We’re pretty positive that if you’re reading this, you already know what marketing segmentation is and most likely clustering as well. For those that may not understand what these terms mean, we will define them before diving in. Marketing segmentation is the identification of unique groups with commonalities that exist within your audience and will respond to market action similarly. It can be done through geographic locations, demographics, psychological traits, filmography, and/or behaviors. It helps brands minimize risks through understanding which products/services will sell and the best way to market them. Clustering is very similar to this. It uses machine tech and algorithms to find these unique relationships between the people in your audience. The difference here is that while marketing segmentation organizes the audience, clustering actually creates new groups based on their unique characteristics. This helps brands gain a competitive advantage over their competitors. The benefits of clustering vs segmentation are that it is done through machine learning and not manually. But, that being said, it’s also a pitfall. It cannot be done with technology. Let’s imagine that a brand has a high-end dress line. They use clustering to find out who they should market too. You enter data that you’ve collected from past purchases and input this into a cluster analysis tool that will give you the answers you’re looking for. This is an example of clustering in marketing. It helps tailor messaging for the right groups. Segmentation can only take you so far is a broader approach while clustering dives into the quantum details of your audience.
