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Application of Marketing Intelligence Among Green Banking and Geographical Indicator Products Attain Elevated Consumer Experience: a Distributor Marketing Intelligence System Approach

EasyChair Preprint 5858

10 pagesDate: June 23, 2021

Abstract

Nowadays, the global competitive environment deals with the quality products so they can attract their consumers and also they can differentiate their products from others adopting marketing intelligence. A Geographical Indication (GI) is a name or sign used on products which corresponds to a specific geographical location or origin. In this paper, we investigate about the consumerexpedience impact on the purchase decision in green banking after consuming the Geographical Indication Products. When it’s coming to the purchasing behaviour of a consumer may depends on various factors that may influence the decision making process such as physical pleasure, income effect, price effect, reference group, culture code, social class, choice of a product, brand and dealer or store, purchase timing and amount, perception, and post purchase behaviour, etc., All factors are dependent on each other and influence the decision making process of a consumer. But the purchasing of the geographical indication is made by the consumer by their locality, tourism places, obtain information from different sources, have different perceptions, have differing satisfaction levels related to past experience, etc., Thus the purchase decision is dependent on many factors. These factors may be specifically related to distributor marketing intelligence system.

Keyphrases: Culture code, GI, Green Banking, Marketing Intelligence, consumer experience, distributor marketing intelligence system

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:5858,
  author    = {V Kalyani},
  title     = {Application of Marketing Intelligence Among Green Banking and Geographical Indicator Products Attain Elevated Consumer Experience: a Distributor Marketing Intelligence System Approach},
  howpublished = {EasyChair Preprint 5858},
  year      = {EasyChair, 2021}}
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