor operational gap was, in reality, a silent killer—overloading support teams, creating constant dependency on backend tech, and forcing creators to wait days for simple tasks. Our processes were duct-taped together—functional, but nowhere near scalable.
We knew this couldn’t last. So we decided to cut the problem at its root and build a self-serve, logic-driven system that empowered creators and freed up our teams.
This is how we dismantled a legacy workflow and replaced it with a solution designed for scale, autonomy, and long-term efficiency.
The Bottleneck: Recording Management Wasn't Scalable
As more creators started hosting live sessions on Exly, a new challenge emerged—recording management was a tedious, manual process that slowed down operations and frustrated both creators and customers.
Recordings sharing so far and what it meant for the user?
🚨 What was happening?
Recording assignments were manual – Our system didn’t automatically map Zoom recordings to sessions, requiring manual intervention.
Delays in content access – Customers had to wait days for recordings to be assigned.
Heavy support dependency – Support teams were overwhelmed with manual recording assignment requests.
We knew that to scale, we needed to give creators full control over their content.
Breaking Down the Problem
Key challenges identified:
The Solution: A Fully Automated Recording System
Automating Recording Assignment Rules
We introduced rule-based automation, allowing creators to either:
- Auto-assign recordings to all customers
- Restrict access to only session attendees (if needed)
- Set manual overrides for exceptions (if needed)
Self-Serve Recording Management
Launched an Unmapped Recordings Section, where creators could manually map recordings if automation failed.
Introduced real-time notifications for unmapped recordings, reducing uncertainty.
Within just two weeks, we were able to bring user frustrations to a hault and adoption of the new automation soon became the new normal. Key to quick adoption and transition proved directly proportional to identifying and solving the right problems.
Impact & Results
Key Takeaways
✅ Automation = Scalability – Removing manual dependencies is essential for growth.
✅ Self-serve tools empower users – Giving creators direct control improves satisfaction and reduces support overhead.
Final Thoughts
This project helped me build an understanding of how removing friction, automating workflows, and empowering users can lead to a more scalable, efficient, and creator-friendly recording system.
Thanks for reading!