Thanks to customer segmentation it is possible to divide customers into groups of similar profiles. A company can this way define the most valuable groups of customers and what is more – identify precisely those who generate low profits or even losses. Option of creating and using such analysis helps undertake more precise and efficient marketing activities, thereby direct a marketing campaign to specific audience whose behaviors and preferences are known.
With a basket analysis it is possible to automatically search for products that are most commonly purchased together. As a result, it is possible to use the Next Best Offer mechanism, that is to suggest to the customer a product that he or she usually purchases along with other items. This type of system contributes to defining a shopping basket that will provide information helpful in organizing company's promotional activities as well as to more efficient product merchandising that can result in up- and cross-selling.
Customer migration analysis allows identifying customers who are likely to stop using existing services or purchase specific products. Owing to that, it is possible to take actions aimed at minimizing risks resulting in the loss of the customer.
Nowadays, almost every company is exposed to various types of frauds which, along with advancement in technology, are increasingly difficult to detect and prevent.
Through data analysis and the usage of advanced predictive models, Comarch Business Intelligence solution allows for accurate analysis and rapid response to negative incidents in order to, for example, minimize possible financial losses. Thanks to statistical analysis of, among others, customer transactions and the implementation of appropriate algorithms, it is possible to detect single fraud cases.
In the context of loyalty programs, it is important to reach a specific target group of clients and create adequate marketing campaigns. Owing to that, it is possible to optimize the whole marketing process with regard to the costs of a conducted campaign, contact with customers and resources allocation. Using data mining processes it is possible to obtain information concerning customers’ needs and expectations and to evaluate the effectiveness of customer acquisition. By specifying customers’ preferences and habits, it is also possible to identify their patterns of behavior.
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