The business case for reducing context switching is strong.

Forrester estimates that organizations with 5,000 information workers can save more than $3.1 million per year by reducing app switching by just 15 minutes per employee per day.

The cost of ignoring the problem goes beyond lost productivity; poor technology drives attrition.

In a Laserfiche survey, 20% of Gen Z workers quit their jobs because of “useless” technology, and 49% said they would consider leaving due to outdated tools.

Contextual, in‑workflow analytics help reclaim time and improve employee satisfaction by reducing friction and making data actionable at the point of decision.

They can also lower support costs: as embedded analytics become more intuitive, developers report a 20% reduction in reporting‑related support tickets.

Bigtincan, an enterprise software vendor, achieved a 215% ROI and a 6.2‑month payback period after embedding analytics directly into its product, while reducing support escalations by 90% and freeing two engineers.

By eliminating context switching and surfacing insights in‑workflow, organizations not only save money but also accelerate decision‑making and increase user engagement.

MageMetrics customers reduce support burdens and churn while realising rapid payback from contextual insights and query logging.