Cross-buying refers to the customer action of buying additional products and/or services from the same provider (Valentin 2004). With the belief that cross-buying enables firms to increase profit from existing customers, firms have steadily placed greater emphasis on cross-selling strategies for profitability. To date, numerous studies show that cross-buying behavior of customers has a positive effect on firm profitability. Business reality, however, offers a different perspective; namely, that high levels of cross-buying may not always be linked to firm profitability. For example, Best Buy (an electronics retailer in the United States) has identified approximately 20% of its customers as unprofitable in spite of them purchasing multiple items (McWilliams 2004). Shah, Kumar, Qu, and Chen (2012) found that customers who persistently exhibit certain types of behavior (e.g., excessive service requests, high levels of returning products, lower levels of revenue growth, promotion maximizers) are unprofitable even though they purchased more than one product category.The aforementioned research implies that cross-buying can exert a negative impact on profitability, thereby calling for further examination of cross-buying behavior. It is conceivable that a repeated purchase propensity (contrasted with a cross-buying propensity) concentrated on a single brand is more profitable. Therefore, our primary objective in this paper is to identify a more beneficial type of customer among those who tend to patronize a limited number of brands versus those who tend to patronize a variety of brands, using a one-dimensional model (brand dispersion index). In addition, the second goal of this research is to investigate the boundary conditions where cross-buying will not lead to an increase in sales (unprofitable cross-buying conditions). As two moderating factors that weaken a customer’s crossbuying propensity and a firm’s sales (frequency and transaction size of firms), we consider (1) promotion dependency and (2) spending limiter condition. We use transaction data that include partners in various industries such as gasoline stations, convenience stores, banks, restaurants, and online shopping malls, covering forty-seven categories. Because multiple partners in many categories are available, this allows us to study whether a customer’s cross-buying level in the current period (t) affects the customer’s purchase frequency and transaction size in the subsequent period (t+1). The observation period for the data set extends over three years. Findings from this study indicate that a high level of cross-buying at period t has a positive impact on increasing customer frequencies and transaction sizes in the subsequent (t+1) period. This means that cross-buying has the potential to increase the firm’s profitability. Customers who show a high level of cross-buying propensity tend to exhibit higher levels of loyalty than customers who concentrated on limited brands. Firms should find ways to induce customers with low cross-buying propensity to increase crossbuying. Regarding moderating effects, promotion dependency and spending growth (decline vs. stagnation), spending growth has a considerable moderating effect on the relationship between cross-buying propensity and a customer’s transaction size. Specifically, the effect of cross-buying on transaction size weakens when spending is shrinking. This result makes an important contribution to cross-buying research. If customers showing a high level of cross-buying do not increase their spending level, they may be merely switching to other brands in the program under a fixed budget. So while the rate of crossbuying seems to increase, profit might not increase. The findings from this study imply that it is crucial to target and motivate customers who tend to use various brands and contribute to sales to do more cross-buying instead of suggesting cross-buying to random customers. The promotion dependency, however, turns out to not have significant moderating effects on the relationship between the customer’s propensity to cross-buying and the customer’s purchase frequency and transaction size. For marketing purposes, it is important to consider which customers are more profitable among those who tend to do cross-buying among multi-brands versus those who tend to purchase repeatedly in a limited number of brands. This research provides a solution with a one-dimensional index, the brand dispersion index. Whether cross-buying is shown to be a positive or negative impact on sales, the results are meaningful in implementing customer relationship management. Regardless of the direction in the level of crossbuying, both directions provide a solution to allocate marketing resources. For instance, if the propensity for cross-buying increases sales, the firm should implement marketing strategies to encourage people to use a variety of brands by adding new brands. If repeat purchases increase sales, the company should concentrate on certain brands that customers use most frequently. In addition, by finding the conditions that do not increase sales (e.g., spending limiter condition), it makes marketing practitioners think that cross-buying does not always bring positive results. Overall, the findings from this study are that it is crucial to motivate and target customers who tend to use various brands and contribute to sales to do crossbuying activity, instead of promoting cross-buying to random customers. Conceptual Framework Figure 1 provides an overview of our framework for the relationship between brand dispersion and visiting frequency and transaction size of customers. Specifically, we hypothesize how customer frequencies and transaction sizes in time t+1 will be influenced by customer brand dispersion levels (the extent that customer transactions occur across a broad range of brands) in time t. In addition, we examine the moderating influence of two customer specific variables: (1) degree of promotion dependency and (2) spending limits.