The value of Lightning Usage data comes from acting on it. The workflow below covers the standard sequence for using the data to drive specific admin actions that improve the org's user experience and adoption.
- Review the metrics monthly
From Setup, search for Lightning Usage and open the page. Review the headline metrics: DAU, MAU, EPT trends, most-visited pages, browser distribution. Compare to the prior month and prior quarter. Note any significant changes: a drop in DAU, a spike in EPT for a specific page, a shift in browser distribution. Capture the observations in the team's running operational log.
- Investigate the anomalies
For each significant change, investigate the root cause. A drop in DAU may correlate with a recent release that introduced friction; check user feedback channels for specific complaints. A spike in EPT may correlate with a new custom component added to a record page; review the component's performance. A shift in browser distribution may correlate with an IT-driven browser policy change. Each investigation produces a specific corrective action or an explicit decision to accept the change.
- Drive corrective actions
Translate the investigations into specific actions: optimize slow pages by reducing component count or refactoring Apex, train low-engagement user groups, redesign underused dashboards. Each action gets an owner and a target date. Track the actions in the team's standard work tracking system (Jira, Asana, or whatever the team uses). Report progress in the monthly Lightning Usage review.
- Build long-term trend visibility
For deeper analysis, export Lightning Usage data into CRM Analytics or a data warehouse for long-term trend tracking. Build dashboards that show engagement by user, team, geography, and feature over multiple quarters. The trend data informs strategic decisions about platform investment: which features are growing in usage and deserve more investment, which are declining and may be candidates for retirement. The trend perspective sometimes reveals patterns that monthly snapshots miss.
- Lightning Usage shows aggregate data; per-user investigation requires CRM Analytics or custom reporting against event logs.
- EPT measurement varies by browser and device. Compare like-for-like (same browser, same page type) for valid trend analysis.
- Mobile usage is tracked separately. Including or excluding it shifts the percentage views significantly.
- The page does not surface field-level engagement. Knowing which fields users actually populate requires deeper analytics.
- Historical data retention is limited. For long-term trends, export to a separate analytics platform.