The other day, my analytical team at a major telecommunications company and I were presenting an all-new behavioral segmentation to one of our senior executives. Seeing the first slide, the executive jumped out of his seat in excitement and exclaimed, “Some of these insights took me years to uncover after repeated trial and error and hundreds of BI (business intelligence) reports.”
Using a cell phone to make a voice call leaves behind a significant amount of data. The cell phone provider knows every person you called, how long you talked, what time you called and whether your call was successful or if it was dropped. When you use your cell phone, the cell phone provider knows where you are, where you make most of you calls from, which promotion you are responding to, how many times you have bought before and so on. In many cases, a cell phone is the only thing people carry with them at all times.
For a BI analyst trying to make sense of all of this data, the task becomes manageable thanks to hundreds of attractive looking tools that instantly create reports presenting data in every conceivable slice, graph, table, pivot or dump imaginable.
However, no matter what tool you use, the best that traditional BI can help you understand is what happened. It cannot, no matter how much you torture the data, tell you when something happened, who will it happen to or why something happened. This is precisely the reason that advanced analytics is so important; it’s the difference between the 99 percent of effort that typically yields very little insight, and the 1 percent that provides a window into the mind of a customer.
Borrowing an analogy from the popular MasterCard commercial, the distinction can also be seen as:
Analytics is not always easy – petabytes of data everywhere and a priceless insight difficult to find. Creating terabytes of reports, engineering gigabytes of excel sheets by writing killer macros and presenting them in flashy slides to top management in the hope that all this effort will tell you something and result in action rarely occurs.
On the other hand, combining the what with the when, who and why will provide a company with a long-term strategic competitive advantage.
Many different methodologies answer the when, who and why questions including:
If you are new to this world, the last bulleted item – the why question – is a great way to start your foray because it is easy to implement and full of insights that will be very action-oriented.
Though traditional BI has several benefits and is easy to implement, it is confined in its ability to predict, identify and give a full customer view, e.g. predicting customer lifetime, identifying triggers for churn, measuring the influence of social network on your customer’s decisions or suggesting the next best offer.
Chief Analytics Officer Spring 2017
15% off with code MP15
Big Data and Analytics for Healthcare Philadelphia
$200 off with code DATA200
10% off with code 7WDATASMX
Data Science Congress 2017
20% off with code 7wdata_DSC2017
20% off with code AIP17-7WDATA-20