Marketing Variables Predicting Customer Value in Empirical Environments

  1. Ana Pedreño Santos 1
  2. Maria Francisca Blasco 1
  3. Jesús García-Madariaga 1
  1. 1 Universidad Complutense de Madrid
    info

    Universidad Complutense de Madrid

    Madrid, España

    ROR 02p0gd045

Libro:
EBOR Conference Abstract Book

Editorial: EBOR Academy Publishing House, Turkey

ISBN: 978-605-68816-6-4

Año de publicación: 2020

Páginas: 126

Tipo: Capítulo de Libro

Resumen

It is essential for a company to know how marketing variables affect customer value. It is necessary to be marketand customer oriented, and to improve efficiency in both attracting and retaining customers. But a comprehensive,integrated assessment of all marketing variables and their interdependencies is an arduous and complex task andthereby, an unsettled issue.This study proposes a customer value management model based in the analysis of empirical studies.There is amanagerial demand for business researchers of doing a transformation from theory to practice, and not allmarketing variables have being studied from a value point of view. The aim of this work is to give a tool formanagers and researchers to work on the variables with a global vision and understand the relationships betweenmarketing variables and its impact in customer value. The model simplifies the task of finding information of theeffects produced using certain marketing variables, in order to work together acquisition and retention areas andpredicting what their possible results of implemented marketing actions will be.The marketing variables found out empirically as value predictors are: brand reputation, point of sale, price,discounts, product complementarity, experiences, emotions, perceived value, satisfaction, quality, switching costs,termination fee commitment and loyalty. The model incorporates the relationship between each variable withretention and with customer value as well as the relationships between them.The results show that customer value for the company is necessarily achieved through customer lifetime and thatthere are four clear predictors to customer lifetime: perceived value, purchase intention, satisfaction and switchingcosts.

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