Home > Free Essays > Business > Company Analysis > Santa Fe Grill Restaurant’s Customer Analysis
20 min
Cite this

Santa Fe Grill Restaurant’s Customer Analysis Essay


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 Joe’s, 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.

X32 — Gender.
Frequency Percent Valid Percent Cumulative Percent
Valid Male 293 65.1 65.1 65.1
Female 157 34.9 34.9 100.0
Total 450 100.0 100.0
X34 — Age.
Frequency Percent Valid Percent Cumulative Percent
Valid 18 – 25 41 9.1 9.1 9.1
26 – 34 45 10.0 10.0 19.1
35 – 49 228 50.7 50.7 69.8
50 – 59 114 25.3 25.3 95.1
60 and Over 22 4.9 4.9 100.0
Total 450 100.0 100.0
Income.
Frequency Percent Valid Percent Cumulative Percent
Valid 10000-15000 78 17.3 17.8 17.8
15001-50000 123 27.3 28.1 45.9
50001-99999 133 29.6 30.4 76.3
100000-130000 77 17.1 17.6 93.8
130001-170000 27 6.0 6.2 100.0
Total 438 97.3 100.0
Missing System 12 2.7
Total 450 100.0

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.

x30 — Distance Driven to Restaurant.
Frequency Percent Valid Percent Cumulative Percent
Valid Less than 1 mile 126 28.0 28.0 28.0
1 — 5 miles 144 32.0 32.0 60.0
More than 5 miles 180 40.0 40.0 100.0
Total 450 100.0 100.0
X33 — Number of Children at Home.
Frequency Percent Valid Percent Cumulative Percent
Valid No Children at Home 215 47.8 47.8 47.8
1-2 Children at Home 119 26.4 26.4 74.2
More Than 2 Children at Home 116 25.8 25.8 100.0
Total 450 100.0 100.0

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.

Mean Mode Standard Deviation
X27 — Food Quality 2 1 1
X29 — Service 3 2 2
X28 — Atmosphere 3 3 1
X26 — Price 2 1 1

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.

One-Sample Test
Test Value = 0
t df Sig. (2-tailed) Mean Difference 95% Confidence Interval of the Difference
Lower Upper
X26 — Price 43.489 449 .000 2.351 2.24 2.46
X27 — Food Quality 46.431 449 .000 1.584 1.52 1.65
X28 — Atmosphere 98.017 449 .000 3.316 3.25 3.38
X29 — Service 29.050 449 .000 2.844 2.65 3.04

Table 5: One-way ANOVA for selection criteria of restaurant responses.

Descriptives
N Mean Std.
Deviation
Std.
Error
95% Confidence
Interval for Mean
Minimum Maximum
Lower
Bound
Upper
Bound
X26 — Price Male 293 2.33 1.093 .064 2.20 2.45 1 4
Female 157 2.39 1.244 .099 2.20 2.59 1 4
Total 450 2.35 1.147 .054 2.24 2.46 1 4
X27 — Food Quality Male 293 1.54 .690 .040 1.46 1.62 1 3
Female 157 1.68 .778 .062 1.55 1.80 1 4
Total 450 1.58 .724 .034 1.52 1.65 1 4
X28 — Atmosphere Male 293 3.34 .696 .041 3.26 3.42 1 4
Female 157 3.27 .756 .060 3.15 3.39 1 4
Total 450 3.32 .718 .034 3.25 3.38 1 4
X29 — Service Male 293 2.92 2.466 .144 2.64 3.21 1 41
Female 157 2.69 .998 .080 2.54 2.85 1 4
Total 450 2.84 2.077 .098 2.65 3.04 1 41
Test of Homogeneity of Variances
Levene
Statistic
df1 df2 Sig.
X26 — Price 14.659 1 448 .000
X27 — Food Quality 3.524 1 448 .061
X28 — Atmosphere .476 1 448 .491
X29 — Service .839 1 448 .360
ANOVA
Sum of
Squares
df Mean
Square
F Sig.
X26 — Price Between Groups .462 1 .462 .351 .554
Within Groups 590.062 448 1.317
Total 590.524 449
X27 — Food Quality Between Groups 1.984 1 1.984 3.810 .052
Within Groups 233.307 448 .521
Total 235.291 449
X28 — Atmosphere Between Groups .419 1 .419 .813 .368
Within Groups 230.772 448 .515
Total 231.191 449
X29 — Service Between Groups 5.438 1 5.438 1.261 .262
Within Groups 1931.673 448 4.312
Total 1937.111 449

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.

One-Sample Statistics
N Mean Std. Deviation Std. Error Mean
X12 — Friendly Employees 450 3.63 1.204 .057
X13 — Fun Place to Eat 450 4.63 .894 .042
X14 — Large Size Portions 450 4.52 1.318 .062
X15 — Fresh Food 450 5.73 1.198 .056
X16 — Reasonable Prices 450 4.60 3.649 .172
X17 — Attractive Interior 450 4.70 1.011 .048
X18 — Excellent Food Taste 450 5.29 1.087 .051
X19 — Knowledgeable Employees 450 3.52 1.509 .071
X20 — Proper Food Temperature 450 4.74 3.840 .181
X21 — Speed of Service 450 5.17 2.072 .098

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.

One-Sample Test
Test Value = 0
t df Sig.
(2-tailed)
Mean
Difference
95% Confidence
Interval of the
Difference
Lower Upper
X12 — Friendly Employees 64.034 449 .000 3.633 3.52 3.74
X13 — Fun Place to Eat 109.903 449 .000 4.631 4.55 4.71
X14 — Large Size Portions 72.658 449 .000 4.516 4.39 4.64
X15 — Fresh Food 101.477 449 .000 5.731 5.62 5.84
X16 — Reasonable Prices 26.770 449 .000 4.604 4.27 4.94
X17 — Attractive Interior 98.664 449 .000 4.700 4.61 4.79
X18 — Excellent Food Taste 103.225 449 .000 5.291 5.19 5.39
X19 — Knowledgeable Employees 49.518 449 .000 3.522 3.38 3.66
X20 — Proper Food Temperature 26.176 449 .000 4.738 4.38 5.09
X21 — Speed of Service 52.939 449 .000 5.171 4.98 5.36

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.

Test of Homogeneity of Variances
Levene Statistic df1 df2 Sig.
X12 — Friendly Employees 6.199 1 448 .013
X13 — Fun Place to Eat .335 1 448 .563
X14 — Large Size Portions .729 1 448 .394
X15 — Fresh Food 30.809 1 448 .000
X16 — Reasonable Prices 1.537 1 448 .216
X17 — Attractive Interior 19.303 1 448 .000
X18 — Excellent Food Taste 30.023 1 448 .000
X19 — Knowledgeable Employees 13.269 1 448 .000
X20 — Proper Food Temperature .938 1 448 .333
X21 — Speed of Service 5.719 1 448 .017
ANOVA
Sum of
Squares
df Mean
Square
F Sig.
X12 — Friendly Employees Between Groups 1.065 1 1.065 .735 .392
Within Groups 649.435 448 1.450
Total 650.500 449
X13 — Fun Place to Eat Between Groups 4.698 1 4.698 5.945 .015
Within Groups 354.066 448 .790
Total 358.764 449
X14 — Large Size Portions Between Groups .091 1 .091 .053 .819
Within Groups 780.300 448 1.742
Total 780.391 449
X15 — Fresh Food Between Groups 1.138 1 1.138 .792 .374
Within Groups 643.327 448 1.436
Total 644.464 449
X16 — Reasonable Prices Between Groups 23.390 1 23.390 1.760 .185
Within Groups 5954.201 448 13.291
Total 5977.591 449
X17 — Attractive Interior Between Groups 10.080 1 10.080 10.070 .002
Within Groups 448.420 448 1.001
Total 458.500 449
X18 — Excellent Food Taste Between Groups .106 1 .106 .090 .765
Within Groups 530.758 448 1.185
Total 530.864 449
X19 — Knowledgeable Employees Between Groups 4.309 1 4.309 1.897 .169
Within Groups 1017.968 448 2.272
Total 1022.278 449
X20 — Proper Food Temperature Between Groups 17.395 1 17.395 1.180 .278
Within Groups 6601.663 448 14.736
Total 6619.058 449
X21 — Speed of Service Between Groups .231 1 .231 .054 .817
Within Groups 1927.593 448 4.303
Total 1927.824 449

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.

Multiple Comparisons
Tukey HSD
Dependent
Variable
(I) Income (J) Income Mean
Difference
(I-J)
Std.
Error
Sig. 95%
Confidence Interval
Lower
Bound
Upper
Bound
X12 — Friendly
Employees
10000-15000 15001-50000 -.013 .169 1.000 -.47 .45
50001-99999 -.424 .166 .082 -.88 .03
100000-130000 -.679* .187 .003 -1.19 -.17
130001-170000 -.902* .260 .005 -1.61 -.19
15001-50000 10000-15000 .013 .169 1.000 -.45 .47
50001-99999 -.411* .146 .040 -.81 -.01
100000-130000 -.667* .169 .001 -1.13 -.20
130001-170000 -.889* .248 .003 -1.57 -.21
50001-99999 10000-15000 .424 .166 .082 -.03 .88
15001-50000 .411* .146 .040 .01 .81
100000-130000 -.256 .167 .542 -.71 .20
130001-170000 -.478 .246 .297 -1.15 .20
100000-130000 10000-15000 .679* .187 .003 .17 1.19
15001-50000 .667* .169 .001 .20 1.13
50001-99999 .256 .167 .542 -.20 .71
130001-170000 -.222 .261 .914 -.94 .49
130001-170000 10000-15000 .902* .260 .005 .19 1.61
15001-50000 .889* .248 .003 .21 1.57
50001-99999 .478 .246 .297 -.20 1.15
100000-130000 .222 .261 .914 -.49 .94
X13 — Fun
Place to Eat
10000-15000 15001-50000 .186 .125 .569 -.16 .53
50001-99999 .377* .123 .019 .04 .71
100000-130000 -.295 .139 .209 -.67 .08
130001-170000 -.269 .193 .629 -.80 .26
15001-50000 10000-15000 -.186 .125 .569 -.53 .16
50001-99999 .191 .108 .391 -.10 .49
100000-130000 -.481* .125 .001 -.82 -.14
130001-170000 -.455 .183 .096 -.96 .05
50001-99999 10000-15000 -.377* .123 .019 -.71 -.04
15001-50000 -.191 .108 .391 -.49 .10
100000-130000 -.673* .124 .000 -1.01 -.33
130001-170000 -.647* .182 .004 -1.15 -.15
100000-130000 10000-15000 .295 .139 .209 -.08 .67
15001-50000 .481* .125 .001 .14 .82
50001-99999 .673* .124 .000 .33 1.01
130001-170000 .026 .193 1.000 -.50 .55
130001-170000 10000-15000 .269 .193 .629 -.26 .80
15001-50000 .455 .183 .096 -.05 .96
50001-99999 .647* .182 .004 .15 1.15
100000-130000 -.026 .193 1.000 -.55 .50
X14 — Large
Size Portions
10000-15000 15001-50000 .119 .177 .963 -.37 .60
50001-99999 .413 .175 .126 -.06 .89
100000-130000 -1.019* .197 .000 -1.56 -.48
130001-170000 -.786* .273 .034 -1.53 -.04
15001-50000 10000-15000 -.119 .177 .963 -.60 .37
50001-99999 .295 .153 .306 -.12 .71
100000-130000 -1.137* .178 .000 -1.62 -.65
130001-170000 -.905* .260 .005 -1.62 -.19
50001-99999 10000-15000 -.413 .175 .126 -.89 .06
15001-50000 -.295 .153 .306 -.71 .12
100000-130000 -1.432* .175 .000 -1.91 -.95
130001-170000 -1.200* .258 .000 -1.91 -.49
100000-130000 10000-15000 1.019* .197 .000 .48 1.56
15001-50000 1.137* .178 .000 .65 1.62
50001-99999 1.432* .175 .000 .95 1.91
130001-170000 .232 .274 .915 -.52 .98
130001-170000 10000-15000 .786* .273 .034 .04 1.53
15001-50000 .905* .260 .005 .19 1.62
50001-99999 1.200* .258 .000 .49 1.91
100000-130000 -.232 .274 .915 -.98 .52
X15 — Fresh
Food
10000-15000 15001-50000 -.148 .159 .884 -.58 .29
50001-99999 -.436* .156 .043 -.86 -.01
100000-130000 -1.302* .176 .000 -1.78 -.82
130001-170000 -1.412* .245 .000 -2.08 -.74
15001-50000 10000-15000 .148 .159 .884 -.29 .58
50001-99999 -.288 .137 .220 -.66 .09
100000-130000 -1.154* .159 .000 -1.59 -.72
130001-170000 -1.264* .233 .000 -1.90 -.63
50001-99999 10000-15000 .436* .156 .043 .01 .86
15001-50000 .288 .137 .220 -.09 .66
100000-130000 -.865* .157 .000 -1.29 -.44
130001-170000 -.975* .231 .000 -1.61 -.34
100000-130000 10000-15000 1.302* .176 .000 .82 1.78
15001-50000 1.154* .159 .000 .72 1.59
50001-99999 .865* .157 .000 .44 1.29
130001-170000 -.110 .245 .992 -.78 .56
130001-170000 10000-15000 1.412* .245 .000 .74 2.08
15001-50000 1.264* .233 .000 .63 1.90
50001-99999 .975* .231 .000 .34 1.61
100000-130000 .110 .245 .992 -.56 .78
X16 — Reasonable
Prices
10000-15000 15001-50000 -.055 .530 1.000 -1.51 1.40
50001-99999 .054 .523 1.000 -1.38 1.49
100000-130000 -1.562 .589 .063 -3.17 .05
130001-170000 -.557 .818 .961 -2.80 1.68
15001-50000 10000-15000 .055 .530 1.000 -1.40 1.51
50001-99999 .109 .458 .999 -1.15 1.36
100000-130000 -1.508* .532 .039 -2.97 -.05
130001-170000 -.502 .779 .968 -2.64 1.63
50001-99999 10000-15000 -.054 .523 1.000 -1.49 1.38
15001-50000 -.109 .458 .999 -1.36 1.15
100000-130000 -1.617* .525 .019 -3.05 -.18
130001-170000 -.611 .773 .933 -2.73 1.51
100000-130000 10000-15000 1.562 .589 .063 -.05 3.17
15001-50000 1.508* .532 .039 .05 2.97
50001-99999 1.617* .525 .019 .18 3.05
130001-170000 1.005 .820 .736 -1.24 3.25
130001-170000 10000-15000 .557 .818 .961 -1.68 2.80
15001-50000 .502 .779 .968 -1.63 2.64
50001-99999 .611 .773 .933 -1.51 2.73
100000-130000 -1.005 .820 .736 -3.25 1.24
X17 – Attractive
Interior
10000-15000 15001-50000 .128 .139 .889 -.25 .51
50001-99999 .517* .137 .002 .14 .89
100000-130000 -.348 .154 .162 -.77 .08
130001-170000 -.538 .215 .091 -1.13 .05
15001-50000 10000-15000 -.128 .139 .889 -.51 .25
50001-99999 .388* .120 .012 .06 .72
100000-130000 -.476* .140 .006 -.86 -.09
130001-170000 -.667* .204 .010 -1.23 -.11
50001-99999 10000-15000 -.517* .137 .002 -.89 -.14
15001-50000 -.388* .120 .012 -.72 -.06
100000-130000 -.865* .138 .000 -1.24 -.49
130001-170000 -1.055* .203 .000 -1.61 -.50
100000-130000 10000-15000 .348 .154 .162 -.08 .77
15001-50000 .476* .140 .006 .09 .86
50001-99999 .865* .138 .000 .49 1.24
130001-170000 -.190 .215 .902 -.78 .40
130001-170000 10000-15000 .538 .215 .091 -.05 1.13
15001-50000 .667* .204 .010 .11 1.23
50001-99999 1.055* .203 .000 .50 1.61
100000-130000 .190 .215 .902 -.40 .78
X18 — Excellent
Food Taste
10000-15000 15001-50000 -.014 .151 1.000 -.43 .40
50001-99999 -.444* .149 .025 -.85 -.04
100000-130000 -.727* .168 .000 -1.19 -.27
130001-170000 -1.001* .233 .000 -1.64 -.36
15001-50000 10000-15000 .014 .151 1.000 -.40 .43
50001-99999 -.430* .131 .010 -.79 -.07
100000-130000 -.713* .152 .000 -1.13 -.30
130001-170000 -.987* .222 .000 -1.60 -.38
50001-99999 10000-15000 .444* .149 .025 .04 .85
15001-50000 .430* .131 .010 .07 .79
100000-130000 -.282 .150 .327 -.69 .13
130001-170000 -.557 .221 .087 -1.16 .05
100000-130000 10000-15000 .727* .168 .000 .27 1.19
15001-50000 .713* .152 .000 .30 1.13
50001-99999 .282 .150 .327 -.13 .69
130001-170000 -.275 .234 .766 -.92 .37
130001-170000 10000-15000 1.001* .233 .000 .36 1.64
15001-50000 .987* .222 .000 .38 1.60
50001-99999 .557 .221 .087 -.05 1.16
100000-130000 .275 .234 .766 -.37 .92
X19 — Knowledgeable Employees 10000-15000 15001-50000 -.049 .208 .999 -.62 .52
50001-99999 -.782* .205 .001 -1.34 -.22
100000-130000 -1.104* .231 .000 -1.74 -.47
130001-170000 -1.148* .321 .004 -2.03 -.27
15001-50000 10000-15000 .049 .208 .999 -.52 .62
50001-99999 -.733* .180 .001 -1.23 -.24
100000-130000 -1.055* .209 .000 -1.63 -.48
130001-170000 -1.099* .306 .003 -1.94 -.26
50001-99999 10000-15000 .782* .205 .001 .22 1.34
15001-50000 .733* .180 .001 .24 1.23
100000-130000 -.322 .206 .523 -.89 .24
130001-170000 -.366 .304 .748 -1.20 .47
100000-130000 10000-15000 1.104* .231 .000 .47 1.74
15001-50000 1.055* .209 .000 .48 1.63
50001-99999 .322 .206 .523 -.24 .89
130001-170000 -.044 .322 1.000 -.93 .84
130001-170000 10000-15000 1.148* .321 .004 .27 2.03
15001-50000 1.099* .306 .003 .26 1.94
50001-99999 .366 .304 .748 -.47 1.20
100000-130000 .044 .322 1.000 -.84 .93
X20 — Proper
Food Temperature
10000-15000 15001-50000 .008 .557 1.000 -1.52 1.53
50001-99999 -.456 .549 .921 -1.96 1.05
100000-130000 -1.717* .619 .045 -3.41 -.02
130001-170000 -1.090 .860 .711 -3.44 1.27
15001-50000 10000-15000 -.008 .557 1.000 -1.53 1.52
50001-99999 -.463 .482 .872 -1.78 .86
100000-130000 -1.725* .560 .018 -3.26 -.19
130001-170000 -1.098 .818 .666 -3.34 1.14
50001-99999 10000-15000 .456 .549 .921 -1.05 1.96
15001-50000 .463 .482 .872 -.86 1.78
100000-130000 -1.262 .551 .151 -2.77 .25
130001-170000 -.634 .813 .936 -2.86 1.59
100000-130000 10000-15000 1.717* .619 .045 .02 3.41
15001-50000 1.725* .560 .018 .19 3.26
50001-99999 1.262 .551 .151 -.25 2.77
130001-170000 .628 .861 .950 -1.73 2.99
130001-170000 10000-15000 1.090 .860 .711 -1.27 3.44
15001-50000 1.098 .818 .666 -1.14 3.34
50001-99999 .634 .813 .936 -1.59 2.86
100000-130000 -.628 .861 .950 -2.99 1.73
X21 — Speed
of Service
10000-15000 15001-50000 .398 .294 .657 -.41 1.20
50001-99999 -.278 .290 .873 -1.07 .52
100000-130000 -.753 .326 .145 -1.65 .14
130001-170000 -1.185 .454 .070 -2.43 .06
15001-50000 10000-15000 -.398 .294 .657 -1.20 .41
50001-99999 -.677 .254 .062 -1.37 .02
100000-130000 -1.152* .295 .001 -1.96 -.34
130001-170000 -1.584* .432 .003 -2.77 -.40
50001-99999 10000-15000 .278 .290 .873 -.52 1.07
15001-50000 .677 .254 .062 -.02 1.37
100000-130000 -.475 .291 .478 -1.27 .32
130001-170000 -.907 .429 .216 -2.08 .27
100000-130000 10000-15000 .753 .326 .145 -.14 1.65
15001-50000 1.152* .295 .001 .34 1.96
50001-99999 .475 .291 .478 -.32 1.27
130001-170000 -.432 .455 .877 -1.68 .81
130001-170000 10000-15000 1.185 .454 .070 -.06 2.43
15001-50000 1.584* .432 .003 .40 2.77
50001-99999 .907 .429 .216 -.27 2.08
100000-130000 .432 .455 .877 -.81 1.68
*. The mean difference is significant at the 0.05 level.

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.

One-Sample Statistics
N Mean Std. Deviation Std. Error Mean
X23 — Likely to Return 450 4.46 1.104 .052
X24 — Likely to Recommend 450 3.78 1.204 .057
X22 — Satisfaction 450 4.82 1.122 .053
One-Sample Test
Test Value = 0
t df Sig.
(2-tailed)
Mean
Difference
95% Confidence Interval of the Difference
Lower Upper
X23 — Likely to Return 85.585 449 .000 4.456 4.35 4.56
X24 — Likely to Recommend 66.650 449 .000 3.782 3.67 3.89
X22 — Satisfaction 91.102 449 .000 4.818 4.71 4.92

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.

Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .849a .720 .719 .595
a. Predictors: (Constant), X24 — Likely to Recommend, X23 — Likely to Return
ANOVA
Model Sum of Squares df Mean Square F Sig.
1 Regression 406.942 2 203.471 575.220 .000b
Residual 158.116 447 .354
Total 565.058 449
a. Dependent Variable: X22 — Satisfaction
b. Predictors: (Constant), X24 — Likely to Recommend, X23 — Likely to Return
Coefficients
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) 1.185 .118 10.073 .000
X23 — Likely to Return .534 .048 .526 11.117 .000
X24 — Likely to Recommend .331 .044 .355 7.508 .000
a. Dependent Variable: X22 — Satisfaction

Table 10: Regression of satisfaction factored by age and income.

Model Summary
Model R R Square Adjusted R Square Std. The error of the Estimate
1 .388a .150 .147 1.036
a. Predictors: (Constant), X35 — Income, X34 — Age
ANOVA
Model Sum of Squares df Mean Square F Sig.
1 Regression 85.004 2 42.502 39.576 .000b
Residual 480.054 447 1.074
Total 565.058 449
a. Dependent Variable: X22 — Satisfaction
b. Predictors: (Constant), X35 — Income, X34 — Age
Coefficients
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) 5.194 .175 29.611 .000
X34 — Age -.214 .052 -.182 -4.140 .000
X35 — Income 3.890E-006 .000 .319 7.240 .000
a. Dependent Variable: X22 — Satisfaction

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.

Multiple Comparisons
Tukey HSD
Dependent
Variable
(I) X34 –
Age
(J) X34 –
Age
Mean
Difference
(I-J)
Std.
Error
Sig. 95%
Confidence Interval
Lower
Bound
Upper
Bound
X22 — Satisfaction 18 – 25 26 – 34 -.049 .225 1.000 -.66 .57
35 – 49 -.180 .177 .845 -.66 .30
50 – 59 .846* .189 .000 .33 1.36
60 and Over .315 .275 .782 -.44 1.07
26 – 34 18 – 25 .049 .225 1.000 -.57 .66
35 – 49 -.132 .170 .938 -.60 .33
50 – 59 .895* .183 .000 .39 1.40
60 and Over .364 .271 .664 -.38 1.11
35 – 49 18 – 25 .180 .177 .845 -.30 .66
26 – 34 .132 .170 .938 -.33 .60
50 – 59 1.026* .119 .000 .70 1.35
60 and Over .495 .232 .208 -.14 1.13
50 – 59 18 – 25 -.846* .189 .000 -1.36 -.33
26 – 34 -.895* .183 .000 -1.40 -.39
35 – 49 -1.026* .119 .000 -1.35 -.70
60 and Over -.531 .242 .185 -1.19 .13
60 and Over 18 – 25 -.315 .275 .782 -1.07 .44
26 – 34 -.364 .271 .664 -1.11 .38
35 – 49 -.495 .232 .208 -1.13 .14
50 – 59 .531 .242 .185 -.13 1.19
X23 — Likely to Return 18 – 25 26 – 34 .122 .222 .982 -.48 .73
35 – 49 .211 .174 .743 -.27 .69
50 – 59 1.132* .187 .000 .62 1.64
60 and Over .333 .271 .736 -.41 1.08
26 – 34 18 – 25 -.122 .222 .982 -.73 .48
35 – 49 .089 .167 .984 -.37 .55
50 – 59 1.010* .181 .000 .52 1.50
60 and Over .210 .267 .934 -.52 .94
35 – 49 18 – 25 -.211 .174 .743 -.69 .27
26 – 34 -.089 .167 .984 -.55 .37
50 – 59 .921* .118 .000 .60 1.24
60 and Over .121 .229 .984 -.51 .75
50 – 59 18 – 25 -1.132* .187 .000 -1.64 -.62
26 – 34 -1.010* .181 .000 -1.50 -.52
35 – 49 -.921* .118 .000 -1.24 -.60
60 and Over -.800* .239 .008 -1.45 -.15
60 and Over 18 – 25 -.333 .271 .736 -1.08 .41
26 – 34 -.210 .267 .934 -.94 .52
35 – 49 -.121 .229 .984 -.75 .51
50 – 59 .800* .239 .008 .15 1.45
X24 — Likely to Recommend 18 – 25 26 – 34 .188 .244 .939 -.48 .86
35 – 49 .454 .192 .127 -.07 .98
50 – 59 1.278* .206 .000 .71 1.84
60 and Over .229 .299 .939 -.59 1.05
26 – 34 18 – 25 -.188 .244 .939 -.86 .48
35 – 49 .265 .184 .602 -.24 .77
50 – 59 1.090* .199 .000 .55 1.63
60 and Over .041 .294 1.000 -.76 .85
35 – 49 18 – 25 -.454 .192 .127 -.98 .07
26 – 34 -.265 .184 .602 -.77 .24
50 – 59 .825* .130 .000 .47 1.18
60 and Over -.224 .252 .901 -.91 .47
50 – 59 18 – 25 -1.278* .206 .000 -1.84 -.71
26 – 34 -1.090* .199 .000 -1.63 -.55
35 – 49 -.825* .130 .000 -1.18 -.47
60 and Over -1.049* .263 .001 -1.77 -.33
60 and Over 18 – 25 -.229 .299 .939 -1.05 .59
26 – 34 -.041 .294 1.000 -.85 .76
35 – 49 .224 .252 .901 -.47 .91
50 – 59 1.049* .263 .001 .33 1.77
X25 — Frequency of Eating at… ?? 18 – 25 26 – 34 1.030 .552 .338 -.48 2.54
35 – 49 .870 .434 .264 -.32 2.06
50 – 59 2.173* .466 .000 .90 3.45
60 and Over 1.949* .676 .033 .10 3.80
26 – 34 18 – 25 -1.030 .552 .338 -2.54 .48
35 – 49 -.159 .417 .995 -1.30 .98
50 – 59 1.143 .450 .084 -.09 2.38
60 and Over .919 .665 .640 -.90 2.74
35 – 49 18 – 25 -.870 .434 .264 -2.06 .32
26 – 34 .159 .417 .995 -.98 1.30
50 – 59 1.303* .293 .000 .50 2.11
60 and Over 1.079 .571 .325 -.49 2.64
50 – 59 18 – 25 -2.173* .466 .000 -3.45 -.90
26 – 34 -1.143 .450 .084 -2.38 .09
35 – 49 -1.303* .293 .000 -2.11 -.50
60 and Over -.224 .596 .996 -1.86 1.41
60 and Over 18 – 25 -1.949* .676 .033 -3.80 -.10
26 – 34 -.919 .665 .640 -2.74 .90
35 – 49 -1.079 .571 .325 -2.64 .49
50 – 59 .224 .596 .996 -1.41 1.86
*. The mean difference is significant at the 0.05 level.

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; Hennig‐Thurau & 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.

Reference List

Andaleeb, SS & Conway, C 2006, ‘Syed Saad Andaleeb, Carolyn Conway, “Customer satisfaction in the restaurant industry: an examination of the transaction-specific model”, 20, (2006)’, Journal of Service Marketing, vol 20, no. 1, pp. 3-11.

Anderson, EW 1994, ‘Cross-category variation in customer satisfaction and retention’, Marketing Letters, vol 5, no. 1, pp. 19-30.

Autya, S 1992, ‘Consumer Choice and Segmentation in the Restaurant Industry’, The Service Industries Journal, vol 12, no. 3, pp. 324-339.

Bellman, S, Lohse, GL & Johnson, EJ 1999, ‘Predictors of online buying behavior’, Communications of the ACM, vol 42, no. 12, pp. 32-38.

Bigne, JE, Sanchez, MI & Sanchez, J 2001, ‘Tourism image, evaluation variables and after purchase behavior: inter-relationship’, Tourism Management, vol 22, no. 6, pp. 607-616.

Bowen, JT & Chen, S-L 2001, ‘The relationship between customer loyalty and customer satisfaction’, International journal of contemporary hospitality management, vol 13, no. 5, pp. 213-217.

Chow, H-S, Lau, VP, Lo, W-C, Sha, Z & Yun, H 2007, ‘Service quality in restaurant operations in China: decision-and experiential-oriented perspectives’, International Journal of Hospitality Management, vol 26, no. 3, pp. 698-710.

Churchill Jr, GA & Surprenant., C 1982, ‘An investigation into the determinants of customer satisfaction’, Journal of marketing research, pp. 491-504.

Crotts, JC 1999, ‘Consumer decision making and prepurchase information search’, Consumer behavior in travel and tourism, pp. 149-168.

Curasi, CF & Kennedy, KN 2002, ‘From prisoners to apostles: a typology of repeat buyers and loyal customers in service businesses’, Journal of Services Marketing, vol 16, no. 4, pp. 322-341.

Danaher, PJ & Mattsson, J 1994, ‘Customer satisfaction during the service delivery process’, European Journal of Marketing, vol 28, no. 5, pp. 5-16.

Dube, L, Renaghan, LM & Miller, JM 1994, ‘Measuring customer satisfaction for strategic management’, Cornell Hotel and Restaurant Administration Quarterly, vol 35, pp. 39-39.

Fornell, C 1992, ‘A national customer satisfaction barometer: the Swedish experience’, The Journal of Marketing, pp. 6-21.

Fornell, CMDJ, Anderson, EW, Cha, J & Bryant, BE 1996, ‘The American customer satisfaction index: nature, purpose, and findings’, The Journal of Marketing, pp. 7-18.

Hallowell, R 1996, ‘The relationships of customer satisfaction, customer loyalty, and profitability: an empirical study’, Emerald, vol 7.

Hellier, PK, Geursen, GM, Carr, RA & Rickard, JA 2003, ‘Customer repurchase intention: A general structural equation model’, European Journal of Marketing, vol 37, no. 11, pp. 1762-1800.

Hennig‐Thurau, T & Klee, 1998, ‘The impact of customer satisfaction and relationship quality on customer retention: A critical reassessment and model development’, Psychology & Marketing, vol 14, no. 8, pp. 737-764.

Jiang, P & Rosenbloom, B 2005, ‘Customer intention to return online: price perception, attribute-level performance, and satisfaction unfolding over time’, European Journal of Marketing, vol 39, no. 1/2, pp. 150-174.

Kim, WG & Kim, H-B 2004, ‘Measuring Customer-Based Restaurant Brand Equity’, Cornell Hospitality Quarterly, vol 45, no. 2, pp. 115-131.

Kim, WG, Ng, CYN & Kim, Y-S 2009, ‘Influence of institutional DINESERV on customer satisfaction, return intention, and word-of-mouth’, International Journal of Hospitality Management, vol 28, no. 1, pp. 10-17.

Kivela, JJ 1997, ‘Restaurant marketing: selection and segmentation in Hong Kong’, International Journal of Contemporary Hospitality Management, vol 9, no. 3, pp. 116 – 123.

Lynn, M 2001, ‘Restaurant Tipping and Service Quality: A Tenuous Relationship’, Cornell Hotel and Restaurant Administration Quarterly 2001; 42; 14, vol 42, no. 1, pp. 14-20.

Matzler, K, Bailom, F, Hinterhuber, HH, Renzl, B & Pichler, J 2004, ‘The asymmetric relationship between attribute-level performance and overall customer satisfaction: a reconsideration of the importance-performance analysis’, Industrial Marketing Management, vol 33, no. 4, pp. 271-277.

McCollough, MA, Berry, LL & Yadav., MS 2000, ‘An Empirical Investigation of Customer Satisfaction after Service Failure and Recovery’, Journal of service research, vol 3, no. 2, pp. 121-137.

McDougall, GH & Levesque, T 2000, ‘Customer satisfaction with services: putting perceived value into the equation’, Journal of services marketing, vol 14, no. 5, pp. 392-410.

Mittal, V & Kamakura, WA 2001, ‘Satisfaction, repurchase intent, and repurchase behavior: investigating the moderating effect of customer characteristics’, Journal of Marketing Research, pp. 131-142.

Oh, H 1999, ‘Service quality, customer satisfaction, and customer value: A holistic perspective’, Hospitality Management, vol 18, pp. 67-82.

Peterson, RA & Wilson, WR 1991, ‘Measuring customer satisfaction: Fact and artifact’, Journal of the Academy of Marketing Science, vol 20, no. 1, pp. 61-71.

Rust, RT & Zahorik, AJ 1993, ‘Customer satisfaction, customer retention, and market share’, Journal of retailing, vol 69, no. 2, pp. 193-215.

Sharp, B & Sharp, 1997, ‘Loyalty programs and their impact on repeat-purchase loyalty patterns’, International Journal of Research in Marketing, vol 14, no. 5, pp. 473-486.

Skogland, I & Siguaw, JA 2004, ‘Are your satisfied customers loyal?’, Cornell Hotel and Restaurant Administration Quarterly, vol 45, no. 3, pp. 221-234.

Smith, AK, Bolton, RN & 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.

Snyder, DR 1992, ‘Demographic correlates to loyalty infrequently purchased consumer services’, Journal of Professional Services Marketing, vol 8, no. 1, pp. 45-56.

Soriano, DR 2002, ‘Customers’ expectations factors in restaurants: The situation in Spain’, International Journal of Quality & Reliability Management, vol 19, no. 8/9, pp. 1055-1067.

Sulek, JM & Hensley, RL 2007, ‘The Relative Importance of Food, Atmosphere, and Fairness of Wait: The Case of a Full-service Restaurant’, Cornell Hospitality Quarterly, vol 45, no. 3, pp. 235-247.

Tarn, JL 1999, ‘The effects of service quality, perceived value and customer satisfaction on behavioral intentions’, Journal of Hospitality & Leisure Marketing, vol 6, no. 4, pp. 31-43.

Victorino, L, Verma, R, Plaschka, G & Dev, C 1991, ‘Service innovation and customer choices in the hospitality industry’, Managing Service Quality, vol 15, no. 6, pp. 555 – 576.

Weiss, R, Feinstein, AH & Dalbor, M 2005, ‘Customer satisfaction of theme restaurant attributes and their influence on return intent’, Journal of Foodservice Business Research, vol 7, no. 1, pp. 23-41.

White, L & Yanamandram, V 2004, ‘Why customers stay: reasons and consequences of inertia in financial services’, Managing Service Quality, vol 14, no. 2/3, pp. 183-194.

Woodside, AG, Frey, LL & Daly, RT 1989, ‘Linking service quality, customer satisfaction, and behavioral intention’, Journal of Health Care Marketing, vol 9, no. 4, pp. 5-17.

Woodside, AG, Frey, LL & Daly, RT 1989, ‘Linking service quality, customer satisfaction, and behavioral intention’, Journal of Health Care Marketing, vol 9, no. 4, pp. 5-17.

This essay on Santa Fe Grill Restaurant’s Customer Analysis was written and submitted by your fellow student. You are free to use it for research and reference purposes in order to write your own paper; however, you must cite it accordingly.
Removal Request
If you are the copyright owner of this paper and no longer wish to have your work published on IvyPanda.
Request the removal

Need a custom Essay sample written from scratch by
professional specifically for you?

Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar

certified writers online

GET WRITING HELP
Cite This paper

Select a referencing style:

Reference

IvyPanda. (2021, February 14). Santa Fe Grill Restaurant's Customer Analysis. Retrieved from https://ivypanda.com/essays/santa-fe-grill-restaurants-customer-analysis/

Work Cited

"Santa Fe Grill Restaurant's Customer Analysis." IvyPanda, 14 Feb. 2021, ivypanda.com/essays/santa-fe-grill-restaurants-customer-analysis/.

1. IvyPanda. "Santa Fe Grill Restaurant's Customer Analysis." February 14, 2021. https://ivypanda.com/essays/santa-fe-grill-restaurants-customer-analysis/.


Bibliography


IvyPanda. "Santa Fe Grill Restaurant's Customer Analysis." February 14, 2021. https://ivypanda.com/essays/santa-fe-grill-restaurants-customer-analysis/.

References

IvyPanda. 2021. "Santa Fe Grill Restaurant's Customer Analysis." February 14, 2021. https://ivypanda.com/essays/santa-fe-grill-restaurants-customer-analysis/.

References

IvyPanda. (2021) 'Santa Fe Grill Restaurant's Customer Analysis'. 14 February.

More related papers
Psst... Stuck with your
assignment? 😱
Hellen
Online
Psst... Stuck with your assignment? 😱
Do you need an essay to be done?
What type of assignment 📝 do you need?
How many pages (words) do you need? Let's see if we can help you!