CLEMCRM is a solution which helps companies to organize and automate business processes in their marketing and CRM activities. Based on data and text mining technologies CLEMCRM is able to support the customer retention and acquisition, reducing marketing costs and improving satisfaction by offering personalized customer experience.

The following features are available to develop customer relationship management:

Customer Segmentation

Based on the customer's past transactions, their personal and behavioral data specific customer segments can be created, which includes similar customers. Using the segmentation performed by CLEMCRM the main segments and patterns of the customers can be identified. Applying the customer profiles helps organizations to support the development of strategy and marketing campaigns: every customer can be reached with different offers on different ways with various promotions, discounts to increase their satisfaction.

Customer segments may serve as the basis of further analyses, for example customer value, customer retention, increase customer number, cross-selling and fraud detection.

Churn forecasting

Applying CLEMCRM organizations can estimate the probability of customer's churn for the next period based on previous customer, transaction and behavioral data. CLEMCRM is a predictive analytics solution, which reveals the churn behavior and provides deeper insight into the customer's reasons. After identifying risky customers, using the appropriate steps organizations can prevent their churn and strengthen their loyalty. Customer segmentation can help to identify the right next steps.

Customer Value

Based on previous customer, transaction and behavioral data, applying CLEMCRM's predictive methods organizations can classify customers according to their future profitability and probability to churn.

Using CLEMCRM the expected profit from every customer can be predicted so personalized customer experience is provided to every customer. The segmentation supports the identification of specific customer needs, so client's with high customer value can easily be targeted with marketing actions to strengthen the long-term loyalty.


CLEMCRM uses modelling algorithms from the wide model palette of IBM SPSS Modeler: from the popular regression models to the decision trees and neural networks, there are many segmentation and classification models.

CLEMCRM solution includes a specific module based on a co-clustering algorithm to develop more accurate customer segmentation and cross-selling models to improves the efficiency of the marketing campaigns.


The completed models are validated with the usual methodology of data mining tools: hit matrix, gain, lift, ROI.


The CLEMCRM solution is able to automate the daily business processes.