Open AccessBusiness Rules Mining Using GUHA Method for the Personalization of Commercial Offers
Author(s) -
Stanislav Vojíř,
Zdeněk Smutný
Publication year - 2017
Publication title -
inžinerinė ekonomika
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.303
H-Index - 29
eISSN - 2029-5839
pISSN - 1392-2785
DOI - 10.5755/j01.ee.28.2.15767
Subject(s) - personalization , association rule learning , computer science , personalized marketing , lisp , business rule , world wide web , business process , database , data mining , data science , digital marketing , marketing , business , business to government , work in process , programming language , return on marketing investment
A shift from mass to personalized marketing, and thus also to personalized offers, brings firms an advantage for building customer relationships. The article introduces an artefact in the form of a method for creating personalized offers, focused on companies engaged in e-commerce. This method is based on mining association rules using the GUHA method. The association rules are converted into business rules and then combined with other manually defined business rules. The application of the method in practice is illustrated on customers' data from the e-shop of a company doing business in navigation systems, for the purpose of selecting personalized offers for an e-mailing campaign. The practical illustration uses a combination of the data mining system LISp-Miner and the business rule system JBoss Drools, which are freely available tools. The advantages and limitations of the proposed method, in connection with creating personalized marketing strategies in e-commerce, are discussed. The purpose of this practically oriented article is to address marketing and account managers and the issues connected with the personalization of marketing activities