Marketing Decision Support System Based on Data Mining Technology
With the continuous development of business intelligence technology, the application research of decision support systems (DSSs) is deepening. In China, the work in this area started relatively late, and there are few DSS research cases to assist in marketing decision-making. Currently, marketing de...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-03-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/13/7/4315 |
| _version_ | 1797608320376242176 |
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| author | Rong Hou Xu Ye Hafizah Binti Omar Zaki Nor Asiah Binti Omar |
| author_facet | Rong Hou Xu Ye Hafizah Binti Omar Zaki Nor Asiah Binti Omar |
| author_sort | Rong Hou |
| collection | DOAJ |
| description | With the continuous development of business intelligence technology, the application research of decision support systems (DSSs) is deepening. In China, the work in this area started relatively late, and there are few DSS research cases to assist in marketing decision-making. Currently, marketing decision support systems have shortcomings in data integration, historical data, query functions, and data analysis. This article analyzes the characteristics of marketing decision-making, discusses the application of data warehouse, OLAP, and data mining technology in marketing decision support systems, and designs a marketing decision support system based on data mining technology. The system uses a BP neural network to conduct data mining marketing forecasting. A three-layer network model for marketing prediction is established, with sales time, product price, and customer purchasing power as network inputs and output as the sales volume of a certain type of product in different locations. The test results show that the average absolute percentage error of this method is 15.13%, and the prediction accuracy is high. Research shows that with the continuous development of data mining technology, the system cannot only help users conduct scientific and reasonable marketing decision-making analyses, making the marketing decision-making process more scientific and reasonable, but also can bring new ideas to enterprise decision-makers, promoting the continuous improvement and progress of the system. |
| first_indexed | 2024-03-11T05:42:48Z |
| format | Article |
| id | doaj.art-55bec95ec39d4e51a0415b9721e3d608 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T05:42:48Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-55bec95ec39d4e51a0415b9721e3d6082023-11-17T16:18:35ZengMDPI AGApplied Sciences2076-34172023-03-01137431510.3390/app13074315Marketing Decision Support System Based on Data Mining TechnologyRong Hou0Xu Ye1Hafizah Binti Omar Zaki2Nor Asiah Binti Omar3Faculty of Economics and Management, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, MalaysiaFaculty of Economics and Management, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, MalaysiaFaculty of Economics and Management, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, MalaysiaFaculty of Economics and Management, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, MalaysiaWith the continuous development of business intelligence technology, the application research of decision support systems (DSSs) is deepening. In China, the work in this area started relatively late, and there are few DSS research cases to assist in marketing decision-making. Currently, marketing decision support systems have shortcomings in data integration, historical data, query functions, and data analysis. This article analyzes the characteristics of marketing decision-making, discusses the application of data warehouse, OLAP, and data mining technology in marketing decision support systems, and designs a marketing decision support system based on data mining technology. The system uses a BP neural network to conduct data mining marketing forecasting. A three-layer network model for marketing prediction is established, with sales time, product price, and customer purchasing power as network inputs and output as the sales volume of a certain type of product in different locations. The test results show that the average absolute percentage error of this method is 15.13%, and the prediction accuracy is high. Research shows that with the continuous development of data mining technology, the system cannot only help users conduct scientific and reasonable marketing decision-making analyses, making the marketing decision-making process more scientific and reasonable, but also can bring new ideas to enterprise decision-makers, promoting the continuous improvement and progress of the system.https://www.mdpi.com/2076-3417/13/7/4315data mining (DM)marketing decisionsdecisions support system (DSS) |
| spellingShingle | Rong Hou Xu Ye Hafizah Binti Omar Zaki Nor Asiah Binti Omar Marketing Decision Support System Based on Data Mining Technology Applied Sciences data mining (DM) marketing decisions decisions support system (DSS) |
| title | Marketing Decision Support System Based on Data Mining Technology |
| title_full | Marketing Decision Support System Based on Data Mining Technology |
| title_fullStr | Marketing Decision Support System Based on Data Mining Technology |
| title_full_unstemmed | Marketing Decision Support System Based on Data Mining Technology |
| title_short | Marketing Decision Support System Based on Data Mining Technology |
| title_sort | marketing decision support system based on data mining technology |
| topic | data mining (DM) marketing decisions decisions support system (DSS) |
| url | https://www.mdpi.com/2076-3417/13/7/4315 |
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