Statistical Analysis: How Sale Models
Change Consumer Buying Behavior
Quddus Syed*, Jyoti Choudhury and McHardy Dale
Assistant Professor, University of The Bahamas, Bahamas
Submission: March 24, 2023; Published: April 03, 2023
*Corresponding author: Quddus Syed, Assistant Professor, University of The Bahamas, UB│Oakes Field
P.O. Box N-4912 │Nassau, Bahamas
How to cite this article:Quddus S, Jyoti C, McHardy D. Statistical Analysis: How Sale Models Change Consumer Buying Behavior. Ann Soc Sci Manage Stud. 2023; 8(3): 555737. DOI: 10.19080/ASM.2023.08.555737
A statistical analysis is processed to systematically explain and evaluate how significantly consumer buying behavior is changed by applying different sale-promotion models. The data was collected by using a convenient sample technique through a questionnaire, floated on an online Google form survey to collect primary source of information based on Likert scale. The SPSS based statistical analysis methods, ‘Cronbach’s Alpha’ and ‘backward regression’ are ‘respectively used to check the reliability of data and to iteratively examine the statistical significance of the criterion and predictors relationship. By knowing the effect and significance of sales promotion tools it will be very beneficial and easy for promoters, marketers and consumers to choose and stimulate their selling and buying strategies respectively.
Researchers have shown limited preference to sales promotion methods. It is believed that the perception of consumers from specific premises and culture and respondents of a particular background is various on different sales promotions methods and consumers may change with possibilities of comparison and education . However, no study was found studying the impact of sales promotions on the consumer behavior with reference to the Bahamas supermarkets. The study contributes to the literature by providing the perceptions of consumers from specific premises and respondents of a particular background in the Bahamas context.
In past some studies have done in different areas by collecting random data from markets but in the present study, 65 respondents are from students and employees of the Business faculty at the University of Bahamas who participated. A regression model equation was developed for forecasting the consumer buying behavior based on sales promotion predictors ,‘price discount’, ‘free-sample’, ‘online sale’ and ‘buy one get one free offer’.
Keywords: Buy One Get One Free; Consumer-Behavior; Free Sample; Price Discounts; Online Sale; Regression; Econometric
A statistical analysis is carried out to analytically explain and evaluate how significantly consumer buying behavior is altered by applying various sale-promotion models. Sales Promotion in precise, is a technique used by marketers to inspire and stimulate consumers to purchase the promoted product . It is clearly from the definition that it is used to stimulate the consumers to accelerate their buying either in terms of time or amount. To motivate the customers, numerous types of monetary or non monetary benefits are offered to them. Salvi  tested various sales promotion techniques (discount, price-off, buy one get one) with respect to different consumer behavior variables (store visit, purchase and earlier purchase). Chaharsoughi, Yasory  studied “effect of Sales Promotion on Consumer Behavior based on culture”. Gilbert, Jackaria  examined the efficiency of sales promotion with reference to supermarkets of UK. The study
compared the performance of coupon, price discount, sample and buy-one get-one free. Shamsi, Khan  assessed the efficiency of Sales Promotion with respect to affecting various consumer behavior factors. Weerathunga, Pathmini  affirms that sales promotion methods have a meaningful correlation with customer buying behavior. Offer, premium and contest significantly influence consumer buying decision . Chakrabortty et al.  advises that sales promotion is more effective than advertisement. Researchers have shown limited preference to sales promotion methods and statistical analysis techniques. However, no study was found studying the impact of sales promotions with reference to the Bahamas concentrating on consumer buying behavior.
To collect data for this research, the questionnaire was
floated to the respondents to know their buying behavior towards
sales promotion activities. We used a Likert scale to quantify
the level of consent and disagreement of each respondent on a
certain parameter. The statistical analysis methods, ‘Cronbach’s
Alpha’ and ‘backward regression’ are ‘respectively used to check
the reliability of data and to iteratively examine the statistical
significance of the criterion and predictors relationship. Most of
studies showed that Cronbach Alpha technique is used to check
the reliability of data.
We start our data analysis with demographic analysis of
respondents. The sample data characteristics are shown in Table
1, 31 % of respondents were male, while 69 % were female. 15%
of respondents were employees of Business faculty, while 85%
were students. In terms of age, 58% were between 18-24 years,
26% were between 25-29 years old, 6% were between 30-34
years, 5% between 35-39%, and 5% student was above 40 years.
We performed Cronbach’s alpha test for measuring reliability
of the scales for the five variables used in the study; ‘price discount’,
‘free-sample’, and ‘buy one get one free offer’, and ‘consumer
buying behaviour’. The results are shown in Table 2. Since the
cut off for Cronbach’s alpha is 0.7 , reliability statistics from the
data collected for our study results in value for each variable in
the range of 0.778 – 0.892 . This means the questionnaire is
To know the value of the coefficients for independent variables
that how much these values have an impact on the dependent
variable, regression analysis has been applied to the collected
data. The backward regression method has been used here to get
the significant independent variables to determine the best-fit
equation for our model.
The above table 3 illustrates the model summary of the data.
The value of R is 0.685 i.e. 68.5% which represents that there is
correlation between variables. The coefficient of determination R
square describes the goodness of fit of the model which is 0.469
in our case. This estimates that changes in sales promotion tools
(i.e. Price Discount, Free Sample, Buy one Get one and Online
Sale) describes 46.9% variations in Consumer Buying Behavior.
Additionally, R square value is 2% different from Adjusted
R-square; this shows that we have taken an adequate size sample.
The below Coefficient, the table 4 shows the significance
of each independent variable in predicting the dependent
variable. The positive value shows that there is a positive effect of
independent variables on the dependent variable.
This table also facilitates in formulating the econometric
model which is:
Consumer buying behaviour = β0 + β1FreeSample + β2PriceDiscount +β3Buy 𝑜𝑛𝑒get one free + β4OnlineSale + u
Y= consumer behavior X1= free sample
X2= price discount
X3= buy one get one free X= online sale
u= error term
By substituting the values in the above equation from table 4
our for our study becomes:
Y = 1.023 + 0.142X1 + 0.295X2 + 0.109X3 + 0.157X4
For this study, the following hypothesis summary is calculated.
If p-value is less than α=0.05 that shows that the variable is
significant (Table 5).
The independent variable of H3 (There is no significant impact
of buy one get one free on consumer buying behavior) was found
insignificant. The results indicate that price discounts, free sample
and online sale has significant and positive impact on consumer
buying choices. Coefficient and significance values showed
positive and strong impact of these sales methods on consumer
buying choice [10,11].
‘Buy one get one free’ offer didn’t show significance for
consumer buying behavior. It has been seen during collecting data that respondents were not so anxious and enthusiastic about ‘buy one get one free’ offer. Their experiences discovered that this
method is mostly used in food items like pizza and burger in the
Bahamas so it did not have much impact on their buying decisions.
The consumer-behavior regression equation explains that
sales-promotion- techniques, ‘price discount’, ‘free-sample’,
and ‘online sale have a strong significant relationship with
consumer buying behavior but the ‘buy one get one free offer’
has no significant relationship with consumer buying behavior.
Our sample size consisted of 65 respondents were limited and
comprised of specific premises and respondents of a particular
background. It is suggested to research further on the people with
all age groups, income and education and from different areas.
Briefly, it can be concluded that different promotional
techniques create a noticeable impact on consumers’ choices and
behavior. It has been observed that sales promotional techniques
are very helpful in boosting the sale of retailers and wholesalers.
These methods served as complementary for their business plans
and future decisions. It is very important for producers to select
the specific strategy which is useful for sales enhancement in a
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Salvi P (2013) Effectiveness of Sales Promotional Tools: A Study On Discount, Price Off And Buy One Get One Free Offers In Branded Apparel Retail Industry In Gujarat. ELK Asia Pacific Journal of Marketing And Retail Management 4(4).
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