The role of content marketing in enhancing customer loyalty: an empirical study on private hospitals in Saudi Arabia

  • Received July 10, 2019;
    Accepted September 12, 2019;
    Published September 24, 2019
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/im.15(3).2019.06
  • Article Info
    Volume 15 2019, Issue #3, pp. 71-84
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This work is licensed under a Creative Commons Attribution 4.0 International License

Due to increasing competition in the private hospital sector in Saudi Arabia, the organizations need to adopt the new ways to foster the brand loyalty and repeated visits. In this context, content marketing may have pleasant effects on a business in terms of customer engagement, trust and loyalty. The present research attempts to investigate the multi-dimensional relationships among content marketing, loyalty, trust and customer engagement in the private hospital sector using primary data collected through a questionnaire from 400 randomly selected respondents. A simple random sampling technique is utilized to select the patients or their family members visiting the private hospital to have their perception regarding hypothesized variables. The findings indicate that content marketing has a positive impact on the factors like customer engagement, trust and loyalty. In comparison, content marketing is found more effective in persuading the loyalty of the customers in comparison of trust and loyalty. Further, the customers’ trust towards a brand has a strong positive relationship with the loyalty. Moreover, the positive effect of customer engagement on the trust has also been found. Based on the results, this study suggests that the private healthcare institutions should adopt a multi-channel content marketing approach to exploit its maximum benefit. Multiple social media platforms and popular healthcare blog sites should be chosen for an effective content marketing advertisement.

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    • Figure 1. Hypothesized relationship between content marketing, customer engagement, trust and loyalty
    • Figure 2. PLS model algorithm
    • Figure 3. PLS model bootstrapping
    • Table 1. Measurement scale of constructs
    • Table 2. Personal information of respondents
    • Table 3a. Reliability
    • Table 3b. Outer model loadings
    • Table 3c. Model fit
    • Table 4. Path coefficient-bootstrapping results
    • Table 5. Estimated coefficients