New RFI Model for Behavioral Audience Segmentation in Wi-Fi Advertising System
In this technological era, businesses tend to place advertisements via the medium of Wi-Fi advertising to expose their brands and products to the public. Wi-Fi advertising offers a platform for businesses to leverage their marketing strategies to achieve desired goals, provided they have a thorough...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-10-01
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| Series: | Future Internet |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-5903/15/11/351 |
| _version_ | 1797459274572496896 |
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| author | Shueh-Ting Lim Lee-Yeng Ong Meng-Chew Leow |
| author_facet | Shueh-Ting Lim Lee-Yeng Ong Meng-Chew Leow |
| author_sort | Shueh-Ting Lim |
| collection | DOAJ |
| description | In this technological era, businesses tend to place advertisements via the medium of Wi-Fi advertising to expose their brands and products to the public. Wi-Fi advertising offers a platform for businesses to leverage their marketing strategies to achieve desired goals, provided they have a thorough understanding of their audience’s behaviors. This paper aims to formulate a new RFI (recency, frequency, and interest) model that is able to analyze the behavior of the audience towards the advertisement. The audience’s interest is measured based on the relationship between their total view duration on an advertisement and its corresponding overall click received. With the help of a clustering algorithm to perform the dynamic segmentation, the patterns of the audience behaviors are then being interpreted by segmenting the audience based on their engagement behaviors. In the experiments, two different Wi-Fi advertising attributes are tested to prove the new RFI model is applicable to effectively interpret the audience engagement behaviors with the proposed dynamic characteristics range table. The weak and strongly engaged behavioral characteristics of the segmented behavioral patterns of the audience, such as in a one-time audience, are interpreted successfully with the dynamic-characteristics range table. |
| first_indexed | 2024-03-09T16:49:07Z |
| format | Article |
| id | doaj.art-9cd08919da7d4f52a5feabfee851d9cf |
| institution | Directory Open Access Journal |
| issn | 1999-5903 |
| language | English |
| last_indexed | 2024-03-09T16:49:07Z |
| publishDate | 2023-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Future Internet |
| spelling | doaj.art-9cd08919da7d4f52a5feabfee851d9cf2023-11-24T14:43:09ZengMDPI AGFuture Internet1999-59032023-10-01151135110.3390/fi15110351New RFI Model for Behavioral Audience Segmentation in Wi-Fi Advertising SystemShueh-Ting Lim0Lee-Yeng Ong1Meng-Chew Leow2Faculty of Information Science and Technology, Multimedia University, Jalan Ayer Keroh Lama, Melaka 75450, MalaysiaFaculty of Information Science and Technology, Multimedia University, Jalan Ayer Keroh Lama, Melaka 75450, MalaysiaFaculty of Information Science and Technology, Multimedia University, Jalan Ayer Keroh Lama, Melaka 75450, MalaysiaIn this technological era, businesses tend to place advertisements via the medium of Wi-Fi advertising to expose their brands and products to the public. Wi-Fi advertising offers a platform for businesses to leverage their marketing strategies to achieve desired goals, provided they have a thorough understanding of their audience’s behaviors. This paper aims to formulate a new RFI (recency, frequency, and interest) model that is able to analyze the behavior of the audience towards the advertisement. The audience’s interest is measured based on the relationship between their total view duration on an advertisement and its corresponding overall click received. With the help of a clustering algorithm to perform the dynamic segmentation, the patterns of the audience behaviors are then being interpreted by segmenting the audience based on their engagement behaviors. In the experiments, two different Wi-Fi advertising attributes are tested to prove the new RFI model is applicable to effectively interpret the audience engagement behaviors with the proposed dynamic characteristics range table. The weak and strongly engaged behavioral characteristics of the segmented behavioral patterns of the audience, such as in a one-time audience, are interpreted successfully with the dynamic-characteristics range table.https://www.mdpi.com/1999-5903/15/11/351behavioral modelengagementbehavioral audience segmentationclustering algorithmsbehavioral characteristics and patterns |
| spellingShingle | Shueh-Ting Lim Lee-Yeng Ong Meng-Chew Leow New RFI Model for Behavioral Audience Segmentation in Wi-Fi Advertising System Future Internet behavioral model engagement behavioral audience segmentation clustering algorithms behavioral characteristics and patterns |
| title | New RFI Model for Behavioral Audience Segmentation in Wi-Fi Advertising System |
| title_full | New RFI Model for Behavioral Audience Segmentation in Wi-Fi Advertising System |
| title_fullStr | New RFI Model for Behavioral Audience Segmentation in Wi-Fi Advertising System |
| title_full_unstemmed | New RFI Model for Behavioral Audience Segmentation in Wi-Fi Advertising System |
| title_short | New RFI Model for Behavioral Audience Segmentation in Wi-Fi Advertising System |
| title_sort | new rfi model for behavioral audience segmentation in wi fi advertising system |
| topic | behavioral model engagement behavioral audience segmentation clustering algorithms behavioral characteristics and patterns |
| url | https://www.mdpi.com/1999-5903/15/11/351 |
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