The Purchasing Behavior Analysis of B2B Customer - Take a Pharmaceutical Company as example
Date Issued
2010
Date
2010
Author(s)
Wang, Lan
Abstract
More and more B2B companies have begun thinking about how to understand their customers deeply, and provide more products and services to meet their needs. By doing this, they can not only increase profits, but also build long-term relationship with customers.
Through the creation of database, companies can control cost structure and the inventory; but how to get effective information from the database to help understanding the demands of market and customers’ potential behavior are really testing the companies’ marketing knowledge. This research focuses on the issue, using the Hierarchical Bayesian Statistical Model to analyze the database and find out the customers’ purchasing behavior.
In order to explore the relevance of inter-purchase time, product price and purchase quantity, the HB method is used to build the model and parameters are estimated by Markov Chain - Monte Carlo method. Besides, the actual transaction records are divided into four major categories to analyze and the customer segmentations are also analyzed in the overall layer.
As the result, some customers have significant behaviors consistent with the assumptions in the oral and external category, and the customers with B class rating in credit are more significant than others. In the future, I believe that the marketing strategy and relationship based on the results would be more useful and effective.
Through the creation of database, companies can control cost structure and the inventory; but how to get effective information from the database to help understanding the demands of market and customers’ potential behavior are really testing the companies’ marketing knowledge. This research focuses on the issue, using the Hierarchical Bayesian Statistical Model to analyze the database and find out the customers’ purchasing behavior.
In order to explore the relevance of inter-purchase time, product price and purchase quantity, the HB method is used to build the model and parameters are estimated by Markov Chain - Monte Carlo method. Besides, the actual transaction records are divided into four major categories to analyze and the customer segmentations are also analyzed in the overall layer.
As the result, some customers have significant behaviors consistent with the assumptions in the oral and external category, and the customers with B class rating in credit are more significant than others. In the future, I believe that the marketing strategy and relationship based on the results would be more useful and effective.
Subjects
Database Marketing
Hierarchical Bayesian Methodology
Purchasing Behavior Analysis
Type
thesis
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