Market Research For Retail Surge Company

Problem definition

The business world has in the recent past been dogged by myriad of problems ranging from global inflation to high level competition. Industries have been growing big due to new entrants in the market. This has posed great challenges in in terms of competition. Due to this, various businesses have embraced various methods to keep their businesses afloat. This include having to introduce online platforms where customers can view and by goods online. Some companies have reverted to doing research about the market trends so as to understand the trends in the market and adapt.

Things have not been different for Retail Surge Company, an online company dealing in clothes and footwear for boys and girls and men and women. Retail Surge also deals in customisation, accessories and sports equipment. Due to low sales and dwindling profit margins, the company decided to conduct a market research by conducting data from customers with an aim of analysing it and drawing important information to guide their business.

• The product category is made the most profit

To give information about the product category that made the most profit at Retail Surge, the appropriate bar graphs were employed to visually present the product and the amount of each.

• Product category that cost the most

To give information about the product category that cost most, at Retail Surge, the appropriate bar graphs were employed to visually present the product and the amount of each.

• Is there a difference in payment methods?

Since is a test for difference in means, an inferential statistics was employed. Independent t-test was employed since the test was being conducted between two variables. Test for difference between two independent variables use independent t-test. The two variables were the two methods of payments which were PayPal and credit card.

• Are there any differences in the user groups on all of the customer attitudes? (6 outcomes)

Since is a test for difference in means, an inferential statistics was employed. Analysis of variance (ANOVA) was employed since the test was being conducted among more 3 variables. Test for difference between three independent variables uses ANOVA. The three variables were light users, medium users and heavy users.

• Are there any differences in gender on all of the customer attitudes?

Since is a test for difference in means, an inferential statistics was employed. Independent t-test was employed since the test was being conducted between two variables. Test for difference between two independent variables use independent t-test. The two variables were the male and the females.  

Figure 1

Figure 1 above is a bar chart showing the mean total profit of different products sold by Retail Surge. The product which fetched the highest profit was the customised products ($ 25). The second best product in terms of mean profit was men’s shoes ($15.5). The product that fetched the least profit was boys clothing.

Figure 2

Figure 2 above is a bar chart showing the mean cost of goods at Retail Surge. The product which had the highest mean cost was the customised products ($9.9). The second costly product was girls’ shoes ($8). The product that was less costly was boys’ clothing.

Figure 3

The box-plots above show that 95% of the time, the mean total purchases paid by PayPal was between around 3.15 while the mean total purchases paid by credit card was between 3.3 and 4.0.

Descriptives
	N	Mean	Std. Deviation	Std. Error	95% Confidence Interval for Mean	Minimum	Maximum
Lower Bound	Upper Bound
Knowledge of the company	Light Users	104	2.85	1.711	.168	2.51	3.18	1	6
Medium Users	204	4.90	1.664	.116	4.67	5.13	2	7
Heavy Users	284	6.45	.601	.036	6.38	6.52	5	7
Total	592	5.28	1.840	.076	5.14	5.43	1	7
Satisfaction with the company	Light Users	104	2.54	1.157	.113	2.31	2.76	1	6
Medium Users	204	5.39	1.033	.072	5.25	5.53	2	7
Heavy Users	284	6.07	.776	.046	5.98	6.16	2	7
Total	592	5.22	1.585	.065	5.09	5.34	1	7
Preference for Nike	Light Users	104	2.46	1.507	.148	2.17	2.75	1	6
Medium Users	204	2.82	1.572	.110	2.61	3.04	1	5
Heavy Users	284	4.45	1.654	.098	4.26	4.64	1	7
Total	592	3.54	1.826	.075	3.39	3.69	1	7
Purchase Intention for Nike	Light Users	100	4.16	1.835	.184	3.80	4.52	1	7
Medium Users	204	4.04	1.893	.133	3.78	4.30	2	7
Heavy Users	284	5.01	1.195	.071	4.87	5.15	3	7
Total	588	4.53	1.648	.068	4.40	4.66	1	7
Would recommend company to a friend	Light Users	104	3.46	1.131	.111	3.24	3.68	2	6
Medium Users	204	4.92	.494	.035	4.85	4.98	4	6
Heavy Users	284	6.35	.477	.028	6.29	6.40	6	7
Total	592	5.35	1.260	.052	5.25	5.45	2	7
Loyalty for Nike	Light Users	104	3.92	1.499	.147	3.63	4.21	2	6
Medium Users	204	4.14	1.563	.109	3.92	4.35	2	6
Heavy Users	284	3.92	1.575	.093	3.73	4.10	2	7
Total	592	3.99	1.559	.064	3.87	4.12	2	7

Analysis and Results

Test of Homogeneity of Variances
	Levene Statistic	df1	df2	Sig.
Knowledge of the company	Based on Mean	137.679	2	589	.000
Based on Median	43.167	2	589	.000
Based on Median and with adjusted df	43.167	2	366.541	.000
Based on trimmed mean	130.226	2	589	.000
Satisfacition with the company	Based on Mean	34.012	2	589	.000
Based on Median	19.318	2	589	.000
Based on Median and with adjusted df	19.318	2	543.743	.000
Based on trimmed mean	28.470	2	589	.000
Preference for Nike	Based on Mean	3.007	2	589	.050
Based on Median	2.032	2	589	.132
Based on Median and with adjusted df	2.032	2	534.316	.132
Based on trimmed mean	3.259	2	589	.039
Purchase Intention for Nike	Based on Mean	51.499	2	585	.000
Based on Median	48.655	2	585	.000
Based on Median and with adjusted df	48.655	2	555.807	.000
Based on trimmed mean	49.574	2	585	.000
Would recommend company to a friend	Based on Mean	155.697	2	589	.000
Based on Median	75.229	2	589	.000
Based on Median and with adjusted df	75.229	2	489.408	.000
Based on trimmed mean	152.051	2	589	.000
Loyalty for Nike	Based on Mean	.438	2	589	.645
Based on Median	1.134	2	589	.322
Based on Median and with adjusted df	1.134	2	466.890	.323
Based on trimmed mean	.333	2	589	.717

Table 1

Homogeneity of variance test was employed to test whether there was equality of variance in customer attitudes. The null hypothesis in this test maintains equality of variance (Derrick, Toher, & White, 2017). Three attitudes; satisfaction with the company, purchase intention for Nike and knowledge with the company had p-values equal to 0.00 which is less than level of significance 0.05. This means that null hypothesis is violated in all the three attitudes thus it is concluded that at least one item has a different mean. On the other hand, under loyalty for Nike, the p-values (0.64) was greater than level of significance 0.05. The alternative hypothesis is accepted thus it is concluded that at least one variance is different (Leigh, 2008). ANOVA
	Sum of Squares	df	Mean Square	F	Sig.
Knowledge of the company	Between Groups	1034.437	2	517.218	315.401	.000
Within Groups	965.888	589	1.640
Total	2000.324	591
Satisfaction with the company	Between Groups	959.259	2	479.630	538.032	.000
Within Groups	525.065	589	.891
Total	1484.324	591
Preference for Nike	Between Groups	461.224	2	230.612	89.966	.000
Within Groups	1509.803	589	2.563
Total	1971.027	591
Purchase Intention for Nike	Between Groups	129.379	2	64.690	25.830	.000
Within Groups	1465.070	585	2.504
Total	1594.449	587
Would recommend company to a friend	Between Groups	692.399	2	346.199	829.181	.000
Within Groups	245.919	589	.418
Total	938.318	591
Loyalty for Nike	Between Groups	6.460	2	3.230	1.331	.265
Within Groups	1429.513	589	2.427
Total	1435.973	591

Table 2

1. Attitude 1: Knowledge of the company

The test found the p-value (0.00) to be less than the level of significance (0.05). The conclusion then is, not all the means are equal

Attitude 2: Satisfaction with the company

The test found the p-value (0.00) to be less than the level of significance (0.05). The conclusion then is, not all the means are equal (Howell, 2007).

1. Attitude 3: Preference for Nike

The test found the p-value (0.00) to be less than the level of significance (0.05). The conclusion then is, not all the means are equal

1. Attitude 4: Purchase intention for Nike

The test found the p-value (0.00) to be less than the level of significance (0.05). The conclusion then is, not all the means are equal (Hinkelmann & Kempthorne, 2010).

1. Attitude 5: Would recommend company to a friend?

The test found the p-value (0.00) to be less than the level of significance (0.05). The conclusion then is, not all the means are equal

1. Attitude 6: Loyalty for Nike

The test found the p-value (0.27) to be greater than the level of significance (0.05). The conclusion then is, all the means are equal (Gelman, 2005).  

Multiple Comparisons
Bonferroni
Dependent Variable	(I) Webiste User Group	(J) Webiste User Group	Mean Difference (I-J)	Std. Error	Sig.	95% Confidence Interval
Lower Bound	Upper Bound
Knowledge of the company	Light Users	Medium Users	-2.056*	.154	.000	-2.43	-1.69
Heavy Users	-3.605*	.147	.000	-3.96	-3.25
Medium Users	Light Users	2.056*	.154	.000	1.69	2.43
Heavy Users	-1.549*	.118	.000	-1.83	-1.27
Heavy Users	Light Users	3.605*	.147	.000	3.25	3.96
Medium Users	1.549*	.118	.000	1.27	1.83
Satisfaction with the company	Light Users	Medium Users	-2.854*	.114	.000	-3.13	-2.58
Heavy Users	-3.532*	.108	.000	-3.79	-3.27
Medium Users	Light Users	2.854*	.114	.000	2.58	3.13
Heavy Users	-.678*	.087	.000	-.89	-.47
Heavy Users	Light Users	3.532*	.108	.000	3.27	3.79
Medium Users	.678*	.087	.000	.47	.89
Preference for Nike	Light Users	Medium Users	-.362	.193	.183	-.83	.10
Heavy Users	-1.989*	.184	.000	-2.43	-1.55
Medium Users	Light Users	.362	.193	.183	-.10	.83
Heavy Users	-1.627*	.147	.000	-1.98	-1.27
Heavy Users	Light Users	1.989*	.184	.000	1.55	2.43
Medium Users	1.627*	.147	.000	1.27	1.98
Purchase Intention for Nike	Light Users	Medium Users	.121	.193	1.000	-.34	.58
Heavy Users	-.854*	.184	.000	-1.30	-.41
Medium Users	Light Users	-.121	.193	1.000	-.58	.34
Heavy Users	-.975*	.145	.000	-1.32	-.63
Heavy Users	Light Users	.854*	.184	.000	.41	1.30
Medium Users	.975*	.145	.000	.63	1.32
Would recommend company to a friend	Light Users	Medium Users	-1.455*	.078	.000	-1.64	-1.27
Heavy Users	-2.887*	.074	.000	-3.06	-2.71
Medium Users	Light Users	1.455*	.078	.000	1.27	1.64
Heavy Users	-1.432*	.059	.000	-1.57	-1.29
Heavy Users	Light Users	2.887*	.074	.000	2.71	3.06
Medium Users	1.432*	.059	.000	1.29	1.57
Loyalty for Nike	Light Users	Medium Users	-.214	.188	.763	-.66	.24
Heavy Users	.008	.179	1.000	-.42	.44
Medium Users	Light Users	.214	.188	.763	-.24	.66
Heavy Users	.222	.143	.364	-.12	.57
Heavy Users	Light Users	-.008	.179	1.000	-.44	.42
Medium Users	-.222	.143	.364	-.57	.12
*. The mean difference is significant at the 0.05 level.

Table 3

Difference in mean for light, medium and heavy users

Hypothesis

The test found the p-value (0.00) to be less than the level of significance (0.05). The conclusion then is, not all the means are equal

However for Nike products, the hypothesis and conclusion was as below;

The test found the p-value (0.27) to be greater than the level of significance (0.05). The conclusion then is, all the means are equal.

Group Statistics
	Gender	N	Mean	Std. Deviation	Std. Error Mean
Knowledge of the company	Female	388	5.02	1.961	.100
Male	204	5.78	1.463	.102
Satisfaction with the company	Female	388	5.18	1.595	.081
Male	204	5.29	1.567	.110
Preference for Nike	Female	388	3.19	1.876	.095
Male	204	4.22	1.516	.106
Purchase Intention for Nike	Female	388	4.67	1.619	.082
Male	200	4.26	1.675	.118
Loyalty for Nike	Female	388	3.44	1.588	.081
Male	204	5.04	.768	.054
Would recommend company to a friend	Female	388	5.40	1.255	.064
Male	204	5.25	1.267	.089

Table 4

Independent Samples Test
	Levene’s Test for Equality of Variances	t-test for Equality of Means
F	Sig.	t	df	Sig. (2-tailed)	Mean Difference	Std. Error Difference	95% Confidence Interval of the Difference
Lower	Upper
Knowledge of the company	Equal variances assumed	56.606	.000	-4.892	590	.000	-.764	.156	-1.070	-.457
Equal variances not assumed			-5.347	522.857	.000	-.764	.143	-1.044	-.483
Satisfaction with the company	Equal variances assumed	.024	.877	-.867	590	.386	-.119	.137	-.388	.150
Equal variances not assumed			-.872	419.112	.384	-.119	.136	-.387	.149
Preference for Nike	Equal variances assumed	14.901	.000	-6.765	590	.000	-1.030	.152	-1.329	-.731
Equal variances not assumed			-7.223	493.730	.000	-1.030	.143	-1.310	-.750
Purchase Intention for Nike	Equal variances assumed	2.724	.099	2.876	586	.004	.410	.143	.130	.690
Equal variances not assumed			2.845	390.123	.005	.410	.144	.127	.694
Loyalty for Nike	Equal variances assumed	246.135	.000	-13.543	590	.000	-1.596	.118	-1.827	-1.364
Equal variances not assumed			-16.471	586.589	.000	-1.596	.097	-1.786	-1.406
Would recommend company to a friend	Equal variances assumed	.157	.692	1.442	590	.150	.157	.109	-.057	.371
Equal variances not assumed			1.437	409.319	.151	.157	.109	-.058	.372

Table 5

• Test for equality of variance in attitude (knowledge of the company) between male and female

Hypothesis

H₀: Variance₁ = Variance₂

Versus

H₁: Variance₁ ≠ Variance₂

The test found the p-value (0.00) to be less than the level of significance (0.05). The conclusion then is, there is a significant difference in the two variances.

• Test for equality of variance in attitude (satisfaction with the company) between male and female

Hypothesis

H₀: Variance₁ = Variance₂

Versus

H₁: Variance₁ ≠ Variance₂

The test found the p-value (0.27) to be greater than the level of significance (0.05). The conclusion then is, all the means in attitude levels between the males and females are equal.

• Test for equality of variance in attitude (preference for Nike) between male and female

Hypothesis

H₀: Variance₁ = Variance₂

Versus

H₁: Variance₁ ≠ Variance₂

The test found the p-value (0.00) to be less than the level of significance (0.05). The conclusion then is, there is a significant difference in the two variances.

• Test for equality of variance in attitude (purchase intention for Nike) between male and female

Hypothesis

H₀: Variance₁ = Variance₂

Versus

H₁: Variance₁ ≠ Variance₂

The test found the p-value (0.00) to be less than the level of significance (0.05). The conclusion then is, there is a significant difference in the two variances.

• Test for equality of variance in attitude (loyalty for Nike) between male and female

Hypothesis

H₀: Variance₁ = Variance₂

Versus

H₁: Variance₁ ≠ Variance₂

The test found the p-value (0.00) to be less than the level of significance (0.05). The conclusion then is, there is a significant difference in the two variances.

• Test for equality of variance in customer attitude (would recommend company to a friend) between male and female

Hypothesis

H₀: Variance₁ = Variance₂

Versus

H₁: Variance₁ ≠ Variance₂

The p-value calculated (0.15) is great compared to the alpha value (0.05). This means that null hypothesis is accepted thus equality of variance in attitude levels between the males and females.

One sample t-test for the mean satisfaction level (3.5)

Hypothesis

H₀: µ = 3.5

Versus

H₁: µ ≠ 3.5

Test results table is as shown below

One-Sample Statistics
	N	Mean	Std. Deviation	Std. Error Mean
Satisfaction with the company	592	5.22	1.585	.065

Table 6

One-Sample Test
	Test Value = 3.5
t	df	Sig. (2-tailed)	Mean Difference	95% Confidence Interval of the Difference
Lower	Upper
Satisfaction with the company	26.349	591	.000	1.716	1.59	1.84

Table 7

Since the p-value calculated (0.00) is less compared to the alpha value (0.05). This means that null hypothesis is not accepted thus the mean satisfaction level is not 3.5.

The research team found many revelations from the data analysis results. The product which fetched the highest profit was the customised products ($ 25). The second best product in terms of mean profit was men’s shoes ($15.5). The product that fetched the least profit was boys clothing. To add on, the product which had the highest mean cost was the customised products ($9.9). The second costly product was girls’ shoes ($8). The product that was less costly was boys’ clothing. The research also found that there was no significant difference in the attitude levels between males and females.

Reference

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

Gelman, A. (2005). Analysis of variance? Why it is more important than ever. The anals of Statistics, 33, 1 – 53.

Hinkelmann, K., & Kempthorne, O. (2010). Design and analysis of experiments (5 ed., Vol. 8).

Howell, D. C. (2007). Statistical methods for Psychology (3 ed., Vol. 5).

Leigh, E. S. (2008). Consumer rites. Selling of American Holidays, 6(3), 106 – 191.