Applications of web mining for marketing of online bookstores

Yeh, I-Cheng; Lien, Che-Hui; Ting, Tao-Ming; Liu, Chin-Hao

doi:10.1016/j.eswa.2009.02.068

Cited by 23 publications

(7 citation statements)

References 7 publications

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“…Opinions, for example, can be extracted from various web sources containing structured or unstructured text, such as customer written comments, blog posts or written feedback, in order to perform opinion mining (Liu, Zhao, Benkler & Xiao, 2006). The web content to be mined may also consist of images, audio or video data (Yeh, Lien, Ting & Liu, 2009). The visitors' web usage patterns and trends for e-commerce might also be predicted (Abraham & Ramos, 2003).…”

Section: Research Propostionsmentioning

confidence: 99%

Spotting The Elusive Prospect Customer: Exploratory Study Of A Web-Powered Customer Relationship Management Framework

Ertz

Graf

2015

JABR

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Research on how Web-Mining (WM) optimizes marketing, is sparse. Especially absent, is research on WM usefulness for Customer Relationship Management (CRM). The purpose of this research, is to propose a Web Mining-enabled knowledge acquisition framework for analytical CRM. An exploratory study consisting of eleven in-depth interviews with marketing scholars and practitioners revealed that, WM methods and techniques - currently available to practitioners - are well-suited for identifying the profile of web prospects according to their browsing behaviour and to classify them into homogeneous groups. Besides, the nascent technologies regarding opinion mining, sentiment analysis or natural language parsing, and which underlie WM, seem sufficient to acquire knowledge pertaining to attitudinal and other more psychometrically-based characteristics about web prospects. Such tools enable to better understand the so-often termed elusive prospects, by crafting fine-grained online marketing strategies to acquire those would-be customers. The authors discuss the managerial implications that derive from these findings.

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Section: Research Propostionsmentioning

confidence: 99%

Spotting The Elusive Prospect Customer: Exploratory Study Of A Web-Powered Customer Relationship Management Framework

Ertz

Graf

2015

JABR

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“…Each transaction t has a unique transaction ID and contains a subset of items in I; each X→Y rule is an implication where X, Y ⊆ I and X ∩ Y = 0 are defined. The set of X and Y items are called antecedent or left-hand-side (LHS) and consequent or right-hand-side (RHS) (Han & Kamber, 2006;Yeh, Lien, Ting, & Liu, 2009). Here, groups are considered as data items and each multi-membership is considered as a transaction.…”

Section: Figure 4 Identify Noises Based On Users' Similarity By Using...mentioning

confidence: 99%

Applying Personalized Recommendation for Social Network Marketing

Esmaeili

Nasiri

Minaei‐Bidgoli

2012

International Journal of Online Marketing

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The competition among manufacturers and service providing companies as well as the widespread presence of electronic processes has introduced new business models that need special e-Marketing. Social network marketing is one of the most recent types of marketing. Today, due to their flexibility and ease of use, social networks have fallen in the center of attention for users of various age groups. The variety of online social network groups, some of which are created with commercial goals, has made users uncertain and skeptical; on the other hand, in today’s competitive market, companies are seeking their potential and actual customers. To solve this problem, this paper introduced a group recommender system which, using data mining techniques and information theory, offers customized recommendations based on user preferences. Supposing that users in each group share similar characteristics, heterogeneous members are identified and removed. Unlike other methods, in special cases where the user does not have relationships with other members or when an activity history for the user does not exist, this method could yet offer recommendations.

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“…On the other hand, the degree of personalization that a Web site is able to offer in presenting its services to users represents an important attribute contributing to the site's success. The need for a Web site that understands the interests of its users is becoming a fundamental issue [39], [13], [38].…”

Section: Introductionmentioning

confidence: 99%

“…[39] Identifies potential customers of an online bookstore (case study www.nsc.gov.tw) through web content mining without using customer's transaction records and [13] illustrates a novel web usage mining approach, based on the sequence mining technique applied to user's navigation behaviour, to discover patterns in the navigation of websites. The case study used to illustrate the methodology is a very successful EC website soling soaps and skin care products in UK.…”

Section: Introductionmentioning

confidence: 99%