Customer Satisfaction Survey Of Woolworths: Results And Analysis

Overview of the Survey Design and Data Collection Process

This report gives a rundown of the reasons, the procedure and the consequences of the customer fulfilment review for the Woolworths. Woolworths is Australia’s biggest market chain. The chain operates 995 stores crosswise over Australia and it depends on the 115,000 colleagues in stores, distribution centres and bolster workplaces to furnish their clients with unrivalled administration, range, esteem and comfort (Croy, 2015). The review is one means through which Woolworths can give a voice to their customers. It is a systematic approach to recognize what is working and what should be enhanced from the customers’ vantage point. This particular survey was performed based on the following reasons which also guided the design and construct of the survey.

• To report where customers are fulfilled alongside where they are disappointed and to recognize what gaps makes customers to be disappointed.
• To discover what changes are imperative to customers.
• To utilize this information to organize the continuous change activities that will make it for the Woolworth customers save on time.

A definitive objective is to give an astounding customer services as well as business needs of the Woolworths. In the close term the objective is to enhance the customers’ capacity to utilize Woolworth’s items.

This section presents the method and procedure utilized in this study, as follows: 1) sample selection, 2) survey instrument, 3) data collection, 4) data analysis, and 5) limitations.

The population in this study was customers leaving the Woolworth stores in Sydney. The sample size of 20 was set for the survey. The researcher administered the questionnaires to the customers leaving the stores.

To test the objectives of the study, a survey was used to collect data for the study (Saris & Gallhofer, 2014). A self-administrated survey was used on a sample of Woolworth customers. The survey was comprised of 10 close ended questions. The questionnaire has been attached in appendix A1.

The potential participants were given a set of questionnaire to fill. The questionnaires were estimated to take not more than 5 minutes to be filled. A participation consent form was attached to each survey to explain the purpose of the study, that their participation in this research was voluntary and anonymous, and that there was no risk and harm to completing a survey. To increase the return rate of the survey, the researcher stayed not far away from where the participants were filling in the forms.

Data was entered and analysed through the Data Analysis Add in option found in excel. With the Pivot tables from excel, the frequencies of respondents were tabulated. In this research, Chi-Square test of association as well as t-test was employed by the researcher to verify the hypothesis.

Two main limitations were identified in this study. These challenges/limitations are:

1. A small sample size that is not representative was used for this study; this means that the results of this study cannot be generalized for the whole population. In addition, the data collection was only done in one city only making it hard to understand the felling of customers from other cities
2. Random sampling was not possible in this case; the researcher mostly relied on convenience where participants who seemed to be willing to participate were selected to participate.

Numerical Analysis of Customer Spending and Demographic Information

In order to clearly understand and analyze customer’s characteristics, it is recommended that the researcher gathers basic demographic data such as age, gender as well as income of the customers (Harry , 2006). It is on this premise that we generated the demographic profile of the customers interviewed.

There were 6 males (30%), and 14 females (70%) customers participating in this study, as illustrated in figure 1.

Figure 1: Bar chart of gender

From the 20 respondents, the age groups of the respondents as per the five age groups is presented in Table 1. As can be seen, majority (30%, n = 6) of the participants were aged below 30 years old. Exactly 75% (n = 15) of the respondents were aged 50 years and below.

Table 1: Age group of the customers interviewed

From a total of 20 respondents, majority (40%, n = 8) reported an annual income less than $50,000 while 25% (n = 5) reported annual household income in excess of $90,000 a year. The tabulation of annual household income is presented in Table 2.

Figure 2: Bar chart of income levels

Table 2: Frequency table for the income level

Participants were asked to state the frequency of their visits to the store in a month. Majority of them visit less than 3 times in a month while 45% (n = 9) visit more than 3 times a month.

Table 3: Frequency of visits

In terms of manner of doing the shopping, most customers (50%, n = 10) would prefer online shopping, 35% (n = 7) would prefer walk through to store while only 15% (n = 3)

Table 4: Preferred shopping method

Participants were asked to state which of the five products they spend most on. Majority (30%, n = 6) said to spend most on bread, drinks was the least (10%, n = 2), fruits was 25% (n = 5) while vegetables and meat took 20% (n = 4) and 15% (n = 3) respectively.

Table 5: Product spent most on

65% of the participants believe that the stores are clean while 25% (n = 5) believe the stores are not clean and 10% (n = 2) believe some of them are clean.

Table 6: Opinion on Cleanliness and organization of stores

In overall, 60% (n = 12) of the participants said to be very satisfied with the Woolworth services, 30% (n = 6) were moderately satisfied while those who were either not satisfied or greatly unsatisfied were 5% each

Results of Hypothesis Tests

Table 7: Overall satisfaction levels

In this section we provide the numerical analysis of the amount of money spent on every visit to the store. Table 3 below gives the descriptive statistics. The computations of the statistics presented in the table is shown in the appendix A2.

Table 8: Descriptive Statistics

As can be seen, on average the participants in the study said to spend $107.75 every time they visit the store with a median spending being $100. The maximum and the minimum amount spent by the customers on every visit to the store was $200 and $50 respectively.

We also computed the 95% confidence interval, from our results we are 95% confident that the true mean spending on every visit to the store is between $87.4731 and $132.0269.

We tested two hypothesis in this study. The first hypothesis test was performed on the sample data to test whether the recommendation rating of the Woolworth varied between the males and the females. An independent samples t-test was done to compare the mean recommendation rating (John , 2006). Results showed that the males (M = 3.33, SD = 1.86, N = 6) had no significant difference in terms of the recommendation rating when compared to the females (M = 3.86, SD = 1.17, N = 14), t (18) = -0.769, p > .05, two-tailed. The difference of 0.5238 showed an insignificant difference. Essentially results showed that the recommendation rating for the Woolworth between the male and female participants did not vary.  

Table 9: t-Test: Two-Sample Assuming Equal Variances

The second hypothesis test was conducted on the sample data to test whether the average spending varied between the males and the females. An independent samples t-test was done to compare the mean spending for every visit to the Woolworth stores (Derrick, et al., 2017). Results showed that the males (M = 163.33, SD = 47.61, N = 6) had significant difference in terms of the mean spending for every visit to the Woolworth stores when compared to the females (M = 83.93, SD = 32.00, N = 14), t (18) = 4.398, p < .05, two-tailed. The difference of 79.40 showed a significant difference. Essentially results showed the male participants on average spend on whenever they visit the Woolworth stores as compared to the female participants.  

Conclusion

This report sought to analyse the customer satisfaction of the Woolworth customers with an aim of informing the organization on the best practises they need to carry out as well as improvement measures that the organization needs to put in place. A total of 20observations (customers) were analysed. Results revealed that on average the participants in the study spend $107.75 every time they visit the store with a median spending being $100. The maximum and the minimum amount spent by the customers on every visit to the store was $200 and $50 respectively. Majority of the customers (50%, n = 10) would prefer online shopping, 35% (n = 7) would prefer walk through to store while only 15% (n = 3). A significant proportion of participants felt that the stores are not clean and organized.

There was no difference in terms of recommendation rating by the males and the female participants however, male participants were found to spend significantly more as compared to the females whenever they visit the stores.

Based on the findings of this study, the management of the stores needs to make some drastic adjustments in order to ensure their stores remain the only choice among its customers and probably attract more customers.

• Focus on organization and cleanliness of the stores; it came out that 25% of the participants had a feeling that the stores are not clean and organized, the management needs to take key initiative to ensure that this is sorted out in all its stores.
• It was established that male participants spend more than the female despite the fact that many females visit the stores; the management should focus on bringing product that attract the female customers towards making purchases.

References

Andersson, K., Dickin, S. & Rosemarin, A., 2016. Towards “Sustainable” Sanitation: Challenges and Opportunities in Urban Areas. Sustainability, 8(12), p. 1289.

Anon., 2015. Woolies dumps flyer points.

Croy, L., 2015. Woolies dumps flyer points.

Derrick, B., Toher, D. & White, P., 2017. How to compare the means of two samples that include paired observations and independent observations. The Quantitative Methods for Psychology, 13(2), p. 120–126.

Harry , H., 2006. How effective are your community services?. Procedures for Performance Measurement.

John , A. R., 2006. Mathematical Statistics and Data Analysis.

Saris, W. E. & Gallhofer, I. N., 2014. Design, evaluation and analysis of questionnaires for survey research.

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