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Introduction
Customer satisfaction surveys are an important part, especially for the service industry, as this provides a vivid view of the way the customers perception regarding quality of service provided and it also provides knowledge of what should be done to have loyal and satisfied customers. Research has shown that brand quality is directly related to the revenue of the restaurants (Victorino et al. 1991; Kim & Kim 2004; Lynn 2001). Understanding the customer helps in developing and bettering the customer experience. This paper is an analysis of a customer survey conducted for Santa Fe Grill Restaurant. The survey was conducted and 450 responses were received. The paper is divided to understand the demographic profile of the customers, their preferences regarding the restaurant, their decision-making criteria, and their satisfaction.
Data Analysis
The survey questionnaire has 35 questions of which 6 are classification questions, 4 are targeted to understand the selection factor of restaurants, 4 for relationship measures, 10 to gauge the perception of customers regarding the services of Santa Fe, 11 are lifestyle questions, and 4 initial questions are just introductory screening questions.
Initial Questions
To the initial questions, the answer was that the respondents regularly ate out in casual dining restaurants. All of the 450 respondents said that they had dinner in some Mexican restaurant in the past 6 months. Out of the 450 respondents, 99.8% of the respondents said that they have a household annual income of more than $15000. When asked which Mexican restaurant they visited most recently, 62.9% said Santa Fe Grill and 37.1% said Joes, Southwestern Grill. From the initial response, the majority of the respondents seem to prefer Santa Fe Grill recently.
Demographic Profile
Of the 450 respondents, 65.1% of the respondents are male and 34.2% are female. Therefore, we have 293 male and 154 female respondents.
Table 1.
Table 1 demonstrates the demographic classification of the respondents based on their age and gender. There were 65.1% made and 34.9 female respondents. The age of the respondents was segregated into 5 segments viz. 18 to 25 years, 26 to 34 years, 35 to 49 years, 50 to 59 years, and over 60 years as shown in table 1. Half (50.7%) of the people visiting Santa Fe Grill are of the age group of 34 to 49 years. 25.3% are in the age group of 50 to 59 years and 10% in 26 to 34 years. The income of the respondents is varied with the majority of the people visiting the restaurant $50,000 to $100,000.
The households that visit the restaurant are then categorized based on the number of children they have and the distance they have traveled to visit the restaurant. This is demonstrated in table 2.
Table 2.
It can be deduced from Table 2 that most of the respondents traveled a distance of more than 5 miles to reach the restaurant (40%), 32% traveled a distance of 1 to 5 miles and 28% traveled less than 1 mile. Most of the respondents visiting the restaurant did not have any children at home (47.8%), 26.4% left 1 to 2 children home and 25.8% left more than 2 children home. This shows that the popularity of the restaurant is more with couples with no or less than 2 children.
Selection Factor
Overall, the arithmetic mean of the responses provided on the selection factor of a restaurant by the respondents shows that the most important factor that they believe is important is the atmosphere of the restaurant. The mean score of for factor Atmosphere as rated by the respondents is 3.32 with a standard deviation of 0.71 indicating that mostly the respondents believe that atmosphere of the restaurant is one of the most important factors for choosing a restaurant as has been observed in other empirical customer choice studies (Autya 1992; Kivela 1997; Sulek & Hensley 2007). The next most important factor is service provided in the restaurants; however, the standard deviation of the Service factor shows that the answers to this may have been widely differentiated. Food quality however was rated the least important factor for the choice of restaurant, which opposes the findings of Sulek & Hensley (2007).
Table 3: Average rating to identify influential factors for a service purchase decision.
On doing a T-test (Table 4) on the selection factor responses, it was observed that the t value for factor Atmosphere was 98.017 indicating that the factor was highly significant on the choice made by respondents of a restaurant. The result was statically significant at 95%.
Table 4: T-test for.
Table 5: One-way ANOVA for selection criteria of restaurant responses.
The ANOVA results in table 5 are presented for selection criteria of a restaurant as answered by the respondents. The first table presents the descriptive statistics with the difference in the response given by gender. The descriptive table shows that female respondents feel that atmosphere is a more impotent factor for deciding restaurant than any other factor; the male respondents share this view too. The test of variance rejects the hypothesis that all the factors have an equal effect on the choice of service made by the respondents. The test shows that price has a significantly higher chance of affecting the choice decision than any other factor. The other factors do not have a significant chance of affecting the restaurant choice made by the respondents. The third table shows the one-way ANOVA results for the four factors. This shows that the significance level for all the four factors is greater than 0.05 indicating that none had a statically significant effect on the choice made by the respondents about restaurant service.
From the above analysis, it can be clearly stated that according to the t-test and the descriptive statistical analysis the most important factor for choosing a restaurant is the atmosphere of the restaurant, while the second most important reason is differing in the case of the t-test which states food quality to be the second most important factor and service according to average scores. However, according to the ANOVA results the factors are equally likely to predict the choice of restaurants.
Customer Satisfaction
Table 4: Descriptive statistics of customer survey question responses.
The descriptive statistics show the mean and standard deviation values of 10 questions measuring customer satisfaction responses. The responses show that the maximum average score that has been received is for the questions that state the reasons for the satisfaction of the customers to be excellent food taste , fresh food , and speed of service .
Table 5: T-test results for customer response for satisfaction survey.
On analyzing this data, further using one-way t-test it can be observed that the factors that have the maximum t value and show statistically significant results are excellent food taste , fresh food , and fun place to eat . Attractive interior also has a strong influence on influencing satisfaction of customers. This shows that the results of the descriptive analysis and t-test vary greatly.
Table 6: ANOVA results.
Table 6 presents the ANOVA results for gauging the degree of customer satisfaction. The first table shows the test of homogeneity. The analysis shows that all except proper food temperature, fun place to eat, large size portions, and reasonable prices, shows significantly different results and negates the null hypothesis of ANOVA. The second table is the ANOVA analysis that demonstrates that there is a significant difference in the groups for a fun place to eat and an attractive interior between genders. However, multiple comparisons for satisfaction results based on gender was not possible.
Based on age, the preferences for satisfaction differ greatly for options such as friendly employees, fun place to eat, large portions, fresh food, attractive interior, excellent food taste, knowledgeable employees, proper food temperature, and speed of service. The post hoc Tuckey test shows that there is a significant difference between the preference for friendly employees for ages 18-25 and 26-34 years and 26-34 with all other age groups. However, there are no significant differences in the older age group of preference for friendly employees. Fun place to eat also has significant differences in preference based on lower ages from 18-25 and all other age groups.
Tuckey test based on the difference in income shows that there is a significant difference in the satisfaction of customers between low and high-income groups, wherein respondents with higher income, i.e. above $100000 were more satisfied with the restaurant than the people with lower income.
Table 7: Tukey Post-hoc test for difference in satisfaction factors based on Income.
Overall, for higher-income groups, the difference in customer satisfaction due to income differences is not much. The Tuckey HSD results show that there is only a significant difference in the mean score of satisfaction questions factored by income and they are in the case of lower-income groups from $10000 to $25000 and higher-income groups $100000 and above. A significant level of differences was registered for factors such as friendly employees, large size portions where higher income groups demand larger portions, knowledgeable, and excellent food taste. These findings are supported by other research findings on customer satisfaction survey conducted for the service industry (Oh 1999; Hallowell 1996)
On answering the question as to how satisfied the customers were a descriptive analysis of the question with age as the independent variable, we find that female customers were more satisfied than male customers. The ANOVA results also confirm the finding that there is a significant difference in the means of satisfaction between genders. Based on the income it can be deduced that the customers with higher income groups were more satisfied with the service provided. In age-based difference, respondents within the age group of 26 to 49 years were more satisfied. The results show that satisfaction among respondents varied significantly based on gender, age, and income as has been confirmed through previous empirical researches (Smith, Bolton & Wagner 1999; Andaleeb & Conway 2006; Danaher & Mattsson 1994; McCollough, Berry & Yadav. 2000; Peterson & Wilson 1991; Dube, Renaghan & Miller 1994).
Willingness to Return to the Restaurant
This section will gauge the willingness of the customers to return to the restaurant based on the responses they presented in the survey. Table 8 presents three questions gauging the relationship built with the customers. It asked them about their satisfaction with the restaurant, their intention to recommend it to others, and the probability for them to return to the restaurant. The T-test results show that that the mean value of the responses measured in a 7-point Likert scale demonstrates that none of the responses were overly optimistic as the mean value of the responses linger below 4.5 that indicates marginally satisfaction. On likely to recommend measure, the respondents gave an average score of 3.78 indicating that they were most likely not going to recommend the restaurant to others. A T-test confirms these findings, as all of them showed significantly different scores from their original mean scores.
Table 8: T-Test for relationship measures.
A regression analysis of the satisfaction measure of the respondents and the likelihood to recommend and return shows that people are more satisfied if they have shown a higher likelihood to return. Regression analysis is used to understand the interlink between the dependent satisfaction, return, and recommend intentions and the demographic variables as has been used in many other customer satisfaction studies (Rust & Zahorik 1993; Matzler et al. 2004; Anderson 1994; Fornell et al. 1996; Woodside, Frey & Daly 1989). Table 9 presents the regression analysis of the satisfaction measure dependent on an inclination to return and recommend. The R-value in the first table of Table 9 demonstrates that there is an 84.9% likelihood of the findings to be true. This shows that with an increase in return intention, there will be a greater inclination of the respondents to return.
Table 9: Regression Analysis.
Table 10: Regression of satisfaction factored by age and income.
Table 10 shows that age has a significantly negative influence on the satisfaction derived by customers in the restaurant. It shows that the higher the age of the customer, the lower is the satisfaction they derived from the services. Income too has a negative relation with satisfaction, indicating that higher-income customers are more difficult to be satisfied with the services provided at the restaurant.
When another regression analysis is done on return to intention-based on age and income it showed that age and income both are negatively related to intention to return.
Table 11: Multiple ANOVA based on Age.
The comparison in table 11 shows the age factor that influences the difference in satisfaction of respondents, intention to return to the restaurant, and intention to spread word-of-mouth advertisement. This finding is consistent with research on customer retention and intention to return literature (Jiang & Rosenbloom 2005; Kim, Ng & Kim 2009; Hellier et al. 2003; Fornell 1992; Churchill Jr & Surprenant. 1982; HennigThurau & Klee 1998; Woodside, Frey & Daly 1989).
Recommendations
Customer satisfaction and their intention to return to the restaurant are closely linked as many of the customers mentioned that they are satisfied and intended to come back (Bowen & Chen 2001; Mittal & Kamakura 2001; McDougall & Levesque 2000; Weiss, Feinstein & Dalbor 2005; Bigne, Sanchez & Sanchez 2001). Age and income influence the satisfaction, intention to return, and intention to recommend (Bellman, Lohse & Johnson 1999; Sharp & Sharp 1997; Skogland & Siguaw 2004; Tarn 1999; Snyder 1992). Within the age group of 25 to 39, respondents were most satisfied and had greater intention to return or recommend the restaurant. In terms of income, people with higher income groups were more inclined to return to the restaurant (White & Yanamandram 2004; Crotts 1999; Chow et al. 2007; Soriano 2002; Curasi & Kennedy 2002).
Further people who had to travel less to the restaurant intended to return more to the restaurant. Therefore, to target market the restaurant, Santa Fe Grill should target young from 25 to 39 groups with moderately high income who live within a 5-mile radius of the restaurant. Further intention to eat out is more for the younger group of 18 to 25 years and above 50 years group, indicating that young and old people are more frequently inclined to eat out as opposed to middle-aged people. The factors that have been found to influence the decision making of the customers are the atmosphere of the restaurant, price, and service. These three factors must be paid more attention to make it more successful. Further, the criteria that satisfied the respondents with lower income more are friendly employees and large size portions served while respondents with higher income were more interested in knowledgeable employees and price. A restaurant service may seem different to different people however, for Santa Fe the best idea would be to attract locals, concentrate on the atmosphere of the restaurant to enhance the ambiance and experience of the customers, and have competitive prices.
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