Developing existing product pricing strategies according to customer types and investigation of their effects on profit maximization - a bank example

One of the most important components of the marketing tools that businesses use in line with their goals is the financial source and the price. Pricing at the right place and time with the appropriate strategy is an important issue in terms of sustainability, which is the main goal of businesses. Pricing includes production and service costs, sales volume, competitors' prices, market conditions, etc. varies depending on the factors. Therefore, the pricing process should be established with appropriate methods and strategies and supported by studies in line with the changing and transforming world dynamics. The aim of this thesis is to analyze the pricing method called customer-based pricing, to ensure the continuity of product and price attractiveness and to develop a price strategy that will maximize total profit. In this context, the time deposit product of a joint stock bank is handled, and the internal and external factors affecting the pricing, depending on the market, are examined. Examples of these factors are customers' consumption behavior, product and price ownership, asset information, estimated income calculations, customers' purchasing tendencies, marketing channels to communicate with customers, competitor prices and market conditions. In line with the principles examined in the literature, the types of customers were decided with methods suitable for the business, bank, structure and nature of the product. Demand forecasting has been studied with a modeling prepared by considering the conditions that will affect the demand of existing customers and potential buyers who already own the product. The main factors that will affect the demand for the product are the sensitivity of the customers to the price, other actions related to the decision to purchase the product and the factors that make up the cost of the product. The demand mentioned in this study, which is intended to be estimated, is whether the customers will extend the time deposit product, that is, the calculation of the process of extending the product period at the end of maturity. It is aimed to minimize the variance between the targeted demand and the actual demand. It has been decided that the most appropriate solution for this working environment where customer and market movements are dynamic is the Boosting algorithm. The pricing process is designed for the existing customer group, which is decided after the demand forecast calculated using the Python program. Then, the customer-specific price determined by appropriate pricing methods was presented to the customer through various communication channels of the bank, and the reaction of the customers to the price and the purchase return rates were examined. It was observed that this study increased profit and income as a result of the new price and the penetration of the previous price with other products and the profit/cost analysis specific to the product. Profitability was also analyzed with the profit margin obtained and the market share that the product brought to the bank. Keywords: Boosting algorithm, Gradient boosting algorithm, Customer-based pricing, Mass customization, Profit maximization.