Introduction
Speed Analysis RUM provides visibility on the web performance of websites. Web Vitals metrics are captured by the Contentsquare tag: Largest Contentful Paint, Cumulative Layout Shift, Time to First Byte, First Contentful Paint, First Input Delay, and Interaction to Next Paint.
Monitor with greater detail, the load time experienced by users and leverage it in conjunction with all other Contentsquare behavioral metrics.
It’s a complementary solution to Speed Analysis Lab
What is Real User Monitoring
RUM (Real User monitoring) is a way to measure website performance by collecting performance data directly from the real audience using a Javascript tag.
RUM captures real-life user experience and enables correlation to business KPIs where as synthetic monitoring is an active approach to testing a website in which user actions are emulated in a ‘lab’ environment.
Key Use Cases
Speed Analysis RUM consists of adding new metrics to be used within Contentsquare’s different modules.
Analyze sessions based on Web Vitals In Journey Analysis
See the journeys of users affected by poor web vitals on a specific page and compare with users who have experienced good timings to analyze the behavioral differences.
- Identify the patterns causing slower sessions
- Analyze differences of behaviors related to slowdowns (eg: bounce rate, etc)
Monitor Web Vitals in Dashboards
Track Web Vitals at the site or page level, for all users or specific segments.
Monitor the amount of traffic with Poor, Need Improvement and Good Web Vitals metrics performance to see the behaviors over time.
Visualize web performance with greater granularity, across browsers and against business metrics.
Compare Web Vitals of different segments In Page comparator
Visualize the LCP performance of page groups to identify slower page groups or to compare the performance between two segments. For example: New versus returning visitors, before and after releases.
- Identify which pages to optimize and prioritize first.
- See performance gaps between two scenarios in correlation with metrics such as bounce, exit rate, etc.
Why use RUM and Synthetic monitoring together
Leveraging RUM and Synthetic monitoring together enables a more comprehensive and precise monitoring.
RUM is the perfect way to see the behavioral differences due to slowdowns or performance improvements. It allows the discovery of unexpected performance bottlenecks.
Synthetic is a fully configurable and stable over time environment, perfect for monitoring and establishing a baseline.
Example of a synthetic analysis leading to a RUM analysis
| Synthetic | RUM | |
| I see a drop in my cart page LCP in my synthetic report and I want to understand how heavily it relates to behavioral differences. |
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I visualize journey differences between users having “poor” and “good” LCP. I check LCP in Page comparator and compare different segments to spot potential important differences. |
Example of a RUM analysis leading to a Synthetic analysis
| RUM | Synthetic | |
| The percentage of people with a Good FID on my product page is dropping severely. I want to understand and isolate the context of this drop to fix it (What script or service might cause this?) |
> |
I’ll trigger a synthetic monitoring to: - better understand the issue using the waterfall and dependency map. - monitor the occurrence over time and verify that the fix resolves the issue and does not return. |