Predictive Marketing is the process, tools and rules for applying predictive analytics to making marketing and sales decisions.
Predictive Marketing is not a replacement for more traditional marketing approaches. Marketing and sales decisions will continue to be based mostly on product releases, inspirational ideas, what competitors and peers are doing, and what has worked well in the past. What Predictive Marketing will do is supplement traditional marketing with a new, more analytical method of sorting and prioritising marketing and sales actions.
One of the key aspects of Predictive Marketing is Predictive Marketing Analytics (PMA), which involves using historical customer data to predict future outcomes and trends. For example, PMA can tell you which accounts to target for churn prevention and which leads are most likely to become customers and are, thus, most worth pursuing. PMA is typically and predominantly done using computer algorithms (e.g., Machine Learning).
Graphic 1: Predictive Marketing Analytics Process
During the last five years, the majority of B2C companies have started utilising Predictive Marketing Analytics. But PMA is really nothing new. The individual methods and formulas have been around for almost fifty years. So what is behind its recent growth in popularity? The explanation is that three critical enablers have simultaneously matured to the point at which PMA has become easily accessible to almost any company.
Predictive Marketing Analytics isn't an absolute science. Like traditional marketing, it is some combination of art, intuition, and science. But it does provide companies with the ability to more reliably forecast customer behaviour.
Read the second part of the blog series to find out how Predictive Marketing adds value to many business processes.
Interested in hearing more? Contact us for a free consultation and let's see how Predictive Marketing Analytics can work for you.
The blog was originally posted on idBBN.com.
Matti Airas is an expert in customer feedback management, marketing automation, predictive marketing analytics, and how to use data and machine learning to automatically trigger customer interactions. Before joining Tieto, Matti worked for a customer feedback analysis company Etuma and before that Nokia in the U.S.