# New RFI Model for Behavioral Audience Segmentation in Wi-Fi Advertising System
## 2 Related Works  
### Behavioral Analysis  
Behavioral analysis has been the focus of numerous research investigations in recent years. Many of these have significant practical uses, particularly from a marketing standpoint. There are many indicators that serve as metrics to examine the behaviors of the customers or users. In existing publications, the RFM model, which refers to the recency, frequency, and monetary values, is a method of behavioral analysis that is widely used in different domains ranging from the e-Commerce, banking, to insurance industries. Table 1 illustrates the application of behavioral segmentation in these domains. \begin{table}
\begin{tabular}{c c c c c} \hline \multirow{2}{*}{**Domain**} & \multirow{2}{*}{**Year**} & **Behavioral** & **Behavioral** & \multirow{2}{*}{**Purpose of Application**} \\  & & **Analysis** & **Segmentation** & \\ \hline \multirow{6}{*}{e-Commerce} & \multirow{2}{*}{2021 [4]} & \multirow{2}{*}{RFM model} & \multirow{2}{*}{K-means clustering} & \multicolumn{2}{c}{Purchasing behavioral segmentation} \\  & & & & - Segment the customers according to their purchasing behaviors as the marketing reference. \\ \cline{2-5}  & & & & - Segment the customers based on their shopping behaviors to discover their online shopping patterns. \\ \cline{2-5}  & & & & - Segment the customers according to their behaviors. \\ \cline{2-5}  & & & & - Segment the customers according to their behaviors for improving sales. \\ \cline{2-5}  & & & & - Segment the customers according to their behaviors for improving sales. \\ \cline{2-5}  & & & & - Segment the customers according to their purchasing behaviors. \\ \hline \multirow{6}{*}{Banking} & \multirow{2}{*}{2021 [8]} & \multirow{2}{*}{RFM model} & \multirow{2}{*}{RFM score} & \multicolumn{2}{c}{Customer segmentation} \\  & & & & - Segment the customer behaviors in banking activities in increasing bank average balances. \\ \cline{1-1} \cline{2-5}  & & & - Segment the customers to discover the customer’s transaction patterns in banking. \\ \hline \multirow{6}{*}{Insurance} & \multirow{2}{*}{2022 [10]} & \multirow{2}{*}{RFM model} & \multirow{2}{*}{RFM score} & \multicolumn{2}{c}{Policyholder segmentation} \\  & & & - Segment the policyholders according to their claiming patterns. \\ \cline{1-1} \cline{2-5}  & & & & - Segment the recommendation - Segment the clients according to their behaviors for the needs of the policy. \\ \cline{1-1} \cline{2-5}  & & & & - Segment the customer's transactions according to their purchasing behaviors. \\ \cline{1-1} \cline{2-5}  & & & & - Segment the customers according to their purchasing behaviors. \\ \hline \end{tabular}
\end{table} 
Table 1: Applications of behavioral segmentation in different domains. From Table 1, most of the behavioral analysis studies are using the RFM model, which is a cost-effective behavioral analysis model. The RFM model has been popularized by [PERSON] since 1994 [12; 13]. The metrics of RFM are vital indicators in measuring the customer lifetime value (CLV) in the customer's behaviors [14]. It was based on the marketing axiom of the Pareto Principle that \"80% of your sales come from 20% of your customers\" [15]. The usage of RFM analysis is for ranking the customers in terms of three quantifiable factors--recency (R), frequency (F), and monetary value (M)--and thus classifying them into homogeneous groups. It is a basic marketing strategy for the customer relationship management (CRC) process in most of the business [16]. Each component in the RFM model corresponds to distinct and significant characteristics of the customer. The most important component of the three RFM models is the recency of the customer, which is represented by the letter R in the RFM analytic alphabet [16]. The recency component refers to the gap of time since the customer's most recent interaction or transaction, which measures the time between the customers' analyzing and purchasing phases. The gap in time is typically measured in days or months. The greater the gap period, the lower the recency number.