Business Information (BI) means actionable, detailed data in a form management can use.
CEIP can give you generic data like - you had 500 application runs out of 1000 downloads as an example, but compare that to getting much greater detail such as 1000 unique users, in specific regions of the world, and out of the 500 who ran the software 100 used a feature 5 times while 400 didn’t use that feature at all but they used another feature 10 times.
Or the 1000 downloads was broken into 3 different products, in different regions and operating system versions, and then of those users, 100 ran certain features and options within a specific timeframe whereas the others did nothing.
These simple examples show you generic data can be inconclusive and unhelpful whereas the other scenarios contain actionable, clearly defined, business intelligence of real value to the management team.
In a real example, an ISV released a new product with Software Analytics enabled for the first time and found that the new “social” features they had spent many months engineering were not being used at all despite all the user surveys, salespeople and the industry saying they were “must haves” to compete.
Sound familiar?
The good thing is now they know…whereas before they were in the dark but what does this mean?
Did they just waste all that development, sales, marketing and management investment?
Did they under-promote the new features?
Or would it have been better to get real-feedback from the application usage itself beforehand to drive a strategy based on hard facts from their beta community or a simple low-cost pilot project?
Users often “say” they need new features but when it comes time to pay for them they don’t upgrade either, that’s hard to judge without testing and finding out the usage and engagement in advance.
Software Analytics is a critical part of the process to cut through the “gut feelings” and anecdotal sales/user feedback to the truth!