Notion launched a 4-month engineering project to improve workspace load performance and reliability for large enterprise customers. The project included backend query optimization, caching changes, and frontend bundle reduction. Leadership now wants a clear metric framework to decide whether the project was successful beyond simply shipping on time.
Before launch, median workspace load time was 3.8s, p95 load time was 9.4s, crash-free sessions were 98.7%, weekly active teams were 42,000, and enterprise account renewal rate was 91%. Six weeks after rollout to 100% of traffic, median load time improved to 2.6s, p95 load time to 6.1s, crash-free sessions to 99.3%, weekly active teams increased to 43,200, support tickets about slowness fell from 1,150/month to 620/month, and renewal rate has not yet materially changed.
The VP of Engineering asks you to define the right success metrics for this project, separate leading from lagging indicators, and explain how you would attribute business impact versus technical improvement.
page_load_events: request_id, workspace_id, user_id, timestamp, load_time_ms, page_type, device_type, browsersession_quality: session_id, user_id, workspace_id, crash_flag, api_error_count, timestampworkspace_activity_daily: workspace_id, date, active_users, documents_opened, edits_completedsupport_tickets: ticket_id, workspace_id, created_at, issue_category, severityaccount_health: account_id, workspace_id, plan_type, renewal_date, renewal_status, arrYou are practicing as a guest. Sign up free to get your answer graded with AI feedback. Your draft stays right here.
