Filtreler
Applications of data mining algorithms for customer recommendations in retail marketing

ELİF DELİCE

Makale | 2022 | Nova Science Publishers, Inc.

In recent years, researchers have highlighted how large volumes of data can be transformed into information to determine customer behaviors, and data mining applications have become a major trend. It has become critical for organizations to use a tool for understanding the relationships between data to protect their marketplace by increasing customer loyalty. Thanks to data mining applications, data can be processed and transformed into information, and in this way, target audiences can be determined while developing marketing strategies. This chapter aims to increase the market share with products specific to the customer portfolio . . ., introduce strategic marketing tools for retaining old customers, introduce effective methods for acquiring new customers, and increase the retail sales chart, based on purchasing habits of customers. The data set was collected under pandemic conditions during the COVID-19 process and analyzed to support retail businesses in their online shopping orientation. By examining the local customer base, it was assumed that the customer group would display similar behaviors in online or teleordering methods, customer identification and order estimation were made to follow an effective sales policy. Segmentation was performed with data mining applications, and the grouped data were separated according to their similarities. The data set consisting of demographic characteristics and various product information of the enterprise's customers were analyzed with Decision Tree and Random Forest, which are data mining methods, the best performing algorithm in the data set was selected by comparing the performance of the methods. As a result of the findings, appropriate suggestions were given to the business to determine the purchasing tendencies of the customers and to increase the level of effectiveness in sales-marketing strategies. In this way, materials were presented to assist the enterprise in developing strategies to increase the number of sales by taking faster and more accurate action by avoiding the time and expense that would be lost by the trial-error method. © 2022 Nova Science Publishers, Inc. All rights reserved Daha fazlası Daha az

Data analytics applied to the human resources industry

CEM UFUK BAYTAR

Makale | 2022 | Nova Science Publishers, Inc.

The department of human resources in companies plays an active role in the architecture of a strategic workforce in terms of creating and managing human capital. It is necessary to embody its strategies with appropriate raw data and accurate analyses. Human resources management gains the feature of being a strategic partner in company management by generating strategies based on consistent measurements related to the workforce. As a result of such an approach, it has an important place in creating competition in businesses and maintaining the existence of businesses. Innovations, which emerge with the transformation of data into inf . . .ormation, not only offer a competitive advantage to companies but also help them make better decisions. In parallel with the developments in technology, changes in the business environment force human resources management to be prepared for these changes and to transform itself with this change. In this study, the concept of analytics is discussed concerning human resources. In addition, by trying to explain the relationship between human resources and analytics concepts, the opportunities waiting for human resources are revealed. As a result, it is clear that digital transformation and developments in technology make the importance of human resources increase. © 2022 Nova Science Publishers, Inc. All rights reserved Daha fazlası Daha az

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