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Data Cleaning

The data cleaning process was conducted to remove the missing value cases, values that are considered to be out of range as well as for the identification.

The identification of the missing values is as summarised in the table format below;

Table 1: Missing values summary

The cases of missing values will be replaced using the data transformation function and the series mean method in SPSS.

In the identification of out of range values, no out of range data was found as illustrated by the table 2 below;

Table 2: Identification of out of range values

Description of the Demographic Profile

The section below outlines the description of the demographic profile of the participants whose data was collected.

Table 3: descriptive for demographic profile

From table 3 above, the mean age of the participant was 3.97 with a standard deviation of 1.470. The same descriptive are outlined for sex (M=1.88, SD = 0.340), as well as occupation (M=3.37, SD =1.668).

Table 4: gender distribution

From the gender distribution in table 4 above, majority of the participants were female represented by 87.9 percent (n=197) whereas the male gender was represented by 11.6 percent (n=27). The gender distribution of the correspondents is further illustrated by figure 1below;

Figure 1: A histogram showing the overall distribution of the sex of the research participants

 Please indicate your age group: Frequency Percent Valid Percent Cumulative Percent Valid 18-24 12 5.4 5.4 5.4 25-34 31 13.8 13.9 19.3 35-44 36 16.1 16.1 35.4 45-54 59 26.3 26.5 61.9 55-64 42 18.8 18.8 80.7 65+ 43 19.2 19.3 100.0 Total 223 99.6 100.0 Total 224 100.0

The age distribution of the participants is shown in the table above. The majority of the participants were in the 45-54 age group represented by 26.3 percent. Those in the 18-24 age group were the least represented by 5.4 percent (n=12). The distribution above is further illustrated in the form of the histogram below;

Figure 2: Histogram showing the age distribution of the participants

The histogram in figure 1 above shows that the majority of the correspondents were old whereas only a small proportion formed the younger generation.

Table 5: occupation distribution

 Please indicate your occupation: Frequency Percent Valid Percent Cumulative Percent Valid Student 5 2.2 2.2 2.2 Working full time 95 42.4 42.6 44.8 Working part time 55 24.6 24.7 69.5 Unemployed 2 .9 .9 70.4 Stay at home parent 12 5.4 5.4 75.8 Retired 54 24.1 24.2 100.0 Total 223 99.6 100.0 Total 224 100.0

From table 5 above, the highest proportion of the correspondents indicated that they were working full time as represented by 42. 4 per cent (n=95). Only a small fraction said that they were unemployed whose proportion was 0.9 percent (n=2). The other least number of participants were those that indicated they were still learning (n=5) with stay at home parent consisting of 5.4 percent (n=12). The distribution is further illustrated by the graph in the figure below;

Description of the Demographic Profile

Figure 3: A histogram showing the distribution of the occupation of the correspondents

Evaluation of the Stirling Store Performance Based on Customers’ Perceptions

The assessment herein utilised the variables that showed how the customers perceived the Stirling store. The performance was measured with reference to the visit frequency. The outcome of the regression is as delineated below;

Table 6: model summary for linear regression

From table 6 above, 5.3 per cent of the outcome is explained by the variables.

Table 7: ANOVA output

The table of ANOVA above shows the ANOVA output of the linear regression. There is positive significant association between the perception of the correspondents of their experience during their visit and their frequency of their visitation. That is F (5,218) = 2.418, p = 0.037. The correlation between these variables is as shown below;

Table 8: correlation between the perception variables

The happy variable is positively correlated to the pleased/annoyed attribute (r =0.852, 99CI), satisfied variable (r=0.785, 99 CI), I enjoyed my visit (r = 0.776, 99CI), I had fun (r =0.522, 99 CI). Scale reliability analysis is as shown by the table below;

Table 9: Reliability Analysis

Table 10: overall reliability statistics

The reliability analysis is as shown in table 9 above. All the items concerning the perception of the research correspondents indicated an excellent value of Cronbach’s Alpha showing that the scale is reliable hence the generalizability of the analysis outcome. The overall value of Cronbach’s Alpha for the five attributes was equally excellent being 0.912.

Evaluation of the Stirling Store Performance by Different Demographic Groups

From the table above, there was no significant difference between the genders on their perception during the visitation. That is p>0.05. Analysing the product design, convenience, uniqueness, and price of the products in relation to the frequency of showing gives the result in the table below;

Customers’ Perceptions Regarding FLEEK’s Brand

From the table above, there is a significant association between the visit frequency variable and the dependent variable. That is F (17,198) = 1.828, p=0.027.

Customers’ Perceptions Regarding FLEEK’s Brand by Different Demographic Groups

Similarly, from the table above, there was no significant difference between the genders on the performance of FLEEK. That is p>0.05.

The Role of the Store in Enhancing FLEEK’s Brand

The efforts of the store to promote brand loyalty shows a positive significant association with reference to the sample mean that is p<0.05.

Evaluation of the Stirling Store Performance Based on Customers' Perceptions

Recommendations to the Stirling store manager and FLEEK’s central offices

The recommendations presented herein are with reference to the analyses that has been conducted in the section above.

The enterprise should consider adopting the competitive pricing strategy. In this regard the store should be committed to providing a fun and convenient shopping experience with access to unique and highly differentiated products at affordable prices. This includes working diligently to ensure that the prices are competitive by monitoring pricing trends and our competitive set???? (Guo, Choi, and Shen, 2020). If you find an identical qualifying item for less from another retailer, upon presentation of the ad, the store should be committed to matching the price. Low-price points are a major stumbling block for apparel retailers. They must be able to create enough product quickly to meet the surge in sales caused by new items, but can't afford to make concessions on quality or features. In reality, creating such items is not difficult. However, many apparel retailers are too afraid to price attractively – either because they don't want to be perceived as selling cheap knock-offs, or because they fear price wars with other manufacturers (Guo, Choi, and Shen, 2020). A logical policy for most retailers would be to price at about twice the highest competing item sold for that particular garment.

The store should also seek to further promote the brand loyalty of its products. Research consistently finds that approximately 90 percent of all new products fail within the first year (Andal, Bello, and Catelo, 2021). Failure rates are especially high for small firms, so marketing managers would be wise to take a closer look at their brand loyalty strategies. Brand loyalty is defined as the extent to which customers consistently purchase the same product instead of purchasing from its competitors. Consumers’ brand loyalty depends on price, availability, product usage and reasons for switching brands. A firm’s marketing plan must consider these factors and find ways to promote customer satisfaction, ensuring repeat purchases from loyal customers. The objectives of effective brand promotion are to improve your branding, increase awareness and maintain an ongoing relationship with customers. By promoting a positive experience that keeps customers coming back, you can retain them for long-term loyalty (Miguel, 2021). Consequently, the importance of brand loyalty cannot be underestimated. If you're beginning a new business, need to develop a marketing strategy or simply want to improve sales, the most important thing you can do is increase the number of loyal customers (Mostafa and Kasamani, 2020). Brand loyalty ensures repeat purchases from loyal customers. By finding ways to promote customer satisfaction, the store’s marketing plan can remain competitive and profitable in the industry marketplace.

Customers' Perceptions Regarding FLEEK’s Brand

The enterprise should direct its efforts towards research and development with an aim of promoting uniqueness of its products. Research and development refers to the process of creating new products, processes or services. Generally, research and development aims to increase knowledge, develop new processes or products, or advance society in some way. There are few advantages of having sufficient research and development to promote product uniqueness. The first is that the uniqueness of products will bring more business. It is because the customers who like your products in the market will try their best to find this kind of products, which will bring more business. The second advantage is that you can enhance the competitiveness of your company in the market since your rivals or competitors cannot learn or steal your technology easily through business operations.

It is crucial for the store to leverage on the capacity of its human resource in promoting new design development and inventions. To encourage innovation, the store should make more of an effort to provide working conditions that are conducive to coming up with new products. Specifically, the store should offer employees a reasonable amount of space within which they can come up with solution to difficult problems. Additionally, the enterprise should allow employees time to work on their own projects rather than have them waste time writing bureaucratic reports, filling out paperwork. Lastly, the store should be clear with employees what the company wants them to do and communicate its expectations clearly and directly.

The store should adopt new technology to develop unique and competitive products. The apparel industry is in a protracted transition from traditional manufacturing to labour-intensive, flexible and sustainable methods of production. Conventional manufacturing involves an extended supply chain where vendors are typically responsible for inventory control and transportation, while retailers are responsible for distribution, product assortment and customer service.

The store should further build on its brand to encourage consumer purchase intentions. It is important to have a brand name in today's competitive world. Competent branding can make a good difference between your product and that of your competitor. Branding is what helps you sell the first time, but quality is what will help you to resell. If your products are sold, then you need one thing to get better revenues - loyalty and trust.

A unique selling proposition for the store to ensure convenience in shopping experience is to use the online platform to its advantage. So here is the company with a unique selling proposition to have a competitive edge: It should have the willingness and the capability to use e-commerce in a new way to reach out to the masses. It should not just sell ready made products online, it actually designs its dresses in such a way that they are reduced at 50% by cutting off unnecessary material and trimmed by knitting (Mohd Satar,  Dastane, and Ma’arif, 2019). This will make it a very economical since there is less waste and transportation cost. Moreover, this design takes into account their target audience; women typically wear loose clothing more often than not. They can be brought close onto their skin which avoids that awkward fit feeling of wearing clothes too large for you when you happen to be petite or have a small bust. At this point, it is feasible to assert that such type of e-commerce selling strategy works best with niche products (It has been noticed that people buy specific types of clothing rather than generic ones).

The store should adopt demographic segmentation and targeting in its promotional campaigns. Competitive edge is created when a company is better at providing a product or service than its competitors in the same industry. This means that the company that knows more about its target customer and what it wants, is able to provide a product or service with better value. Demographic segmentation is one of the simplest ways to market your apparel business. It’s also one of the most powerful ways. With demographic segmentation, you break your customers into important segments to understand their specific needs, behaviours and characteristics (Osei et al. 2021). The categories in this marketing strategy are the same ones from your census data: gender, age, income and education. The fashion industry is an extremely competitive business filled with talented, creative people who set styles and trends. As new garments are designed and brought to the marketplace, there are many players who have roles in getting the finished product to the consumer. Because of such a complicated process in getting clothing to market, the apparel industry is broken into segments that focus on designing, manufacturing or retailing clothing.

References

Andal, E.G., Bello, A. and Catelo, M.A., 2021. Coping and recovery strategies of MSMEs in the Laguna one year after COVID19. Philippine Review of Economics, 58(1&2), pp.241-263.

Guo, S., Choi, T.M. and Shen, B., 2020. Green product development under competition: A study of the fashion apparel industry. European Journal of Operational Research, 280(2), pp.523-538.

Miguel, E., 2021. Evidence on research transparency in economics. Journal of Economic Perspectives, 35(3), pp.193-214.

Mohd Satar, N.S., Dastane, O. and Ma’arif, M.Y., 2019. Customer value proposition for E-Commerce: A case study approach. International Journal of Advanced Computer Science and Applications (IJACSA), 10(2), pp.454-458.

Mostafa, R.B. and Kasamani, T., 2020. Brand experience and brand loyalty: is it a matter of emotions?. Asia Pacific Journal of Marketing and Logistics.

Osei, F., Ampomah, G., Kankam-Kwarteng, C., Bediako, D.O. and Mensah, R., 2021. Customer Satisfaction Analysis of Banks: The Role of Market Segmentation. Science Journal of Business and Management, 9(2), pp.126-138.

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