# New RFI Model for Behavioral Audience Segmentation in Wi-Fi Advertising System
## 3 Proposed Framework
### Data Transformation  
After data cleaning, the dataset was then processed to data transformation and transforming those meaningless data into meaningful data, which represented the behavior of each audience in the recency, the frequency, and the interest level towards the advertisement. Therefore, the first step of the data transformation was the RFI modeling. The computations of the recency, frequency, as well as the interest metrics were measured based on the engagement behaviors of an individual audience towards common advertisement campaigns. The recency metric was defined as the time interval between when the audience returned to the Wi-Fi advertising system. The shorter interval allowed for a stronger impression to be retained in the audience's mind. The recency of the specific audience in a campaign was calculated by using the difference between the latest broadcast time \(Broadcast_{t}\) and the previous broadcast time \(Broadcast_{t-1}\) in seconds. If the audience was a one-time audience, the latest broadcast time was the last active time of accessing the specific campaign. As the recency metric was measured in days, the difference of broadcast  
Figure 3: Snippet of the dataset. time was divided, with 86,400 s in a day. The recency metric of a specific audience in a campaign is shown in Equation (1). \[Recency\ (day)=\frac{Broadcast_{t}-Broadcast_{t-1}}{Total\ Seconds\ in\ 1\ Day}. \tag{1}\]  
The frequency metric was defined as the total number of advertisement occurrences recorded by the specific audience in a campaign. The higher occurrence of an advertisement allowed for a stronger impression to be implanted in the subconscious mind of the audience. As the click action of audience to visit the advertisement webpage indicated the audience showing interest towards the advertisement, the interest metric in previous research was measured by the number of click actions [37]. Whenever the audiences were interested, they would respond to the advertisement on its first occurrence; otherwise, they would not respond to the advertisement. The previous research [37] highlighted the limitations of a recorded click action without specifying the view duration of the advertisement. As stated in Section 2.1, both the view duration of the advertisement and the click to visit the advertisement webpage action are crucial components that are used as the measurement criteria of the interest level towards the advertisement. Prior to interest metric formulation, this study must investigate the relationship between the total view duration and the overall number of clicks received within the Wi-Fi advertising system. In this study, a relationship between the total view duration and the overall number of clicks received was found. As the interest metric was formulated to assess the interest level expressed towards the advertisement, it was recommended to exclude the mandatory 10 s non-skippable advertisement display time. Consequently, the view duration was calculated by excluding the mandatory 10 s non-skippable advertisement display time _Mandatory_ from the broadcast time _Broadcast\({}_{t}\)_ of a specific audience in a campaign. Hence, the total view duration _View_ of a specific audience in a campaign is deduced in Equation (2). \[View(seconds)=\sum_{t=1}^{n}Broadcast_{t}-Mandatory. \tag{2}\]  
The relationship between the total view duration and the overall number of clicks received are extracted to determine their correlation. Figure 4 depicts the correlation between total view duration and the overall number of clicks received for the two most active campaigns, which were Campaign 764 and Campaign 776. In order to evaluate the goodness of fit of the linear regression model to the data, the \(R^{2}\) values of Campaign 764 and Campaign 776 were found to be 0.704 and 0.710, respectively. These values indicated that both campaigns exhibited a strong and positive linear relationship between the total view duration and the overall number of clicks received.