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Pricing personal information of E-consumers
Abstract
With the emergence of precision marketing on B2C e-commerce platform, its foundation of
realization, personal information of E-consumers has become a hot data commodity. At the same
time, personal information trading platform is springing up all over the world, and the pricing
strategy is particularly important for the trading. However, in China, a mature pricing mechanism
has not yet been formed.
In this paper, on the basis of sorting out relevant research literature on data and information
product pricing at home and abroad, combining with the status quo of customer shopping
information trading and existing pricing strategies. The customer shopping information value model
under the B2C e-commerce platform based on the cost-plus pricing method was proposed, and the
Delphi method and the interview survey method were innovatively used to obtain expert opinions.
Based on this, entropy method and AHP are combined to determine the value weight of different
customer indicators, and then the scarcity index, information correlation value and information
immediacy value are introduced based on information rules and Gaussian function. On this basis,
the concept of data saturation was introduced by combining the logistic growth function, so as to
calculate the total number of samples needed when the K value was reached in different fields, and
then the value model of packets containing multiple personal shopping information was obtained
dynamically.
When B2C e-commerce platform sells customers' shopping information packet as data
commodity, its price should not be determined only according to its value. Combined with Philip
Kotler's pricing process, this paper divides the enterprise pricing process from a strategic perspective
into five steps: First, the pricing method is cost plus pricing. Then the market demand is estimated
by the demand elasticity function and the market life cycle. Next, combined with the customer
shopping information value model, other factors affecting pricing (market control policies, privacy
policies and externalities) are briefly described. Finally, how to implement and control the price is
explained.
In this paper, the customer shopping information pricing model under the B2C e-commerce
platform is proposed, which makes up the research gap to a certain extent and has certain academic
and theoretical significance. At the same time, the pricing model proposed in this paper can provide
reference for setting the pricing mechanism of shopping information trading platform for domestic
and foreign customers, which has certain practical and practical significance.
Key words: Customer shopping information, Data commodity, Pricing model.
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