SetXRM has created 3 different systems for RM solutions. Data on these systems propose different marketing approaches. Our main aim is to analyze our customers perfectly, separate them into segments and take related action. After these analyses, it is detected whether the activities have reached the intended target customers and thus accuracy of applied sales and marketing strategies can be questioned. For SetXRM analytic CRM, these systems are available.
Estimation Service: It is the most important service of Analytical CRM systems. This system aims creating estimation processes in line with previous classification algorithms which were developed in the previous term. Within this process, estimation service creates a decision tree algorithm to see or estimate to which classifications new customers might be suited. Decision Tree algorithm makes use of available customer data and creates a decision tree. Root an intermediary nodes of decision tree contain customer features while leaf nodes contain classifications. Information of new customer is entangled on the tree to estimate which class this customer is most suited up for. Decision tree algorithm works on categorical data. That is why our available data needs to be categorized and transferred to decision tree making service.
Customer scoring: In Analytical CRM applications, RFM (Recency, Frequency, Monetary) scoring service creates a score on last shopping date of customer, shopping amount and frequency of a customer. This score will be used to measure loyalty of a customer. Customers with highest RFM scores are the ones who are most likely to answer to promotions and marketing campaigns of the company.
N-layer validation service: In Analytical CRM applications, N-layer Validation Service is used for measuring success rates of cumulating algorithms. N-layer validation technique is used in services. N number is submitted to methods as parameters. His number specifies the number of divisions data set will have to apply validation process. The service submits a success percentage in line with submitted data and n number.