Years ago when I first heard agencies and corporations talking about “Analytics,” I must confess, I got a little worried. As someone with a graduate degree in applied statistics, I had a definite perception of what the term “Analytics” means. In my mind the term Analytics was related to the use of statistics, mathematics, and predictive modeling to find patterns, meaning, and probabilities in data. As many around me in business and marketing circles bandied around the term “Analytics,” for a short period I saw my training in data science becoming somewhat useless as it seemed that everyone now had the ability to develop “Analytics.”
I now realize that this is not entirely true.
The purpose of this article is to draw a distinction between the different types of Analytics because they are not all the same.
The term “Analytics” has become a blanket term that includes:
Predictive Analytics is used in both Advanced Analytics and Machine Learning/Artificial Intelligence.
Often referred to as “Analytics,” reporting refers to the process of exploring data (e.g. with frequency counts or crosstabs) and generating a report of the findings. Fundamentally, this process turns raw data into actionable information.
Technically, reporting is not Analytics but it is described as such by many in marketing as Analytics. A readily accepted definition of Analytics in mathematical and statistical circles is the use of statistics, mathematics, and predictive modeling to find patterns, meaning, and probabilities in data.
Reporting is geared towards examining the outcomes of “past” marketing efforts and decisions. It is typically a rear-view mirror approach and does not provide projections about the future. The biggest benefit of Reporting is that it is immediate and it can zone in on the where and what; however, Reporting does not provide any detail on the why.
Advanced Analytics is the analysis of data or content using sophisticated tools and statistical techniques to obtain rich insights, make predictions, and/or make recommendations. Techniques used in advanced analytics range from data/text mining to forecasting and visualization, and include:
Advanced Analytics typically requires substantial human intervention. A special category of Advanced Analytics occurs when Machine Learning/Artificial Intelligence is involved.
MACHINE LEARNING/ARTIFICIAL INTELLIGENCE
Machine Learning or Artificial Intelligence is where the Analytics processor becomes smarter over time and is able to “understand” and optimize itself with less direction from humans.
Predictive Analytics includes a variety of Advanced Analytics approaches from data mining and statistics to analyze current and historical data in order to make predictions about the future. Predictive models leverage patterns in survey, historical, and transactional data to identify opportunities and risks by applying the principles of probability theory. These tools allow businesses to set business strategies based on future projected customer activities and help justify marketing efforts. Machine Learning is also sometimes incorporated into predictive models.
APPLICATIONS OF PREDICTIVE ANALYTICS
Predictive analytics is applied to many different types of projects. Some examples of Predictive Analytics used in marketing include:
WHAT IS ANALYTICS?
Using a strict mathematical or statistical definition of “Analytics,” the discipline includes:
Reporting, labeled by some as “Analytics” is not technically Analytics. However, all types of Reporting and Analytics are important tools in the marketer’s tool box.
Predictive Analytics are some of the most effective tools in the marketing arsenal. Reporting is taking a rear-view mirror approach. Predictive Analytics is akin to having a crystal ball to look into the future.
Kirsty Nunez is the President and Chief Research Strategist at Q2 Insights, Inc., a research and innovation consulting firm with offices in San Diego and New Orleans. One area in which Q2 Insights is well practiced and well-known is Predictive Analytics. If you would like to learn more, please reach out to Kirsty at (760) 230-2950 ext. 1 or email@example.com.
This entry was posted in Market Research and tagged on June 18, 2018 by Q2 Insights