Improving-Effectiveness-of-Direct-Marketing-through-Predictive-Modellling

Customer Retention using supervised classification algorithms

Direct marketing in the sector of banking, aims to establish a cost-effective way of marketing. To achieve efficient direct marketing, possessing information about the present and estimating future customer’s preferences always provides an edge over the competitors. The availability of prospective customer data combined with improvements in data analysis has prompted firms to develop more customer-oriented strategies in recent decades to remain competitive.Direct Marketing campaigns can have high failure rate if the target customers are not chosen properly. This project can help such Data Marketing campaigns to choose their target customer well so that time and resources can be saved for the banking institution. From the customer’s point of view a smaller number of non-interested target audience will get disturbed by the Direct Marketing campaign.Transactions in banks are recorded on day-to-day basis and customer-relationship is very important these days. Customers are made aware of new products or services offered by the bank.

Telemarketing, which is a very popular form of direct marketing, targets customers from a database of prospective customers. To ensure the success of techniques such as this, the company must focus on their potential customer database by predicting the customers who have higher chances of using the product or service.Many banks have been using data mining techniques to predict the class of customers who are most likely to buy or use the products or services. Nowadays, commercial banks implement telemarketing campaign to optimize the allocation of resources, satisfy the needs of customers, thus, enhancing the productivity of companies.Through a marketing campaign, contacting clients on telephone directly, the bank intends to select the best set of clients. It is beneficial for narrowing the range of potential customers, elevating the rate of success as well as reducing the cost of the marketing process efficiently.