In the world of business applications, when users are forced to switch from app to app to analyse their data they immediately lose any efficiencies they gained.
Self-service is an IT departments’ favourite phrase, or so it seems at the moment, as the availability rates continue to gain momentum.
However, research shows that there has been a drop in end-user adoption over recent years.
As IT teams continue to force self-service solutions onto their users, the backlash and rejection of these tools has grown.
End users don’t want to adopt these tools because they find them difficult to use, don’t like switching over from their usual applications to separate analytics tools, and don’t have easy access to analytics tools in their daily workflows.
In fact, recent research Logi Analytics conducted on the state of analytics adoption found that 83% of business users expressed a strong desire to stay in one application instead of switching to standalone analytics applications.
Despite this, the report also shows that nearly 67% of business users find themselves having to switch to separate analytics tools to get the data or analytics they need, something that industry analysts have said can waste users one to two hours a week.
Today’s users are desperate for something that is better, easier, and more efficient for them to work into their own daily workflows and app usage patterns.
Companies need to start embracing the value of delivering sophisticated analytics when and where people most need them most.
Embedded analytics puts intelligence inside the applications people use every day to improve the analytics experience and make users more productive by combining insight and action in the same application.
A second survey conducted into State of Embedded Analytics report uncovered that 94% of independent software vendors (ISVs) and 80% of non-commercial application providers said embedded analytics is important to their users.
Application providers stated that 43% of their users use embedded analytics on a regular basis. That’s double the adoption rate of traditional analytics tools, which typically peaks at 20-30%.
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