On the technical tab within RUMvision, you can really get started analyzing data by adding filter(s). You also get more information from certain metrics and dimensions. Below is an explanation of what you will see within the technical tab.

Adding filters

To spot issues and actionable insights from your RUMvision data, it is useful to start using filters. This way you can see under what circumstances a problem occurs and what causes it.

If I go to add a new filter, for example lazyloading, I get to see different data again. Namely "none" and "lazy", or in other words what are the values when an image is lazyloaded or not.

lazyloading core web vitals

Now if I want to filter further I can start adding more filters, as I want to know on which template this happens. I click on "lazy" and then select "add filter" and add the page template filter.

Now I get to see specifically which templates have a lazyloaded LCP image.

Even now you can dive further into what the specific element is, because not every visitor has the same LCP element. In the screenshot below, you can see which element is the LCP, but also that it is being lazyloaded. From here you can, for example, create a to-do to remove the lazyload class here from the specific element. With more than 30 filters, there are endless opportunities to spot things in your performance data.

Distribution summary

When you have a value of 2500ms or higher at the LCP it means that the average within this bucket is at that value. This does not necessarily mean that everyone has a bad experience under these circumstances. With the distribtion summary you can see what % fall into the good, moderate and poor buckets. It depends on which metric you select what the thresholds are.

In the LCP experience on the right you will see the values of before and after, this depends on which data ranges you have selected. Then the percentage increase or decrease and the current UX score.


Based on which filter and which bucket within a filter you selected you will be shown the values. For example, you can also see the timeline of a specific LCP element. In the screenshot below we see a timeline of the last 14 days with a time interval of 12 hours. Also an annotation is visible, this way you can clearly see what the result is after a certain release.

core web vitals timeline

Aftert the annotation, this particular LCP element remained below the Core Web Vitals thresholds of 2500ms for the LCP except for one data point.

Histogram & percentiles

As with the distribution summary, the histogram chart and percentile chart allow you to see how many of your visitors fall into the green, orange and red buckets. The histogram chart is divided into buckets of x number of milliseconds, which you can customize. When you hover over a bar you see the size of the bucket, the number of pageviews that fall into this bucket and the difference in pageviews compared to the previous period.

Core Web Vitals histogram

On the percentile chart, you can see up to what percentile your visitors stay within the thresholds of the metric. For example, if you are doing well up to the 75th percentile, you may want to look at a higher percentile to give even more visitors a better experience. In the chart you see 2 lines, one from the current period and one from the previous period. You can hover over the line to see the difference in milliseconds.


In the technical tab, you can analyze at a deeper level what's going on on your website and where it's coming from. On the previous dashboards, it gets a little more flattened. The data you see within the technical tab depends on what filter you have active and what element you clicked on.