Lightning Usage
Lightning Usage is a Salesforce Setup page that surfaces detailed analytics about how users interact with Lightning Experience, providing metrics on daily and monthly active users, page load performance, most-visited pages, browser distribution, and Salesforce Mobile usage.
Definition
Lightning Usage is a Salesforce Setup page that surfaces detailed analytics about how users interact with Lightning Experience, providing metrics on daily and monthly active users, page load performance, most-visited pages, browser distribution, and Salesforce Mobile usage. The page is part of the broader Adoption Assistant suite and is the canonical data source for understanding how users actually consume the platform versus how admins assume they do.
The data on Lightning Usage matters because admin-built customizations only deliver value when users actually engage with them. A meticulously crafted dashboard that nobody opens is wasted effort; a flow that no rep uses provides no business outcome. Lightning Usage exposes the engagement reality so admins can iterate based on actual user behavior rather than assumptions. The page also surfaces performance metrics that drive technical optimization: slow-loading record pages, browsers with degraded performance, mobile usage patterns. Combined, the engagement and performance data shapes a productive admin practice focused on what actually moves the needle for users.
What Lightning Usage tells you
Daily and monthly active user metrics
The headline metric on Lightning Usage is active user count: how many distinct users logged in and used Lightning Experience over various time windows. Daily Active Users (DAU) over the past 30 days shows the trend; Monthly Active Users (MAU) shows the broader engagement. The DAU/MAU ratio is a leading indicator of engagement health: a high ratio means most users come back daily, a low ratio means many users log in only occasionally. Adoption Assistant tracks these metrics over time and can flag concerning trends: a steady decline in DAU often signals user dissatisfaction, a sudden drop signals a specific problem (a release introduced friction, a key feature broke). The metrics are aggregated from the platform's standard event logging, so they are reliable and consistent.
Page load performance and EPT
Experience Page Time (EPT) is the standard Salesforce performance metric: the time from clicking a link to the page being fully interactive. Lightning Usage shows EPT distribution across the most-visited pages, with averages, percentiles (P50, P95), and trends over time. Pages with elevated EPT degrade user experience and drive reps away from the Salesforce UI toward shortcuts and workarounds. The EPT data identifies which pages need optimization: too many components on the page, expensive Apex methods running in the page lifecycle, slow Lightning Component initialization. For service consoles and high-volume sales pages, EPT optimization is one of the highest-leverage investments admins can make.
Most-visited pages and feature usage
Lightning Usage ranks the most-visited pages in the org over a chosen time window: which record pages get the most traffic, which list views, which apps. The data tells admins where users actually spend their time, which often differs from where leadership thinks they should. If the Opportunities list view dominates traffic but a custom Pipeline Dashboard is barely used, the dashboard may need redesign or the team may need training. Tracking the most-visited pages monthly catches shifts in usage patterns as new features roll out or business priorities change. Pairing the usage data with field-level engagement metrics (which fields users actually populate on each record) gives a deeper picture of how the platform is consumed.
Browser and device distribution
Lightning Usage reports the browsers and devices users access Lightning from: Chrome, Edge, Safari, Firefox, plus Salesforce Mobile. The distribution matters because Lightning Experience has different supported feature sets and performance profiles per browser. Customers heavy on older browsers (Internet Explorer 11, deprecated long ago but occasionally lingering) face support limitations. Customers heavy on Salesforce Mobile need to optimize record pages for mobile-specific layouts. The browser data informs the org's browser support policy and any browser-specific testing investment. Most orgs find Chrome dominant; outliers usually indicate specific business-unit or regional patterns worth understanding.
Mobile usage patterns
Lightning Usage tracks Salesforce Mobile usage separately: how many users access the org through the mobile app, what their session patterns look like, which features they use. For field-facing teams (field service, outside sales, executives traveling), mobile usage is the primary engagement surface. The mobile metrics drive specific design considerations: which fields fit on the small mobile layout, which actions are most important to expose on mobile, which dashboards work well in the smaller form factor. Without monitoring mobile usage, admins easily underinvest in mobile optimization because their own primary usage is desktop.
Comparison with Classic Usage (for migrating orgs)
For orgs in the middle of migrating from Salesforce Classic to Lightning Experience, Lightning Usage shows the migration progress: percentage of users on Lightning versus Classic, which user groups have moved and which have not. The comparison data drives the migration roadmap: target the lagging user groups with training, identify which Classic-specific features are blocking migration, prioritize Lightning improvements that would attract Classic holdouts. Most orgs have completed this migration by now, but Salesforce continues to track the data for the ones still in transition.
Action and process metrics
Beyond raw page views, Lightning Usage tracks actions: how often users create records, edit them, run reports, view dashboards, use Quick Actions. The action metrics provide a richer engagement picture than page views alone. A user who opens many record pages but never edits or creates may be a passive consumer rather than an active contributor. Comparing action volumes by user, team, and time window reveals engagement patterns that page views miss. Mature analytics programs build CRM Analytics dashboards layered on the Lightning Usage data to provide more sophisticated views than the standard Setup page offers.
Linking Lightning Usage data to business outcomes
The deepest value of Lightning Usage data comes from connecting it to business outcomes. A drop in sales rep engagement on the Opportunity record page correlates with a decline in pipeline accuracy three weeks later. An increase in Knowledge article views on the case timeline correlates with reduced average handle time and higher first-call resolution. These connections are not always immediately obvious in the raw usage data; they emerge from combining Lightning Usage metrics with the org's broader operational KPIs in a unified analytics view. Programs that have made this connection use it to justify investment in Salesforce improvements: every percentage point of EPT improvement on the highest-traffic page produces a measurable productivity gain. Programs that have not made the connection treat Lightning Usage as administrative trivia and miss the strategic value. The investment required to build the connection is modest: a CRM Analytics dashboard layering Lightning Usage data on top of pipeline, case, and revenue metrics. The return is significant: clear evidence for the platform investments that actually move business outcomes, versus the ones that just produce activity. Senior admins who can demonstrate this connection earn credibility with business stakeholders that purely technical admins typically do not.
Use Lightning Usage to drive adoption decisions
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.
Trust & references
Straight from the source - Salesforce's reference material on Lightning Usage.
- Lightning UsageSalesforce Help
- Lightning ExperienceSalesforce Help
About the Author
Dipojjal Chakrabarti is a B2C Solution Architect with 29 Salesforce certifications and over 13 years in the Salesforce ecosystem. He runs salesforcedictionary.com to help admins, developers, architects, and cert/interview candidates sharpen their fundamentals. More about Dipojjal.
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