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Do managers know what their customers think and why?

  • Original Empirical Research
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Abstract

The ability of a firm’s managers to understand how its customers view the firm’s offerings and the drivers of those customer perceptions is fundamental in determining the success of marketing efforts. We investigate the extent to which managers’ perceptions of the levels and drivers of their customers’ satisfaction and loyalty align with that of their actual customers (along with customers’ expectations, quality, value, and complaints). From 70,000 American Customer Satisfaction Index (ACSI) customer surveys and 1068 firm (manager) responses from the ACSI-measured companies, our analyses suggest that managers generally fail to understand their firms’ customers in two important ways. First, managers systematically overestimate the levels of customer satisfaction and attitudinal loyalty, as well as the levels of key antecedent constructs such as expectations and perceived value. Second, managers’ understanding of the drivers of their customers’ satisfaction and loyalty are disconnected from those of their actual customers. Among the most significant “disconnects,” managers underestimate the importance of customer perceptions of quality in driving their satisfaction and of satisfaction in driving customers’ loyalty and complaint behavior. Our results indicate that firms must do more to ensure that managers understand how their customers perceive the firm’s products and services and why.

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Notes

  1. Consumers surveyed by the ACSI are asked questions with regard to a specific product/service brand rather than the company marketing the brand (where these are different). These named brands are the largest that a company will sell in that specific marketplace. In many cases, companies have only one brand in that marketplace, or one major brand that most consumers will have experienced. However, as a robustness check we compared our results for the whole sample with those for the subset of companies in our sample marketing only one brand in the same ACSI industry and did not find any significant differences.

  2. As a robustness check we also examined the impact of using 2010 ACSI consumer data, and the conclusions of the analyses remain largely unchanged. This is not surprising, as company-level ACSI satisfaction results tend to exhibit a significant amount of autocorrelation.

  3. The standard ACSI structural model typically includes a 14th survey item, a question regarding price tolerance/reservation price included in the customer loyalty latent variable. This question asks the respondent to indicate how much the company could raise the price of the product/service/brand experienced before he or she would definitely defect to a competitor. During questionnaire design and pre-testing with academics and managers, it was determined that this question would be too difficult to meaningfully adapt to the marketing manager questionnaire, and it was therefore excluded from both samples.

  4. As part of the qualification/eligibility validation process, the responding managers were asked to respond to the statement, “I have great knowledge of our company’s customers” using a 10-point Likert-type scale ranging from “strongly disagree” to “strongly agree.” Respondents reported an average score of 7.89 (standard deviation = 1.82). In all of the analysis that follows, we limited our sample of manager-respondents to only those who answered above average on the “knowledge of their company’s customers” question, i.e., scoring 8 or higher.

  5. One of the two variables for which this is not the case is the percentage of customers who have complained about their experiences with the firm’s products/services within the past 6 months. While the manager sample number is lower than that self-reported by customers, this is also a further indicator of a “rosy view” bias among managers.

References

  • Aksoy, L., Cooil, B., Groening, C., Keiningham, T. L., & Yalcin, A. (2008). The long term stock market valuation of customer satisfaction. Journal of Marketing, 72(July), 105–122.

    Article  Google Scholar 

  • Anderson, E. W., Fornell, C., & Mazvancheryl, S. K. (2004). Customer satisfaction and shareholder value. Journal of Marketing, 68(4), 172–185.

    Article  Google Scholar 

  • Anthony, R. N. (2007). Management control systems (12th ed.). New York: McGraw-Hill.

    Google Scholar 

  • Cassel, C., Hackl, P., & Westlund, A. (1999). Robustness of partial least squares method for estimating latent variable quality structures. Journal of Applied Statistics, 26(4), 435–446.

    Article  Google Scholar 

  • Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295–336). Mahway: Lawrence Erlbaum Associates.

    Google Scholar 

  • Chinader, K. R., & Schweitzer, M. E. (2003). The input bias: the misuse of input information in judgment of outcomes. Organizational Behavior and Human Decision Processes, 91(2), 243–254.

    Article  Google Scholar 

  • Clark, T., Key, T. M., Hodis, M., & Rajaratnam, D. (2014). The intellectual ecology of mainstream marketing research: an inquiry into the place of marketing in the family of business disciplines. Journal of the Academy of Marketing Science, 42(3), 223–241.

    Article  Google Scholar 

  • Compeau, D. R., & Higgins, C. A. (1995). Application of social cognitive theory to training for computer skills. Information Systems Research, 6(2), 118–143.

    Article  Google Scholar 

  • Dotson, J., & Allenby, G. (2010). Investigating the strategic influence of customer and employee satisfaction on firm financial performance. Marketing Science, 29(5), 895–908.

    Article  Google Scholar 

  • Drucker, P. F. (1954). The practice of management. New York: Harper & Brothers.

    Google Scholar 

  • Eberl, M. (2010). An application of PLS in multi-group analysis: The need for differentiated corporate-level marketing in the mobile communications industry. In V. E. Vinzi, W. W. Chin, J. Henseler, & H. Wang (Eds.), Handbook of partial least squares: Concepts, methods and applications in marketing and related fields. New York: Springer.

    Google Scholar 

  • Feng, H., Morgan, N. A., & Rego, L. L. (2015). Marketing department power and firm performance. Journal of Marketing, 79(September), 1–20.

    Article  Google Scholar 

  • Fornell, C. (1992). A national customer satisfaction barometer: the Swedish experience. Journal of Marketing, 56(1), 6–21.

    Article  Google Scholar 

  • Fornell, C., & Bookstein, F. L. (1981). Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. Journal of Marketing Research, 19(4), 440–452.

    Article  Google Scholar 

  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 28(1), 39–50.

    Article  Google Scholar 

  • Fornell, C., Johnson, M. D., Anderson, E. W., Cha, J., & Bryant, B. E. (1996). The American customer satisfaction index: nature, purpose, and findings. Journal of Marketing, 60(4), 7–18.

    Article  Google Scholar 

  • Fornell, C., Mithas, S., Morgeson, F. V., & Krishnan, M. S. (2006). Customer satisfaction and stock prices: high returns, low risk. Journal of Marketing, 70(1), 3–14.

    Article  Google Scholar 

  • Fornell, C., Morgeson, F.V., & Hult, G.T.M. (2016). Stock returns on customer satisfaction do beat the market: gauging the effect of a marketing intangible. Journal of Marketing, 80(5), In Press.

  • Germann, F., Ebbes, P., & Grewal, R. (2015). The chief marketing officer matters. Journal of Marketing, 79(May), 1–22.

    Article  Google Scholar 

  • Gilin, D., Maddux, W. W., Carpenter, J., & Galinsky, A. D. (2013). When to use your head and when to use your heart: the differential value of perspective-taking versus empathy in competitive interactions. Personality and Social Psychology Bulletin, 39(1), 3–16.

    Article  Google Scholar 

  • Gruca, T. S., & Rego, L. L. (2005). Customer satisfaction, cash flow and shareholder value. Journal of Marketing, 69(3), 115–130.

    Article  Google Scholar 

  • Habel, J., & Klarmann, M. (2015). Customer reactions to downsizing: when and how is satisfaction affected? Journal of the Academy of Marketing Science, 43(6), 768–789.

    Article  Google Scholar 

  • Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3), 414–433.

    Article  Google Scholar 

  • Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2014). A primer on partial least squares structural equation modeling (1st ed.). Newbury Park: Sage Publications.

    Google Scholar 

  • Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (2nd ed.). Newbury Park: Sage Publications.

    Google Scholar 

  • Henseler, J., Ringle, C. M., & Sinkowics, R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20(1), 277–319.

    Google Scholar 

  • Hirschman, A. O. (1970). Exit, voice, and loyalty: Responses to decline in firms, organizations, and states. Cambridge: Harvard University Press.

    Google Scholar 

  • Homburg, C., Vomberg, A., Enke, M., & Grimm, P. H. (2015). The loss of the marketing department’s influence: is it really happening? and why worry? Journal of the Academy of Marketing Science, 43(1), 1–13.

    Article  Google Scholar 

  • Hulland, J., Ryan, M. J., & Rayner, R. K. (2010). Modeling customer satisfaction: A comparative performance evaluation of covariance structure analysis versus partial least squares. In V. E. Vinzi, W. W. Chin, J. Henseler, & H. Wang (Eds.), Handbook of partial least squares: Concepts, methods and applications in marketing and related fields. New York: Springer.

    Google Scholar 

  • Hult, G. T. M. (2011). Toward a theory of the boundary-spanning marketing organization and insights from 31 organization theories. Journal of the Academy of Marketing Science, 39(4), 509–536.

    Article  Google Scholar 

  • Hult, G. T. M., & Ketchen, D. J. (2001). Does market orientation matter?: a test of the relationship between positional advantage and performance. Strategic Management Journal, 22(9), 899–906.

    Article  Google Scholar 

  • Hult, G. T. M., Ketchen, D. J., & Slater, S. F. (2005). Market orientation and performance: an integration of disparate approaches. Strategic Management Journal, 26(12), 1173–1181.

    Article  Google Scholar 

  • Johnson, M. D., & Fornell, C. (1991). A framework for comparing customer satisfaction across individuals and product categories. Journal of Economic Psychology, 12(2), 267–286.

    Article  Google Scholar 

  • Johnson, M. D., Herrmann, A., & Gustafsson, A. (2002). Comparing customer satisfaction across industries and countries. Journal of Economic Psychology, 23(3), 749–769.

    Article  Google Scholar 

  • Kahneman, D., & Tversky, A. (1979). Prospect theory: an analysis of decision under risk. Econometrica, 47(2), 263–291.

    Article  Google Scholar 

  • Kristensen, K., & Eskildsen, J. (2010). Design of PLS-based satisfaction studies. In W. W. Chin, J. Henseler, & H. Wang (Eds.), Handbook of partial least squares. New York: Springer.

    Google Scholar 

  • Luo, X. (2007). Consumer negative voice and firm-idiosyncratic stock returns. Journal of Marketing, 71(3), 75–88.

    Article  Google Scholar 

  • Luo, X., & Homburg, C. (2008). Satisfaction, complaint, and the stock value gap. Journal of Marketing, 72(4), 29–43.

    Article  Google Scholar 

  • Mithas, S., & Rust, R. T. (2015). How information technology strategy and investments influence firm performance: conjectures and empirical evidence. MIS Quarterly, 40(1), 223–245.

    Google Scholar 

  • Morgan, N. A., & Rego, L. L. (2006). The value of different customer satisfaction and loyalty metrics in predicting business performance. Marketing Science, 25(5), 426–439.

    Article  Google Scholar 

  • Morgan, N. A., Anderson, E. A., & Mittal, V. (2005). Understanding firms’ customer satisfaction information usage. Journal of Marketing, 69(3), 131–151.

    Article  Google Scholar 

  • Morgeson, F. V., Sharma, P. N., & Hult, G. T. M. (2015). Cross-national differences in consumer satisfaction: mobile services in emerging and developed markets. Journal of International Marketing, 23(2), 1–24.

    Article  Google Scholar 

  • Narver, J. C., & Slater, S. F. (1990). The effect of a market orientation on business profitability. Journal of Marketing, 54(4), 20–35.

    Article  Google Scholar 

  • Oliver, R. L. (2010). Satisfaction: A behavioral perspective on the customer. London: ME Sharpe Incorporated.

    Google Scholar 

  • Parker, S. K., & Axtell, C. M. (2001). Seeing another viewpoint: antecedents and consequences of employee perspective taking. Academy of Management Journal, 44(6), 1085–1100.

    Article  Google Scholar 

  • Rigdon, E. E., Ringle, C., Sarstedt, M., & Gudergan, S. P. (2011). Assessing heterogeneity in customer satisfaction studies: across industry similarities and within industry differences. Advances in International Marketing, 22(1), 169–194.

    Article  Google Scholar 

  • Rust, R. T., Moorman, C., & Dickson, P. R. (2002). Getting return on quality: revenue expansion, cost reduction, or both? Journal of Marketing, 66(4), 7–24.

    Article  Google Scholar 

  • Schmenner, R. W., & Vollmann, T. E. (1994). Performance measures: gaps, false alarms, and the ‘usual suspects’. International Journal of Operations & Production Management, 14(12), 58–69.

    Article  Google Scholar 

  • Sleep, S., Bharadwaj, S., & Lam, S. K. (2015). Walking a tightrope: the joint impact of customer and within-firm boundary spanning activities and perceived customer satisfaction and team performance. Journal of the Academy of Marketing Science, 43(4), 472–489.

    Article  Google Scholar 

  • Srivastava, R. K., Shervani, T. A., & Fahey, L. (1999). Marketing, business processes, and shareholder value: an organizationally embedded view of marketing activities and the discipline of marketing. Journal of Marketing, 63(Special Issue), 168–179.

    Article  Google Scholar 

  • Tetlock, P. E. (2000). Cognitive biases and organizational correctives: do both disease and cure depend on the ideological beholder? Administrative Science Quarterly, 45(2), 293–326.

    Article  Google Scholar 

  • Tuli, K., & Bharadwaj, S. G. (2009). Customer satisfaction and stock returns risk. Journal of Marketing, 73(6), 184–197.

    Article  Google Scholar 

  • Varadarajan, R. (2010). Strategic marketing and marketing strategy: domain, definition, fundamental issues and foundational premises. Journal of the Academy of Marketing Science, 38(2), 119–140.

    Article  Google Scholar 

  • Vargo, S. L., & Lusch, R. F. (2016). Institutions and axioms: an extension and update of service-dominant logic. Journal of the Academy of Marketing Science, 44(1), 5–23.

    Article  Google Scholar 

  • Vavra, T. G. (2002). Customer satisfaction measurement simplified: a step-by-step guide for ISO 9001:2000 certification. Milwaukee: ASQ Press.

    Google Scholar 

  • Vilares, M. J., Almeida, M. H., & Coelho, P. S. (2010). Comparison of likelihood and PLS estimators for structural equation modeling: A simulation with customer satisfaction data. In V. E. Vinzi, W. W. Chin, J. Henseler, & H. Wang (Eds.), Handbook of partial least squares: Concepts, methods and applications in marketing and related fields. New York: Springer.

    Google Scholar 

  • Voorhees, C. M., Brady, M. K., Calantone, R. J., & Ramirez, E. (2016). Discriminant validity testing in marketing: an analysis, causes for concern, and proposed remedies. Journal of the Academy of Marketing Science, 44(1), 119–134.

    Article  Google Scholar 

  • Vorhies, D. W., & Morgan, N. A. (2005). Benchmarking marketing capabilities for sustainable competitive advantage. Journal of Marketing, 69(1), 80–94.

    Article  Google Scholar 

  • Watson, G. F., Beck, J. T., Henderson, C. M., & Palmatier, R. W. (2015). Building, measuring, and profiting from customer loyalty. Journal of the Academy of Marketing Science, 43(6), 790–825.

    Article  Google Scholar 

  • Wetzel, M., Odekerken-Schroder, G., & Van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical constructs models: guidelines and empirical illustration. MIS Quarterly, 33(1), 177–195.

    Google Scholar 

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Correspondence to G. Tomas M. Hult.

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Constantine Katsikeas served as Area Editor for this article.

Appendices

Appendix 1

Table 8

Table 8 Survey items, item wording, and scale

Appendix 2

Table 9

Table 9 Companies included in sample

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Hult, G.T.M., Morgeson, F.V., Morgan, N.A. et al. Do managers know what their customers think and why?. J. of the Acad. Mark. Sci. 45, 37–54 (2017). https://doi.org/10.1007/s11747-016-0487-4

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