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The Development of a Response-Function for Customer Relationship Marketing

Author

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  • Michael Toedt

    (University of Riga, Latvia and University of Applied Sciences Kufstein, Austria)

Abstract

The paper focuses on the effect of communication on the sales performance within CRM. The paper uses the hotel business as an example to evaluate if communication within Customer Relationship Management creates loyalty measured by the re-purchase behavior of existing hotel guests. The re-purchase behavior is regarded in the paper as the final outcome of loyalty. The research evaluates the reaction of message receivers who are already customers, which means the receivers know the advertised products and services. Therefore the author assumed that learning effects are not necessary within CRM which leads to the conclusion that an advertising response function for the communication with existing customers should be concave instead of s-shaped. S-shaped response functions are used in many articles to describe the effects of marketing actions.To prove the hypothesis the author conducted a quantitative research over a time period of 4.5 years where all marketing and booking transactions of four hotels in Germany were monitored. Due to the fact that hotels are characterized by moderate marketing budgets and brand awareness levels the result of the research should be applicable especially for small and medium enterprises (SME?s).The data analysis approved a direct correlation between communication and the sales performance of the hotels. For the first time it was possible to define a response function for CRM, which is a concave increasing function. This new knowledge should stimulate manager to adapt their existing communication strategy and should be used as a basis for further research.

Suggested Citation

  • Michael Toedt, 2014. "The Development of a Response-Function for Customer Relationship Marketing," Proceedings of International Academic Conferences 0100789, International Institute of Social and Economic Sciences.
  • Handle: RePEc:sek:iacpro:0100789
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    File URL: https://iises.net/proceedings/9th-international-academic-conference-istanbul/table-of-content/detail?cid=1&iid=129&rid=789
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    Cited by:

    1. Dario Dunkovi? & Antonia Petravi? Cili, 2017. "Retailer pricing strategy: diffuse coupons effects contingent on store format," Proceedings of Business and Management Conferences 5207242, International Institute of Social and Economic Sciences.

    More about this item

    Keywords

    Response Function; CRM; Communication; Learning Effects;
    All these keywords.

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism
    • M30 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - General

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