Employing marketing mix to increase the efficiency of CRM within organic products marketers in Jordan

  • Received May 9, 2019;
    Accepted June 11, 2019;
    Published June 25, 2019
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/im.15(2).2019.07
  • Article Info
    Volume 15 2019, Issue #2, pp. 84-95
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Marketing mix appeared to be one of the most influential approaches on the marketing plans in the organizations. The current study seeks to examine the influence of marketing mix (4Ps – promotion, price, place and product) on the efficiency of CRM (responsiveness, empathy, customer relations, assurance and reliability) within the organic products market in Jordan. The researcher employed the quantitative approach through distributing a questionnaire on total of 37 individuals who were involved in the marketing field of organic products. The results of the study indicated that marketing mix appeared to have an influence of the efficiency of CRM practices within the marketing of organic goods in Jordan. The most influential variable appeared to be the price, which is considered to be high for organic product in Jordan, and that is why customer tend to avoid such product. Following the price came the variable of product, which was important as customers tend to give much emphasis on the specifications of the product and the fact that it is healthy and organic tends to appeal them regardless of the price. The study recommended increasing the level of awareness regarding organic products marketing strategies among the marketing managers in Jordan.

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    • Figure 1. Model of the study
    • Table 1. Sample characteristics according to gender
    • Table 2. Sample characteristics according to experience
    • Table 3. Sample characteristics according to position
    • Table 4. Descriptive statistics of study variables
    • Table 5. Model summary
    • Table 6. ANOVA
    • Table 7. Model summary
    • Table 8. ANOVA
    • Table 9. Model summary
    • Table 10. ANOVA
    • Table 11. Model summary
    • Table 12. ANOVA
    • Table 13. Model summary
    • Table 14. ANOVA
    • Table 15. Model summary
    • Table 16. ANOVA
    • Table 17. Reliability statistics