Who are your customers?
What type of customers do you have? What appears to be a simple question may not be so simple to answer. It is reasonably straight forward to segment customers by a single metric such as ‘total spend’ or ‘total time subscribed’ but what happens when there are many different attributes? For example, what do they buy, when do they typically purchase, frequency of purchase, the size of each purchase or a host of any other attributes related to how they interact with your website or product. Conceptualising how to trade-off and weight these different aspects to find ‘similar’ customers can be a difficult task.
Go beyond just demographics
Madlytics utilises machine learning and statistical modelling to be able to take into account all the various attributes of your customers and divide them into similar groups. Being able to understand what sort of customers you have and what sort of variables are driving this segmentation is powerful knowledge for business decision makers.
Utilising this knowledge, organisations are able to perform deep retrospection on who they are currently servicing and how they are servicing their different segments. Organisations can use this knowledge to better service existing customers, attract similar customers or strategically move into servicing new customers.