Behavioral dataset provides an evidence-based view of how work compares
ActivTrak today launched the Productivity Lab Benchmarking Assessment, a new service that helps organizations understand how their work patterns compare to peers. The program draws on the largest behavioral dataset on work activity captured across millions of users and billions of interactions — reflecting how work actually happens rather than how it is reported.
The problem it solves
Organizations have more workforce data than ever, but lack the context to prioritize what matters most. Internal metrics such as productivity, utilization, focus time and tool usage are difficult to evaluate without a credible external reference point. The challenge compounds as AI adoption introduces new variables, leaving organizations with more data but less clarity on whether investments deliver results. As a result, leaders struggle to determine if performance gaps reflect execution issues or normal operating conditions.
How it works
The Productivity Lab Benchmarking Assessment uses the largest continuously observed behavioral dataset on work activity, segmented by industry, role and function to provide a comparative baseline grounded in actual work patterns. Organizations typically engage after establishing a behavioral data baseline, generally three or more months post-deployment, or during initiatives such as:
- AI transformation and workflow modernization
- Business acquisition, consolidation or reorganization
- Cost optimization and efficiency programs
- Hybrid or distributed work model shifts
- Technology rationalization or tool consolidation
Metrics are benchmarked against peer cohorts aligned to an organization’s industry and operating model, with side-by-side comparisons that include medians, ranges and percentile distributions to contextualize results.
What organizations receive
The assessment identifies where an organization falls above, below or within expected norms, and includes expert interpretation connecting performance patterns to operational drivers, along with targeted guidance on where to focus.
For example, top-performing Account Executive teams spend 70% of their time on core selling activities like customer meetings and deal progression, nearly double the 38% average, giving leaders a clear model to replicate.
“We’ve built a dataset that shows how work actually happens at scale,” said Gabriela Mauch, Chief Customer Officer at ActivTrak. “This brings that data into a form customers can use, so they can understand where they stand relative to peers and take action based on that insight.”
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