Unfolding large-scale marketing data

Ho, Ying Chin; Chung, Yuho; Lau, Keith K.

doi:10.1016/j.ijresmar.2009.12.009

Cited by 11 publications

(11 citation statements)

References 14 publications

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“…Managers can use this big data application to dynamically adjust their advertising spending on the basis of the market response model they have developed. In addition, Ho et al (2010) describe a visual data mining tool for identifying core customers for representing the relationship between customer preferences and product and brand positioning in an understandable way by visualizing large marketing data sets on a map (see also Hariharan et al , 2015; Tirunillai and Tellis, 2014). From this, targeted advertising measures can be deduced.…”

Section: Resultsmentioning

confidence: 99%

The use of big data in corporate communication

Wiencierz

Röttger

2017

CCIJ

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Purpose The purpose of this paper is to illustrate the current state of research on the significance of big data in and for corporate communication and to introduce a framework which provides specific connecting points for future research. This is achieved by summarizing and reviewing the insights provided by relevant articles in the most significant scholarly journals. The paper also investigates trends in the literature. Design/methodology/approach On the basis of a systematic literature review, 53 key articles from 2010 to 2015 were further analyzed. Findings The literature review illustrates the potentialities of big data for corporate communication, especially with regard to the field of marketing communication. It also reveals a dramatic lack of research in the fields of public relations and internal communication with respect to big data applications. Research limitations/implications The online databases used in this paper comprised of refereed scientific journals with the highest impact factor in the respective disciplines. Journals with a lower impact factor and books were not included in the search process for this thematic analysis. Practical implications This paper provides a conceptual framework that describes four phases of strategic big data usage in corporate communication. The results show how big data is able to highlight stakeholders’ insights so that more effective communication strategies can be created. Originality/value This paper brings together previously disparate streams of work in the fields of communication science, marketing, and information systems with respect to big data applications in corporate communication. It represents the first attempt to undertake a systematic and comprehensive interdisciplinary overview of this kind.

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Section: Resultsmentioning

confidence: 99%

The use of big data in corporate communication

Wiencierz

Röttger

2017

CCIJ

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“…Bijmolt and Van de Velden [15] proposed an attribute-based perceptual mapping procedure with an idiosyncratic brand and attribute sets that alleviate some of these disadvantages. Finally, in recent years, researchers have used a wide range of alternative data sources for perceptual mapping, some of which may accommodate large sets of brands: e.g., transaction and customer network data [16] and product reviews [17].…”

Section: The Scaling Of Large Brand Setsmentioning

confidence: 99%

Adaptive Multidimensional Scaling: Brand Positioning Based on Decision Sets and Dissimilarity Judgments

Bijmolt

Wedel

DeSarbo

2020

Cust. Need. and Solut.

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Assessing market structure by deriving a brand positioning map and segmenting customers is essential for supporting brand-related marketing decisions. We propose adaptive multidimensional scaling (ADMDS) for simultaneously deriving a brand positioning map and market segments using customer data on cognitive decision sets and brand dissimilarities. In ADMDS, the judgment task is adapted to the individual customer where dissimilarity judgments are collected only for those brands within a customers’ awareness set. Thus, respondent fatigue and unfamiliarity with the brands are circumvented thereby improving the validity of the dissimilarity data obtained, as well as the multidimensional spatial structure derived from them. Estimation of the ADMDS model results in a spatial map in which the brands and derived segments of customers are jointly represented as points. The closer a brand is positioned to a segment’s ideal brand, the higher the probability that the brand is considered and chosen. An assumption underlying this model representation is that brands within a customers’ consideration set are relatively similar. In an experiment with 200 respondents and 4 product categories, this assumption is validated. We illustrate adaptive multidimensional scaling model on commercial data for 20 midsize car brands evaluated by 212 members of an on-line consumer panel. Potential applications of the method and future research opportunities are discussed.

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“…Offline data refers to the inventory, cost, and logistics information in e-commerce enterprises. (Wang, Feifei, & Li, Jing, 2012) 3.1.2 Data Preprocessing E-commerce enterprise's data is large size and high dimensional (Ying Ho, Yuho Chung, & Kinnam Lau, 2010, June) based on the big data. The raw data collected from each of the data sources probably exist missing values, repeat, incomplete, etc, which requires data preprocessing.…”

Section: Determining Data Sourcementioning

confidence: 99%

Research Intelligent Precision Marketing of E-commerce Based on the Big Data

Zhang¹,

Zhu²

2014

JMS

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This paper analyzed and summarized the development path of electronic commerce marketing based on the big data; the related aspects of intelligent precision marketing framework has been designed combined with smart technology; and describes its functional structure and operational processes. Taking into account the differences between e-commerce and traditional retail industry; constructed RFMA model combined with characterizes of the electricity suppliers, by means of k-means clustering to achieve the client's "precision" division. Finally, verified the model of marketing by a c2c transaction data, clarify this model could develop precise marketing strategies to deal with the challenges posed by big data has some significance.

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Unfolding large-scale marketing data

Cited by 11 publications

References 14 publications

The use of big data in corporate communication

The use of big data in corporate communication

Adaptive Multidimensional Scaling: Brand Positioning Based on Decision Sets and Dissimilarity Judgments

Research Intelligent Precision Marketing of E-commerce Based on the Big Data

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