Identifying customer priority for new products in target marketing: Using RFM model and TextRank
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DOIhttp://dx.doi.org/10.21511/im.17(2).2021.12
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Article InfoVolume 17 2021, Issue #2, pp. 125-136
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Target marketing is a key strategy used to increase the revenue. Among many methods that identify prospective customers, the recency, frequency, monetary value (RFM) model is considered the most accurate. However, no RFM study has focused on prospects for new product launches. This study addresses this gap by using website access data to identify prospects for new products, thereby extending RFM models to include website-specific weights. An RF model, built using frequency and recency information from website access data of customers, and an RwF model, built by adding website weights to frequency of access, were developed. A TextRank algorithm was used to analyze weights for each website based on the access frequency, thus defining the weights in the RwF model. South Korean mobile users’ website access data between May 1 and July 31, 2020 were used to validate the models. Through a significant lift curve, the results indicate that the models are highly effective in prioritizing customers for target marketing of new products. In particular, the RwF model, reflecting website-specific weights, showed a customer response rate of more than 30% among the top 10% customers. The findings extend the RFM literature beyond purchase history and enable practitioners to find target customers without a purchase history.
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JEL Classification (Paper profile tab)C61, M31, M39
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References44
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Tables4
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Figures4
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- Figure 1. Conceptual framework to identify prospective customers
- Figure 2. Example of the difference in the website pages accessed by customers
- Figure 3. Cumulative lift chart of the RwF and RF models (R = recency; w = utility-weighted frequency; F = frequency)
- Figure 4. Cumulative distribution of website weight
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- Table 1. Partial website access data
- Table 2. RF value statistics
- Table 3. RwF values statistics
- Table 4. Performance results of the models
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Competitiveness of the information economy industry in Ukraine
Tetiana Ponomarenko
,
Veronika Khudolei ,
Olha Prokopenko ,
Janusz Klisinski
doi: http://dx.doi.org/10.21511/ppm.16(1).2018.08
Problems and Perspectives in Management Volume 16, 2018 Issue #1 pp. 85-95 Views: 2280 Downloads: 644 TO CITE АНОТАЦІЯInformation economy, being the newest type, in the course of formation acquires its distinctive features, which include a significant change in the needs of investors, producers, consumers and other economic relation participants. In order to achieve a competitive information economy, state support for high-tech industries is needed. It is crucial to create a clear legal framework, give boost to the formation of intellectual capital based on other countries' experience. Implementation of the strategy for high-tech industries development in Ukraine is a decisive step in creating a platform for information technology dissemination, creation of new competitive products with high added value. The purpose of the article is to investigate the transformation to the information economy, to analyze the industry competitiveness, to define the opportunities for information sphere improvement. The theoretical aspect of the emergence and formation of the information economy category is studied, the approaches to the defining this economic category and its derivatives have been studied and generalized, essential features of the information type of economic relations have been investigated, and their main components have been determined. In the article, the relationship between the level of information economy development and the competitiveness of domestic enterprises' products has been described, the factors influencing high-tech industries development in Ukraine are considered, and suggestions as for increasing the assistance to the development of knowledge-intensive sectors, including information technology, are proposed.
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Strategic pricing across the product’s sales cycle: a conceptualization
Establishing the initial price for a new product is one of the most important decisions a firm will make. Implementing and adjusting this price over the sales cycle of the new product are crucial decisions for both its short- and long-term success. A modification of the product life cycle (PLC) concept is presented to reflect one of the many alternative price-setting strategies available to the company. After justifying and illustrating the modified PLC pricing strategy, applications and limitations are presented and discussed.
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Impact of consumer innovativeness on risk and new product adoption: a moderating role of Indonesia’s demographic factors
Anna Triwijayati ,
Melany ,
Dian Wijayanti
doi: http://dx.doi.org/10.21511/im.16(4).2020.05
Consumer innovativeness is an important driver of economic progress and a country’s position in global competition. This study aims to examine the moderating effect of demographic factors of Indonesian consumers on the impact of consumer innovativeness on perceived risk and new product adoption. The type of research chosen is a causal comparative study by using online and offline survey methods. Data were obtained from a sample of 1,000 consumers from 31 provinces. The results showed that the demographic variable became a moderating variable for the impact of consumer innovativeness on new product adoption, but did not play a role in the influence of consumer innovativeness on credit-purchase risk perception. With regard to the influence of consumer innovativeness on credit-purchase risk perception, only social class has a significant effect as a moderating variable. As for the effect of consumer innovativeness on a new product adoption, the variables of marital status, occupation, income, and social class have significant effects. The social class variable consistently becomes a moderating one in both equations. The results of this study are useful for marketers to focus more specifically on their target markets, especially on the diffusion of new product innovations based on demographic characteristics.
Acknowledgment
PDUPT Research Grant by Ministry of Research and Technology of The Republic of Indonesia, 2019.
