Customers are important intangible assets [1
] and sources of profits of the firms [5
]. As an important supplement to corporate financial indicators, customer equity (CE) and its derivative indicator, customer equity sustainability ratio (CESR), are measurements of the financial status of a firm’s customers and thus clearly reflect the future development trend and growth potential of the firm [6
]. Customer equity has thus become an important reference for investment decisions and this concept has established its important position in both the academic and industry field [7
Customer equity reflects the value of customers and is closely associated with the customer lifetime value (CLV). CLV refers to the net present value of profits that a customer can bring to a firm during his or her entire life of transactions with the firm [10
]. Customer equity is then defined as the sum of the lifetime value for all customers of the firm [2
]. Skiera, Bermes, and Horn [13
] further proposed the concept of customer equity sustainability ratio (CESR), which is defined as the ratio of a customer’s (or all customers’) future CLV (or CE) to the customer’s (or their) total CLV (or CE). The definitions of major concepts and their abbreviations are shown in Table A1
in the Appendix A
. Customer equity is a forward-looking indicator that measures the future profits generated by the customers and therefore it can provide a reference foundation for firms to allocate marketing resources and formulate value-based marketing strategies [1
]. Although customer equity plays an important role in terms of either the disclosure of stakeholder information [13
] or the allocation of marketing resources [1
], the accurate prediction of customer equity remains a difficulty in research [3
]. Many researchers have conducted in-depth studies and explorations of the measurement of customer equity under different scenarios using different data sources.
On the basis of previous research, this paper focuses on the measurement of customer equity for the scenario of mobile payment that has continued its global growth due to the development of mobile devices, Internet, and wireless communication technologies. China is experiencing rapid development of mobile payment and ranks among the top nations in the world in terms of both the transaction volume and the penetration rate. According to the data provided by the People’s Bank of China, China’s banking institutions handled 60.531 billion mobile payment transactions with a total amount of 277.39 trillion RMB in 2018. It is estimated that the number of mobile payment users in China will reach 790 million in 2020. With the rapid development of mobile payment, many third-party payment providers have sprout out, among which Wechat pay and Alipay are the main players. Under this circumstance, mobile payments aggregators have been established as a new business pattern in order to integrate different third-party payment methods and provide one-stop payment solutions for retailers. These platform-based aggregators can take full advantage of the network effect. Besides providing convenient and efficient payment solutions, these aggregators can also provide the retailers with derived services such as membership management and precision marketing since they have direct access to customer payment data. Predicting customer equity and customer equity sustainability ratio based on customer mobile payment data is very important for these mobile payments aggregators. One reason is that most income of these aggregators comes from a commission fee, which is 0.3% the amount of each mobile payment. Calculating customer equity and the customer equity sustainability ratio based on customers’ mobile payment data helps to assess the future development of these aggregators. The other reason is that calculating customer equity and customer equity sustainability ratio also helps the retailers, i.e., the clients of these mobile payments aggregators, to better understand the value generated from their customers who are using mobile payment and thus helps to make marketing and promotion decisions. Therefore these payment aggregators can generate a service fee from their clients and it is gradually becoming an important source of income for these aggregators. We can see that predicting customer equity and customer equity sustainability ratio is an essential task for these mobile payments aggregators.
Mobile payment has been well accepted in brick-and-mortar stores. Shoppers can use their mobile devices to scan the code and make a payment. This new payment method begun in 2015 and has become the most popular payment method in brick-and-mortar stores. According to Payment and Clearing Association of China, 89.1% of shoppers embraced this new payment method in 2018. The rapid development can be explained from both sides of the retailers and the consumers. From the retailers’ perspective, there are four reasons: firstly, mobile payment is faster than credit card and cash payment, helping retailers to improve their customer services; secondly, using mobile payment helps brick-and-mortar retailers attract a large number of existing Wechat pay and Alipay users in online payment scenarios; thirdly, the commission fee on each mobile payment is 0.3%, however the commission fee on each credit card payment is 1%; lastly, mobile payment offers offline retailers new communication channels and opportunities for personalized marketing. From the consumers’ perspective, firstly, mobile payment is easy to use, especially for those who have already got used to Wechat pay or Alipay for an online payment; secondly, mobile payment is good to use, on the one hand it is more convenient than paying by cash or credit card, and on the other hand, the retailers offered preferential treatment to the consumers using a mobile payment at the early stage of promotion; lastly, imitating other shoppers at the cashier’s also contribute to the rapid development of this new payment method. Due to these above reasons, it took only three years for the mobile payment to become popular in brick-and-mortar stores.
The development and popularization of mobile payment in brick-and-mortar stores can be seen as a diffusion process of a new technology. Consumers are different in technology acceptance. Segmenting consumers based on their acceptance of new technology and understanding their behavior is more and more important in today’s fast-paced and technology-driven world. Therefore, in this paper we use the Bass diffusion model [15
] to estimate the potential number of customers of a retailer and group these customers according to their first-time adoption of mobile payment in brick-and-mortar stores. On the basis of customer segmentation, a Pareto/NBD (Negative Binomial Distribution) model [16
] is used to describe customer behavior and estimate the customer retention rate. This paper thus proposes a method of measuring customer equity under the scenario of mobile payment by combining the Bass diffusion model and Pareto/NBD model. In this paper, we conduct an empirical study using data from one of the leading mobile payments aggregator in China. These data are customer mobile payment data of an offline retailer from May 2016 to May 2018. This period covers the whole diffusion process of mobile payment in brick-and-mortar stores in China, which started in late 2015 and popularized in 2018. The gradual adoption of mobile payments by customers during the 25 months can be seen as the diffusion of a new technology, we therefore calculate customer equity of the mobile payments aggregator generated from this specific retailer using the Bass diffusion model and Pareto/NBD model. First, we use the Bass model to estimate the potential customer number and group customers into five categories including innovators, early adopters, early majorities, late majorities, and laggards according to their first-time adoption of mobile payment. Second, the Pareto/NBD model is used to estimate the use frequency and retention rate of each customer category. Finally, the customer equity and customer equity sustainability ratio for each customer category is calculated and the overall customer equity of the mobile payments aggregator generated from this specific retailer is obtained by summing up the customer equity of each customer category.
The paper is organized as follows. Section 2
presents a literature review of customer equity modeling approaches, especially the measurement of customer equity based on a diffusion model. Section 3
introduces the theoretical models of this paper. Section 4
presents the research methodology and research framework. Section 5
presents empirical research and analysis results. Section 6
outlines the managerial relevance of the study and summarizes the contributions of the paper.
6. Managerial Relevance and Conclusions
As the marketing theory and practice becoming more and more customer-centered, customers and relationships with customers are treated as vital intangible firm assets, which should be measured and managed. Customer equity (CE) is an essential metric to measure customer based assets and it can further provide a new tool for firm valuation instead of financial-based valuation. Compared with traditional financial-valuation, the customer-based firm valuation method is more precise and more accountable especially for today’s loyalty economy. The reason is that customer equity is a forward-looking metric, which means that it not only considers the profit that has been already generated by the customers but also takes customer’s future profit potential into consideration. Besides being a metric to assess firm’s underlying value, customer equity also works as an important base for customer-centric marketing practice. According to customer equity, managers are able to identify their most profitable customers and those unprofitable ones. Therefore, calculating customer equity provides managers a reference standard to allocate marketing resource and make strategic marketing decisions in order to increase future profits.
With the managerial importance, the calculation of customer equity and its derivative concept, customer equity sustainability ratio, is being discussed more than ever before. In this paper, we focused on the calculation of customer equity of a mobile payments aggregator. With the rapid development of mobile payment in China, mobile payments aggregator, as a new business pattern, helps to connect the retailers with different third-party payment firms, thus providing one-stop payment solutions for retailers. Calculating customer equity of these mobile payments aggregators is very important due to two reasons. The first reason is that customer equity helps to assess the future development potential of these aggregators that are emerging business patterns with the recent development of mobile payment. The second reason is that customer equity helps the retailers, i.e., clients of these mobile payments aggregators, to better understand the buying behavior and the value generated from the customers who are using mobile payment. Therefore the mobile payments aggregators are able to provide their clients with value added services and help the retailers make customer-centered marketing and promotion decisions. Generating a service fee from the retailers has gradually become an importance source of income besides the commission fee. Measuring customer equity of the mobile payments aggregator generated from a specific retailer is of great importance since it not only helps the aggregator evaluate its future business development but also provide value-added service and generate a service fee from the retailer. The main purpose of this paper was to calculate customer equity of a mobile payments aggregator generated from a specific retailer from the perspective of technology diffusion. The proposed method could contribute to the literature in two ways.
First, we used the Pareto/NBD model to estimate the retention rate. In the current literature, customer equity measurement using diffusion models usually adopts an aggregate-level approach, which means the retention rate is regarded as an exogenous variable and can be obtained from annual reports, related literature, or industry experts. Compared with taking the retention rate as an exogenous variable, estimating retention using a Pareto/NBD model based on individual transaction data is more appropriate in measuring customer equity in noncontractual settings such as retailing.
Second, unlike the aggregate-level approaches of modeling customers as a whole, this paper proposed an operable customer equity measurement model based on customer segmentation, thus reducing the measurement error caused by the heterogeneity of customer groups. Although some scholars have proposed that customer equity should be calculated according to different customer segmentations, there is still relatively little discussion on specific implementation methods. In this paper, customers are segmented into five categories, i.e., innovators, early adopters, early majorities, late majorities, and laggards, according to their adoption time of mobile payment. Customer segmentation is usually based on demographic or psychographic characteristics. However, in this paper, we proposed using the adoption time of mobile payment as customer segmentation criteria. This is more appropriate because customer equity of this mobile payments aggregator generated from the specific retailer comes from the commission fee of each transaction, which is directly connected with customers’ mobile payment behavior, meaning that customers with different adoption time of mobile payment will contribute differently to customer equity. The result shows that customer equity of the early adopters and the early majorities are more than those of the other three categories and the customer equity sustainability ratio of these two categories are respectively 98.06 and 98.18%, indicating much room for future profit growth. The customer equity sustainability ratio of innovators was only 35.04%, indicating limited room for future profit growth, despite their early adoption of new technologies. Firms should increase marketing efforts to maintain relations with early adopters and early majorities. Our method helps the firm to identify and target these customers in marketing, such as distributing coupons, giving more shopping points or higher discounts. In the meanwhile, firms should reduce marketing investments for the innovators and late majorities since their growth potential is relatively lower. By doing this, firms are able to allocate their marketing resources more appropriately and make their marketing investment more effective. Besides, our study also helps the mobile payments aggregator to choose the most valuable market to target when promoting a new technology-based service, such as face-scan payment, E-card, or electronic discount coupon. Our study segmented customers according to their new technology acceptance degree and this segmentation criteria is becoming more and more important when new technologies are emerging in an endless stream. The empirical research shows that although innovators accept a new technology very quickly, their future profit potential is quite limited. According to our study, it is the early adopters and the early majorities that are the most valuable customer segments the payment aggregator should really target when promoting new technology-based services.
Although our study focuses on the customer equity measurement of a mobile payments aggregator, this calculation method also works for other aggregators with similar business logic and profit model, such as health care and medical aggregator Apps like Apple Healthkit, smart home aggregator Apps like Apple Homekit, and cloud service aggregator like Tencent Cloud. These aggregator apps act as platforms connecting the product or service providers on the one side and their clients on the other. Like mobile payments aggregators, these aggregators also have direct access to consumer data. Based on consumer data, our study provided a method to segment customers according to their technology adoption and then further calculated customer equity generated by each segment. This helps the aggregator to target the most profitable customers when promoting a new technology-based service. In future research, we could apply the proposed method to segment customers and calculate customer equity and customer equity sustainability ratio based on technology diffusion model for these aggregators, verifying that early adopters and early majorities are the categories that will generate most profit in the future.
Our study developed a method to calculate customer equity of a mobile payments aggregator based on the technology diffusion model. However, the customer equity we calculated was only a small part of a whole picture, which means in this study we only focused on the customer equity generated from one specific retailer. The adoption time of mobile payment and customer segmentation were subject to the payment data of this retailer. Although the research could help this specific retailer to better understand its customers and making relevant marketing strategies based on customer future potentials, it was not enough to get a whole picture of the development potentials of the mobile payments aggregator since it had many other retailers as its clients. In order to overcome this limitation and calculate total customer equity, in future research, the customer payment data of this aggregator could be restructured as customer-centered instead of retailer-centered, which means merging an individual customer’s payment records in different retailers according to his or her payment ID. Then we can identify innovators, early adopters, early majorities, and late majorities in a more general level. We can thus not only calculate the total customer equity of the payment aggregator but also provide its clients, i.e., the retailers, with more customer information by comparing customer equity generated from one specific retailer and total customer equity generated from all the retailers.