Since retail banks have understood the benefits of a targeted marketing method, the normal marketing technique is not in favor. Banks would be able to segment consumers into groups based on the demographic and consumer behavior, by following a targeted marketing approach.
Creating a positive customer experience in the extremely competitive retail banking environment is a significant challenge for the retail banks. Guided by the enhancement in the availability of multiple communication devices & technologies, customer expectations have undergone a transformation.
Banks have to offer personalized products to stay in business. The basic assumption with regard to predictive analysis is very simple, predictive analytics can furnish the banks useful insights into the regularly transforming consumer behavior and requirements throughout the consumer life cycle.
Banks usually follow the normal marketing technique of having marketing campaigns year-on-year. The marketing strategy is based on in-house measures instead of consumer preferences. Targeted marketing campaigns emphasize consumer requirements that result in an effective reply rate.
The utilization of predictive analytics requires banks to finalize critical data points to ensure successful marketing:
Communicating with Customers
Predictive analytics can assist in identifying the high-value customers to be targeted. This reduces the no of customers to be communicated, thereby ensuring significant cost reduction while enhancing the reply rates.
Predictive analytics can enable a bank to identify the best channel to communicate with a targeted customer. This would to a large extent enhance the response rate. Therefore, predictive analysis enables banks to maximize the marketing campaigns across the channels. The focus on communicating with the client through a preferred channel could assist in enhancing the customer loyalty.
Providing customers with unwanted offerings could result in alienation. Under these circumstances, predictive analytics would perform a vital role. The technology would enable the customer to evaluate all existing products delivered by a bank and select one that matches the customer’s choice. The method would be useful in initiating a need-based selling.
The timing of a marketing offer is critical. Predictive analytics can assist in monitoring consumer databases to identify critical life outcomes, thereby ensuring delivery of the perfect offer at the appropriate time.
Leveraging Predictive Analytics across the Consumer Life cycle
Leveraging predictive analytics can assist a bank in providing the most optimal offer at an appropriate time. The basic crux of predictive analytics is in comprehending the relationships between previously detailed customer actions and non-detailed actions which can be used to forecast the probable actions.
In the recent past, there has been a significant requirement for retail banks to manage certain issues such as cementing relationships with high-value clients. Therefore, banks have spent on analytics tools.
The advanced analytical apps enable banks to validate the clients based on key information – credit worthiness, loan portfolio among others. The customers spending pattern can also be monitored to determine the customer’s loan repayment capability. All debtors can be forced to make the payment.
It ensures lesser customer attrition. Banks can monitor a customer’s previous record to ascertain the possibility of the customer moving to another bank. Leveraging predictive analytics would assist the banks in interfacing with HNIs and develop customized marketing plans to retain their accounts.
Banks continue to face several obstacles. The main objectives of banks are to transform prospects into clients, manage relationships with HNIs and enhance revenue. The use of predictive analytics in marketing would assist in providing specific offers, thereby boosting sales.