By Scott Koegler
Scott Koegler is a writer, publisher, editor, photographer, videographer. He is the community manager at The Enterprising CIO.
Analytics is everywhere. At least talk about analytics is everywhere. And with the amount of big data available for analysis, it's not a surprise that while there is plenty of activity, much of that activity may be misguided, misused, or simply wrong. The more important issue is finding the right use and the right interpretation of the results.
Of course, getting meaningful results means starting with the right data. Mike Dickey, CEO of Cloudmeter, which helps companies use data to optimize the end user experience, finds that there are problems not only with validating that the data being analyzed is correct, but that the necessary data is being used. Dickey says, "You need to be able to capture everything, then focus on what's important and be able to feed that to your analytics solution. It's all about capturing the right data and filtering out what you don't need. To ensure the numbers you are looking at are meaningful, it's also crucial to watch out for blind spots that could lead to a skewed picture of customer experience and behavior."
And that behavior can change quickly. Old data that's processed and reviewed slowly can lead to late assessments and acting on the wrong information. Missing a spike or dip in results can deliver even worse results. Dickey explains, "Be careful of stale data. Your customers perform in real-time and so should your analytics. Getting there requires not only real-time analytics but also the ability to feed your analytics solution with real time data." The systems that collect, house, transform, and deliver the results needed to deliver actionable insights need to accomplish all results, not just a few of them. What's your plan for providing the right infrastructure to deliver the right results?
