The TAGGRS analytics dashboard gives you full control over how you slice and analyze your data stream.
You can filter all graphs by:
For time granularity, you can use preset ranges like Last 7 days, or Last 90 days, define a fully custom date range for aggregated daily data, or switch to Last 24 hours to view data hour-by-hour.
The Adblock impacted events metric shows the percentage of events that would have been blocked by ad blockers without Server-side Tracking in place. Because TAGGRS routes data through your own subdomain on the server side, these requests bypass browser-based ad blocking entirely.
The higher the percentage, the greater share of your conversion and analytics data is being recovered through the TAGGRS Enhanced Tracking Script: data that would otherwise be silently lost on a purely client-side implementation.
This is also reflected in the Improved data quality graph:
The Consent rate KPI shows the percentage of users who have fully granted consent, giving you an at-a-glance health check on your consent configuration.
The Consent Approvals graph goes deeper, breaking down the distribution of all consent states over time, from Granted to Denied by Default and Not Set.
Below the graph, a breakdown table shows (for each consent type) the total number of consented events and the approval rate:
The Request distribution graph in your Analytics provides an overview of the requests made to a website. The calculated number of requests comes directly from activity on your website, including pageviews and data client deployments via Google Tag Manager (such as gtm.js, analytics.js, and gtag.js).
By switching the Show categories toggle in the Requests graph, you can view detailed types of requests and their sources.
The following types of requests are
distinguished:
In the Browser Analytics graph, you get insights into how browser tracking prevention mechanisms impact data collection accuracy, drawing from real-time analysis of website traffic patterns. This is measured by the percentage of users on browsers with built-in tracking prevention—features like those in Intelligent Tracking Prevention.
Select your preferred time range (90, 60, 30, or 7 days, last 24 hours, or custom) to view statistics on traffic affected by tracking prevention across all major browsers except Google Chrome, which lacks such mechanisms. So, the percentage reflects total visitors minus Chrome users. A higher percentage indicates greater data loss from untracked user activity, impacting analytics accuracy and digital marketing effectiveness.
Want to know how much extra data you gain from Server-side Tracking? The Signal Comparison graph shows the differences between client-side (web container) and server-side (server container) data, depending on consent.
TAGGRS now uses incoming server container data directly as the source for uplift measurement, replacing the previous model that relied on client-side tag configuration. This results in a more accurate and stable representation of actual server-side signals: completely unaffected by consent configuration issues, incorrect event handling, or misfiring client-side tags.
The number of server-side requests in TAGGRS is automatically calculated and shown in your account overview. It mainly depends on the number of clients you use (e.g. GA4, Universal Analytics), your website or app traffic (pageviews), and the number of additional events you track (such as e-commerce events). Want a detailed breakdown? See our page on Server Side Tracking costs.
TAGGRS uplift measurement is now based directly on incoming server container data, rather than relying on your client-side TAGGRS tracking tag configuration. This makes it significantly more reliable: your uplift figures will no longer be affected by consent issues, incorrect event handling, or client-side tag misconfigurations. The client-side tag is still needed for client-side comparison data in the Signal Comparison graph.
