2020 Volume 23 Issue 1

Management and Cultural Implications of Customer Satisfaction Differences for Help Desks in South America

Management and Cultural Implications of Customer Satisfaction Differences for Help Desks in South America

Guest Article: A quantitative study of customer satisfaction in six South American countries

In the current high technology markets, customer satisfaction is becoming a more and more significant aspect of business management. IT South America companies that provide products and services may be affected by the cultural and economic environments. This study examines measures of customer satisfaction in six countries within South America: Argentina, Brazil, Chile, Colombia, Peru, and Venezuela over the five-year period 2013 through 2017. The research question is whether or not these six countries have similar perceptions for customer satisfaction.

The first research question is whether or not satisfaction has similar meanings within the countries. If all six countries have similar meanings it would allow corporations with products and services in these countries to provide similar training programs and levels of service. If the satisfaction levels are different, then each country may need to have a different service strategy. The results of this study shows statistically that satisfaction is not the same across the six countries.

The second question is whether or not satisfaction measures are relatively consistent over the five-year period. In other words, should management monitor the changes in satisfaction perceptions within each country to see if they have changed or if they can assume the perceptions of satisfaction are the same each year. The results of the study show that statistically three of the countries have satisfaction levels that have consistent perceptions of satisfaction over the five-year period while three of the countries have satisfaction perceptions that change across the five-year period.

The study shows that there are no consistent drivers of overall satisfaction within the six countries and five-year time frame. However, the ability of the technician was the question that had the highest correlation with overall satisfaction most often for the five years across the six countries.

In general, the six major South American countries act very differently and should not be considered as homogeneous with respect to customer satisfaction for computer products or high technology medical equipment.

1. Introduction

For most companies, market dominance requires a well-organized product service organization. One stepping stone to dominance is to provide a level of Customer Satisfaction that meets or exceeds the customer expectations in each unique market. While Customer Satisfaction does not directly yield customer loyalty, it is usually considered one of the significant components. Since the high technology industry has such a short half-life and serious competition, high technology companies usually pay attention to support their products in order to assure customer satisfaction and ultimately, retention.

The use of help desks to improve Customer Satisfaction, especially in high technology companies, has been studied and found to be a major contributor to Overall Satisfaction and Loyalty. Help desks along with on-site service and depot repair are the three components that CompTIA (Computer Technology Industry Association) considers key to understanding the state of satisfaction in the high technology market.

With the advancement of technology, the complexity of the products and the ability to provide immediate response to equipment problems, the role of the help desk continues to take on greater roles. In many cases product problems are resolved directly through the capability of the help desk.

2. Research Hypotheses

The most direct questions were whether or not:

  1. The satisfaction with high technology products in South America was increasing,
  2. If Dissatisfaction was decreasing, and
  3. What were the factors that had the greatest influence?

These are the three major research hypotheses to be examined in this paper.

Hypothesis I: satisfaction characteristics are similar for the six countries. (The distribution of satisfaction scores will be the same for each country)

Hypothesis II: satisfaction measures are relatively constant over the five-year period of research. (The distribution of satisfaction scores will be the same over the five-year period for each country)

Hypothesis III: the drivers of Overall Satisfaction will be the same for the six countries.

3. The Study

Help desk is a term used to describe telephone support for customers from a company service facility in order to assist them in resolving problems. This study has been conducted to examine customer satisfaction for worldwide companies with operations in South America in the area of help desk services.

Key assumption and rationale for the key assumption

The most important assumption for this study is that service provided by help desk personnel is about the same for each of the companies and the measurements from each company can be considered to be on the same scale.

Each of the companies involved in the study used service level agreements (SLAs) to define the parameter limits for their help desk operations. These service performance parameters are consistently implemented in each country. Small differences, if any, between the companies in their SLAs will not have a significant impact on the customer’s perception of the Customer Satisfaction measurements of the help desk.

The rationale for this primary assumption of similar service by each company is also based on the following aspects of the study and why the data can be combined and compared:

  1. The study includes similar industries. Products offered by each company provide approximately the same level of complexity.
  2. For each company, the same measurement system has been used to measure Customer Satisfaction.
  3. The same survey company has taken all the measurements
  4. All satisfaction measurements were performed by telephone using personnel who spoke the local language in each country to reduce translation errors.

What Was Not Studied

There are still some limitations of the study that should be presented.

  • First, the data only covers a five-year period (2013 to 2017).
  • Second, even though there were more than five questions in this study, only the overall ranking question (Overall Satisfaction) was used to evaluate the null hypothesis for the first two research questions. While there is a great deal of correlation between individual questions, these correlations were not considered when testing the research hypotheses within this study.
  • Third, since each of these six countries are different in size, there may be neglected subcultural differences within each country that would impact perceptions of satisfaction. Although the questionnaire has set a consistent rule to evaluate the satisfaction, the differences resulting from these subcultural differences, if any, have been ignored.

All questions in the benchmark survey used a five-point Likert scale where one (1) was considered Very Dissatisfied and five (5) was considered Very Satisfied.

The values shown on the charts represent the average value of the “Overall Satisfaction” question. The same survey company (SERVICE 800, Inc., Minnesota) has taken all the measurements for the entire five-year period using the same survey instrument adapted to the local language for each country so that local idioms could be used to clarify the answers.

A final assumption is that cultural influence will be minimal since these products are technology based and all users have been trained by the product companies that are all multinational providing world-wide support. With this assumption is the complementary assumption that the Likert scale values will have similar (if not identical) interpretations in all six of the countries.

The arithmetic average was used to identify the performance of the help desks for each year. While statistically the arithmetic average is not considered appropriate as a valid measure, companies using the CompTIA benchmark identify with this measure and consider it useful and often rely on it to make strategic decisions (especially with respect to trending).

Note: Arithmetic averages were not used in any statistical test of significance in this paper.

There were several items that were not covered in this study. The benchmark program which has a history of over 20 years, has been limited to a review of the last 5 years. In order to test the research hypotheses the question “Overall Satisfaction” was used. Since the various companies had additional questions for their specific equipment, only the few questions that were consistent for all companies were used and the “Overall Satisfaction” question was used for the proposed hypothesis questions. Other questions in the survey were not considered in the hypotheses tests except some performance questions that were used to detect the drivers of Overall Satisfaction for each year. The questions that were used to detect the drivers excluded those unique questions used by some companies who added them to the base survey.

Since all the companies in the benchmark are multinational, it was assumed that all customers had approximately the same skill level for operating the equipment. In addition, it was assumed that all the customers had approximately the same level of training on the equipment. Since the sample sizes from each country in every year are generally in excess of 100 (with 3 exceptions), the use of the arithmetic average should be representative of the customer base. The actual sample size by country for each year is shown in table 1 following:

Table 1: Sample sizes by country and year

The computer company draws a random sample from all the service events completed by each company each week and is the source for the survey. The sample size is based on providing a minimum of 95 percent confidence for each metric in the benchmark.

4. Analysis

In order to understand the Customer Satisfaction characteristics of the six countries in South America a number of analyses were necessary. Descriptive statistics were used to determine the time characteristics (annual data) of satisfaction for the six countries. Regression analysis was applied to the arithmetic means of the Overall Satisfaction of each country over the five-year period. Although the underlying data is ordinal, regression analysis was used as an approximation. Given the large sample sizes, this approximation provides a reasonable representation. The chi-square nonparametric statistic was used to compare the response distributions of “Overall Satisfaction” for each country and the five-year data set. Correlation analysis was used to determine the strength of the relationships between the individual survey questions and the Overall Satisfaction question. The results of these analyses are shown below.

The following represents the arithmetic mean of the satisfaction scores by country and by year. 

Table 2: Arithmetic means by country and by year

This data is shown in the graph below by country.

Table 3: Graphic of the Arithmetic means by country and by year

An important observation of the arithmetic means shown in Table 3 indicates that most of the countries appear to have increasing levels of satisfaction over the five-year period 2013 through 2017.

The arithmetic average of all six countries was computed and compared to the Global Contact Center Satisfaction Index for the same time period (2013-2017). The arithmetic average used to represent South America is not weighted by sample, it provides a trend. Since the satisfaction scales on both charts shown below in Table 4 are different, the only purpose was to provide a general comparison of the two data sets.

Table 4: Average Satisfaction for all 6 Countries by Year versus Global Contact Center Satisfaction Index

The chart on the left that shows a trend in Average Satisfaction for the six countries in South America being considered indicates a strong positive trend. The second chart (shown on the right) shows the trend for the Global Contact Center satisfaction Index as decidedly negative. While these two trends were developed from different surveys under different conditions, there is an apparent difference that may override the differences in the populations used for each of the surveys. In other words, it is likely that the trend from South America does not have a significant impact on the trend measured by the Global contact Center satisfaction index nor may it even be included in the sampling population of the Global Contact Center Satisfaction Index.

One of the most important aspects of satisfaction surveys is the magnitude of the responses that are identified as either “dissatisfied” or “very dissatisfied.” The percent of surveys that were scored either “dissatisfied” or “very dissatisfied” for the Overall Satisfaction question is shown in Table 5 below.

Table 5: Percent of Scores that Represent Dissatisfaction

It should be noted that for the years 2016 and 2017, Venezuela had no responses that indicated either measure of Dissatisfaction. Many companies who use satisfaction surveys consider the Dissatisfaction scores as indicators of customers who are vulnerable. The NPS system refers to lower scores on their scale as Detractors, customers who will not provide positive comments and who may defect to a competitor.

Each country was evaluated in terms of the trend in average satisfaction during the 5-year range of data. For each of these countries a regression was performed with the results shown in the Table 6 below.

Table 6: Results of regression analysis of the means of Overall Satisfaction

From the results noted in Table 6 above, there is a statistically positive slope for Venezuela, Peru, and Chile. The values for Argentina change both positively and negatively over the five-year period and hence, there is no statistically significant trend, either positive or negative. These trends are also apparent when viewing the individual annual averages shown previously in Table 3.

A correlation was performed for each year of each country. From the correlations derived from the sample data, the survey question with the highest correlation with “Overall Satisfaction” was noted. The combined results of those analyses are tabulated in Table 7 below.

Table 7: Highest correlations by country/year

The abbreviations shown above are derived from the actual survey questions to indicate the drivers of “Overall Satisfaction” and are represent by “ease of requesting service (ease)”, “response time” (resp), “technical ability of the technician (tech)”, and “professionalism of the technician” (prof).

Although there is no obvious pattern for the correlations between individual survey questions and Overall Satisfaction, the number of occurrences for the “technical ability of the technician” is dominant. The “ease of requesting service” appears second-most frequently, while all the other questions have fewer strong correlations. Hence, no general conclusions have been drawn that represent all six countries. The inferences noted above are provided as strong indicators and should be considered accordingly.

5. Results

The following results and conclusions have been derived from the data set.

Hypothesis I: the distribution of satisfaction scores will be the same for all countries.

Result: a chi-square analysis of the distribution of satisfaction scores is NOT the same for each country, and hence the null hypothesis is REJECTED for the five years (p is less than 0.01).

Hypothesis II: the distribution of satisfaction scores will be the same for each of the five years for each country.

Result: a chi-square analysis of the distribution scores for the five years for each country individually indicates that the null hypothesis is REJECTED for Brazil, Chile and Colombia (p is less than 0.01). The null hypothesis is NOT REJECTED for Argentina (p=0.26), Peru (p=0.10) and Venezuela (p=0.54).

Hypothesis III: specific drivers of Overall Satisfaction will be the same for each country.

Result: no pattern is present either by country or by year. By observation the null hypothesis is REJECTED. The question most often correlated highest is the “technical ability of the technician” and is the only one that is mentioned in each country. 

6. General Discussion of Results and Possible Future Research

Although the results of the three research hypotheses indicate very few similarities with regard to satisfaction among the six countries, There are some trends and indicators in the data and analyses that suggest some common themes; namely,

  1. Satisfaction for most of the countries has a positive trend even though the Global Contact Center Satisfaction Index appears negative for the private sector for the same 5-year period.
  2. Culture and customs appear to play a significant role in perceptions of satisfaction since the results show they are statistically different among the six countries (refer to Hypothesis I).
  3. Three of the countries seem to be consistent in their perceptions of Satisfaction (Argentina, Peru and Venezuela – refer to Hypothesis II).
  4. Perceptions of Satisfaction appear not to be consistent over the 5-year period for three countries (Brazil, Chile and Columbia). It is not clear what is causing the variations in perceptions (refer to Hypothesis II).
  5. Similarly the level of Dissatisfaction for each of the countries seems to have a negative trend showing that the percent of customers indicating some level of Dissatisfaction is decreasing.
  6. There also seems to be a consistency among the six countries that the “Ability of the Technician” is most important with respect to service.

Some parting comments by executives operating businesses in South America also indicate future research possibilities.

  1. Carlos Melendez, COO and cofounder of wovenwear has noted lower wages of customer service reps in South America makes it easier to compete against the current value equation offered through automation. He also noted that countries in South America are improving their STEM education. He notes that Chile has initiated a program, called Startup Chile, which was created by the Chilean government and seeks to attract early stage, high potential entrepreneurs to bootstrap their startups using Chile as a platform to go global. He continues to focus on an educated workforce and to encourage growth in technology fields. Countries can take advantage of the automation revolution, instead of being victims of it.
  2. David Poole, co-founder and CEO of Symphony Ventures notes Brazil is likely to experience the most significant impact in automation as it starts to emerge from its recession and GDP starts to grow. There is an opportunity for Brazilian companies to grow without expanding their headcount and at the same time improve their profitability.

Poole adds that there is a huge amount of potential for automation in Latin America as the technology works best with more structured and digitized inputs.

Companies who provide call-center services in Latin America should recognize that the countries in South America have different perceptions of Customer Satisfaction; and hence cannot be managed as a unified group. While the equipment may be the same in each country, the way customers respond to service may be significantly different from country to country.

Perhaps the most significant opportunity for future research will be detecting the impact of technology on the cultures of the various South American countries.

References

Bibliography

  1. Curren, M.T., & Folkes, V. S. (1987). Attitudinal influences on consumer’s desire to communicate about products. Psychology and Marketing, Vol. 4, pp. 31-45.
  2. Folkes, V. S. (1984). Consumer reactions to product failure: an attributional approach. Journal of Consumer Research, Vol. 10, No. 4, pages 398-409.
  3. Hart, C. W. L., Heskett, J. L., & Sasser, Jr. W. E. (1990). The profitable art of service recovery, Harvard Business Review. Vol. 68, No. 4, pp. 148-156.
  4. Hess, R. L., Ganesan, S., & Klein, N. M. (2003). Service failure and recovery: the impact of relationship factors on Customer Satisfaction. Journal of the Academy of marketing science, Vol. 31, No. 2, pp. 127-145.
  5. Richins, M. L. (1987). A multivariate analysis of responses to Dissatisfaction. Journal of Academy of Marketing Science, Vol. 15, No. 3, pp. 24-31.
  6. Smith, A. K., Boltoon, R. N., & Wagner, J. (1999). A model of Customer Satisfaction with service encounters involving failure and recovery. Journal of Marketing Research, Vol. 36, No. 3, pp. 356-372.
  7. Hair, Jr., J. F., Anderson, R. E., Tatham, R. I., & Black, W. C. (1998). Multivariate Data Analysis. New York: Macmillan Publishing Co.

References

  1. Kay, J., & Thomas, R. C. (1995). Studying long-term system use. Communications of the ACM, 38, No. 7, pp. 61-69.
  2. Homburg, C., & Furst, A. (2005). How organizational complaint handling drives customer Loyalty: an analysis of the mechanistic and the organic approach. Journal of Marketing, Vol. 69, pp. 95-114.
  3. Mohr, L. A., & Bitner, M. J. (1995). The role of employee effort in satisfaction with service transactions. Journal of Business Research, Vol. 32, pp. 239-252.
  4. Seiders, K., Berry, L. L., (1998). Service fairness: what is it and why it matters. Academy of Management Executive, Vol.12, No. 2, pp. 8-20.
  5. Anderson, E. W., Sullivan, M. W. (1993). The antecedents and consequences of Customer Satisfaction for firms. Marketing Science, Vol.12, No. 2, pp. 125-143.
  6. Bearden, W. O., &Teel, J. E. (1983). Selected determinants of consumer satisfaction and complaint reports. Journal of Marketing Research, Vol. 20, No. One, pp. 21-28.
  7. Blodgett, J. G., Hill. D. J., & Tax, S. S. (1997). The effects of distributed, procedural, and interactional justice on post complaint behavior. Journal of Retailing, Vol 73, No. Two, pp. 185-210.
  8. Churchill, Jr., G. A., & Surprenant, C. (1982). An investigation into the determinants of consumer satisfaction. Journal of Marketing Research, 19, No. F, pp. 490-504.
  9. Desousa, A. C., Awazu, Y., & Ramaprasad, A. (2004). Modifications and innovations to technology artifacts. Technovation, Vol. 27, No. F, pp. 204-220.
  10. Fornell, C., & Wernerfelt, B. (1987). Defensive marketing strategy by customer complaint management: a theoretical analysis. Journal of Marketing Research, Vol. 24, No. F, pp. 337-346.
  11. Jha, S., Sangareddy, S. R. P., Desousa, K. C., Seo, Dongback, & Ye, Chen Ye. (2010). Impact of complaint management on repurchase intention of consumer technologies: employing the justice theory lens. International Journal of Product Development, Vol. 12, No. ¾, pp. 352-371.
  12. Goodwin, C., Ross, I. (1992). Consumer responses to service failures: influence of procedural and interactional fairness perceptions. Journal of Business Research, Vol. 25, pp. 149-163.
  13. Maxham III, J. G., & Netemeyer, R. G. (2002). A longitudinal study of complaint customers evaluations of multiple service failures and recovery efforts. Journal of Marketing, Vol. 66, pp. 57-71.
  14. Tax, S. S., Brown, S. W., & Chandrashekaran, M. (1998). Customer evaluations of service complaint experiences: implications for relationship marketing. Journal of Marketing, Vol. 62, pp. 60-76.
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Authors of the article
William Bleuel, PhD
William Bleuel, PhD
Dr. Bleuel's expertise lies in the quantitative aspects of business. He specializes in the measurement and analysis of business operations, call center operations, customer satisfaction, customer loyalty, and customer retention. He acts as an expert witness in the area of intellectual property. He has held senior positions in engineering, marketing, and service management at Xerox, Taylor Instrument Company, and Barber Colman Company. Dr. Bleuel has also had experience as general manager in two start-up companies that he co-founded. After the Sale, his second textbook, has replaced his first book, Service Management. He has been the Franz Edelman Award winner for The Institute of Management Sciences. He also received the Armitage Medal from the Society of Logistics Engineers, and the Patton Publication Award.. He became a Luckman Distinguished Teaching Fellow at Pepperdine in 1996.
John Robert
John Robert "Bob" McQuaid Jr., PhD
Prior to academia, Dr. McQuaid's industry experience included engineering, operations, and project management positions with U.S. Steel, General Dynamics, and Abbott Laboratories. After receiving his PhD in Management Science from the University of North Texas, he joined Graziadio as a Decision Sciences faculty member in 1998. In addition to teaching classes in both Decision Sciences and Information Systems, he has served in a variety of service and administrative leadership roles including inter alia: Director of the Full-time MBA Program; inaugural Director of the MS in Business Analytics Program; Chair of the newly created Information Systems and Technology Management discipline; Chaired the Pepperdine Graziadio Business School Full-time MBA Program, Faculty Council, and Personnel Committees; Chairing the University Faculty Council for four years and serving on the University Academic (UAC), Grievance (UGC), and Tenure (UTC) Committees. He was also Chair of the Faculty Engagement sub-committee during the last WSCUC accreditation review at Pepperdine Graziadio and co-authored the Provost's policy on Shared Governance approved by all five Pepperdine schools. For the past two years, Bob has also served on the Board of Directors for the Decision Sciences Institute.
Demosthenes Vardiabasis, PhD
Demosthenes Vardiabasis, PhD
Dr. Vardiabasis has over 25 years of experience as a professor, entrepreneur, executive, and consultant. He has founded several companies and has served as a chairman and CEO of the IQ Now Corporation, which was acquired by a public company and of Health Windows, which provided services to such companies as American Express, Hilton, Yamaha, and Honeywell. As a consultant, Dr. Vardiabasis has worked with companies representing a wide range of industries, including: Baxter Healthcare, Northwest Airlines, ICTS Europe, Edison Utilities, Northgate Supermarkets, El Proyecto, Brinks, Greek National Tourism Organization, Korean government, Latin Business Association, and the Arthritis Foundation. He has been an advisor and board member of several start-up companies. He served as a member of the U.S. committee to assist Russian Reform and of the National Policy Forum, chaired by U. S. Senator Phil Gramm. Recently he was appointed as Economic Commissioner in California by Governor Schwarzenegger. Dr. Vardiabasis, through his company, Global Strategic Edge, is currently working with executives and entrepreneurs on business strategy and creative operational solutions. Dr. Vardiabasis has published extensively in refereed journals, business magazines, and conference proceedings. He is the editor of a five-volume book on economics, published by Salem Press and has contributed to the book International Trade: Global Commodity Prize Stabilization, published by Quorum Books. A number of his articles have appeared in Annual Editions in Marketing, Business Insights, International Journal of Management, Mergers and Acquisitions, Journal of Commerce, Southwestern Economic Review, Business to Business, Journal of Economic Review, Japanese Management News, Developments in Marketing Science, Management Insight, and the Los Angeles Times.
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