在数据科学的帮助下,银行服务部门的营销策略

IF 1.2 Q4 MANAGEMENT Marketing and Management of Innovations Pub Date : 2022-01-01 DOI:10.21272/mmi.2022.2-11
T. Zatonatska, Maryna Hubska, V. Shpyrko
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引用次数: 4

摘要

企业营销策略之间的竞争转向人工智能的使用,并开始在数据科学项目之间竞争的背景下进行考虑。因此,在特定领域开发方法和建立模型的问题是相关的,这将使项目非常有效,并确保实现公司的目标。银行服务市场具有一定的消费者行为特殊性,因此营销策略的形成是一个比较复杂的过程。因此,银行面临着保持现有客户忠诚度和吸引新客户的任务。本文旨在利用数据科学工具建立一个营销策略,以吸引银行业的新客户。研究的结果是构建了现金贷款和信用卡这两种不同银行信贷产品的计量经济模型,确定了各因素对这一过程的影响,有助于在不同类型的广告之间分配广告预算。利用所建立的模型,确定广告活动直接影响银行新客户数量的增加和社会对银行机构品牌知识的整体增长。此外,确定每个影响因素的权重有助于形成广告预算,增加了12%的客户流入量,平均投资回报率为3.18。考虑到所有因素,当使用数据科学技术做出决策时,该模型在组织银行广告活动方面显示出了其有效性。基于这些模型得到的结果对影响银行新客户流入的因素有了一个相当清晰的认识,这将对未来广告活动的预算分配进行建模,并预测其有效性。该国金融业的竞争正迫使银行机构在其营销活动中使用数据科学。
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Marketing Strategies in the Banking Services Sector With the Help of Data Science
Competition between marketing strategies of enterprises shifts to the use of artificial intelligence and begins to be considered in the context of competition between Data Science projects. Therefore, the issue of developing methodology and building a model in a particular area is relevant, which will make the project quite effective and ensure the achievement of goals for the company. The banking services market has a certain specificity of consumer behaviour, so forming marketing strategies is a somewhat complex process. Thus, banks face the task of maintaining the loyalty of their existing customers and attracting new ones. This article aims to build a marketing strategy to attract new customers in the banking sector using Data Science tools. The result of the study is the construction of two econometric models of the different bank's credit products: cash loans and credit cards, which determine the influence of various factors on this process and helps to distribute the advertising budget between different types of advertising. Using the built model, it was determined that advertising campaigns directly affect the increase in the number of new customers in the bank and the overall growth of brand knowledge about the banking institution in society. In addition, the determined weights of each influencing factor helped form an advertising budget, which increased customer inflows by 12%, with an average ROI of 3.18. Taking all into account, the model had shown its effectiveness in organising the bank's advertising campaign when decisions were made using Data Science technologies. The results obtained based on the models give a fairly clear understanding of the factors influencing the inflow of new customers in the bank, which will model the distribution of the budget for advertising campaigns in future periods and predict their effectiveness. Competition in the country's financial sector is forcing banking institutions to use data science in their marketing activities.
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