Analytics

BobL · ‎09-12-2013

In my previous blog in the Customer Analytics Series, I discussed the first of three challenges we uncovered in our survey about customer analytics usage. Now, let’s explore the second significant challenge, which has to do with a user’s ability to actually do what they need to do with the data.

Within most companies, the data needed for customer analytics is spread across many disparate systems. Many people feel like they have no option other than to turn to their IT department to begin a long and complicated data blending and analytics project, with a detailed scope of work and multiple revisions. Typically, that takes a long time to determine what’s actually going on, and what’s really impacting the way customers interact with you. More often than not, by the time you get the answer to your question, the market has changed, and the question, let alone the answer, is no longer relevant.

In response to the limited IT resources available to them and the deadlines that many have to deal with, a lot of users attempt to do their own analytics in programs such as Microsoft Excel or Access. In fact, there are literally hundreds of specialized tools out there to accomplish specific tasks such as data blending, data cleansing, analytics, and reporting. The problem is that in order to get the answers you need, you literally have to pass data back and forth between all of these tools, making things extremely complex and putting the validity of your analysis at risk.

The other major problem is that some of these tools were not designed for mere mortals like us to use. They require complex coding and have steep learning curves, which is why these tools rarely make it out of the IT department where most users having advanced degrees in mathematics or statistics.

Clearly, the way to address this challenge is by making real analytics tools easier to use and more accessible to users in the line of business – the people who deal with the business problems day in and day out. That way they can free up IT resources to focus on things like data collection, security and access, and allow the users with the industry knowledge and skills to focus on getting the insight from the data.