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2011
Conference Paper
Title

Companies website optimising concerning consumer's searching for new products

Abstract
In this paper, we focus on consumer's needs for new products. Normally consumers search for these new products in internet by using a web search engine. They focus on websites of specific selected enterprises where they suppose the existence of such new products. Very often, consumers only get information from enterprise websites about existing products. However, these products do not fulfill consumer's needs for new products. Then, they probably request the enterprise hotline to ask for these new products. The manual response process is time und cost consuming. If we identify consumer's needs for new products by time then we easily can preview consumers search queries and their intention. With this information, we can support marketing professionals to optimize the enterprise website concerning consumer's searching for new product ideas. Therefore in this paper, we present a semi-automatically approach that firstly extracts consumer's needs for new products from the internet and that secondly compares these new product ideas with existing or future products from the enterprise. After company's decision to realize the new product ideas as product in future or not, the approach thirdly gives recommendation to marketing professionals for optimizing an enterprise website in a way that consumers find information about their new needs. This increases customer satisfaction and reduces expenditure of time and cost.
Author(s)
Thorleuchter, Dirk  
Fraunhofer-Institut für Naturwissenschaftlich-Technische Trendanalysen INT  
Poel, Dirk van den
Ghent University, Faculty of Economics and Business Administration
Mainwork
International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011. Proceedings. Vol.1  
Conference
International Conference on Uncertainty Reasoning and Knowledge Engineering 2011  
Open Access
File(s)
Download (191.02 KB)
Rights
Use according to copyright law
DOI
10.1109/URKE.2011.6007834
10.24406/publica-r-372918
Additional link
Full text
Language
English
Fraunhofer-Institut für Naturwissenschaftlich-Technische Trendanalysen INT  
Keyword(s)
  • web mining

  • text classification

  • text mining

  • knowledge discovery

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