Understanding s.t() and s.tl() Server Calls

When analyzing user interactions on a webpage, two common types of server calls in Adobe Analytics are s.t() and s.tl(). Both play a role in collecting data, but they affect metrics like bounce rate differently:

• s.t() (Page View Tracking): Triggered during a page load to track the initial server call for a page view.

• s.tl() (Link Tracking): Triggered during interactions such as banner clicks, image impressions, or other non-page load events.

Since s.tl() counts as an interaction, it artificially reduces bounce rate by indicating user engagement even when no subsequent page view occurs.

Key Considerations

To better understand and work with bounce and bounce rate metrics, refer to Adobe’s documentation.

• You can use calculated metrics to create more tailored reports based on single access or single-page visits.

• Choose the metric based on your reporting requirements—whether page-specific or site-wide analysis.

Solutions for Adjusting Bounce Metrics

Solution 1: Use Alternative Metrics

You can mitigate the bounce rate distortion by building calculated metrics based on single access or single-page visits:

• For Specific Dimensions (e.g., Pages, eVars): Use the formula:
  Single Page Visits / Entries

  Example visualization:
  

  

• For Site-Wide Analysis: Use the formula:
  Single Access / Visits

  Example visualization:
  

  

Choose the formula based on your reporting needs and the granularity of your data.

Solution 2: Track Banner Ads More Accurately

To avoid bounce rate inflation caused by s.tl() for banner impressions, implement the following approach:

1. Track Banner Loads via JavaScript Variables:
   Store banner data in a local JavaScript variable during page load, e.g.:

   var bannerData = "banner1:banner2:banner3";
   

2. Pass Banner Data to Analytics Variables:
   Populate this value into an analytics variable (e.g., prop or eVar) during the s.t() server call triggered by page load.

This method provides insights into how many banners were loaded without triggering s.tl(), thus maintaining the integrity of bounce rate calculations.

Final Note

The choice of metrics and tracking approach depends on your reporting requirements and how you want to interpret user interactions. Carefully consider which solution best aligns with your goals. If you have questions or need help implementing these solutions, leave a comment below!