Traditional static relationship management models, in which clients are classified and managed according to their assets, are no longer appropriate in retail banking. Clients are managed in portfolios, i.e. assigned to an advisor, without clients explicitly expecting this. In such a service model, the assigned advisor is responsible for all client concerns as well as the portfolio analysis and invests a lot of time in maintaining the client relationship.
In dynamic care models, the efficiency of customer care can be significantly increased through the use of customer intelligence (CI). The data-driven identification of potential encompasses the entire customer base and is no longer limited to those customers with whom the bank is currently in contact. Leads generated by CI become the central sales instrument in potential-oriented, dynamic support.
In accordance with the strategic orientation, data evaluation campaigns are programmed that provide the appropriate client advisor with leads according to defined criteria and thus provide him with information on a possible sales opportunity. In this way, the client advisor can target clients with potential and focus his advisory services on those topics that have a high probability of closing a deal. This ensures that the client receives the best possible advice with regard to his individual concerns.
Flexibility in cross-channel customer allocation is of great importance for the success of such a dynamic service model. The interaction of the different channels and organisational units must be clearly regulated and anchored in the processes. The role of the advisor and thus the required skills are changing. Instead of the classic customer relationship management on a limited customer base (farming), advisors must address a much larger number of customers based on leads and process them without relationship history (hunting).