Taking into account the strategic importance of information and the one related to clients in particular, many companies have focused on segmenting correctly their client data base. However, one of the limits of segmentation of clients is that it’s static, that is, we define a segmentation and, from this, a visit cadence. What if something changes? Are we really going to do a monthly check on our clients’ segmentation?
To cover this problem, we suggest the Dynamic Scoring concept, which has been used for years in banking for years to manage the grants of credits. The concept behind client scoring is the combination of static information from the segmentation with dynamic information, like the time since the last visit, the increasing or decreasing tendency of orders, negotiations, etc. This combination of data allows us to assign a punctuation to every client that lets us rank him according to its importance.
This way, a type A client, considered very important for our company, could have a very low scoring if yesterday he was successfully visited, while a type C client, less important, could have a very high scoring if he hasn’t been visited for months and his orders volume tendency is decreasing, as I could lose him.