In my last blog post, I talked about advanced analytics and what makes it different from traditional business intelligence (BI). If you found yourself asking, “So what?”, here is your answer!
While traditional BI techniques provide business users an easy way to organize and flexibly slice and dice large amounts of data to gain insights from different angles, there are challenges many business functions may experience with only traditional techniques. An advanced analytics architecture offers a set of techniques that help deal with these challenges through statistical and technical methods, ultimately supporting strategic and fact-based decisions.
The sections below describe some of the questions various business functions strive to answer – questions where a traditional BI architecture and techniques may fall short and advanced analytics shine.
Marketing and Customer Analytics
Customers are becoming more sophisticated and finicky, so understanding them in order to improve their experiences is the key to success. Organizations who can accurately predict a customer’s needs and match it to the right product at the right price will gain an upper hand over their competition.
While BI systems can integrate data from multiple sources and present historical performance to users in a clean and predefined format (e.g., reports and dashboards), they are limited in their ability to uncover hidden patterns in a timely manner.
Also, simple operators and formulae may not be able to adequately show the significance of differences observed in the numbers. Advanced analytics, fortunately provides a quantitative approach to answer these questions and address these challenges.