Impact of online sales promotion on women's buying attitude
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AEGAEUM JOURNAL ISSN NO: 0776-3808
Impact of online sales promotion on women’s
buying attitude
Jitendra Singh Rathore1, Rohini Baghel2
1Assistant Professor, Faculty of Management Studies, Banasthali Vidyapith, India
2Research Scholar, Faculty of Management Studies, Banasthali Vidyapith, India
Abstract - In the modern times, online purchasing has proved very useful to consumers,
particularly women’s buyers. Looking at the psychology of women, E- retailers have
launched heavy discounts during the festival season ,like Amazon incentives schemes
during the festival season, big billion sales offered by Flipkart and Unbox Zindagi sales
by Snapdeal are some of the attractive discounts. These discounts are in the form of
quantity Discounts, cash back Offers, Coupons, Buy one, get one free, Free shipping etc.
It has become essential for both online retailer and consumers to identify the relevance of
these discounts and devise strategies accordingly. The present research studies the
significance of online discounts on women buying attitude with reference to Indian
scenario. We have used the price–feature–value model and means end approach in this
context.
Keywords: Online Discount, buying attitude buying behavior.
1. Introduction
Festival sales are the recent trend in India. All Indian retailers provide attract heavy
discounts during festival season and clear their new and old stock. They provide several
offers during festival season to attract new and old customers. These offers are like;
Freebies, cash back, and buy1 get free, etc. These E-Commerce portals are promoted
these days for a particular name such as Big billion days by Flipkart, Great Indian festival
sale by Amazon, Unbox Zindagi by Snapdeal (V.T. Shailashri & Aithal et al, 2019).
E-Commerce portal have many advantages; they are very helpful to consumer, in
searching new product and services to related information’s (Park & Kim, 2003). They
provide 24x7 services available for customers. Customers can purchase the article any
time and at any location on comparable price. They can check quality of products on the
basis of related consumer's feedback. They can also review the products. The internet
method of shopping is available on the internet. In the days to come, it shall generate the
large volumes of revenue. It is hoped that it will contribute up to 4% to GDP (Gross
Domestic product). These sectors are divided into four segments like - Business to
Business (B2B), Customer to Customer (C2C), and Business to Customer (B2C), and
Customer to Business (C2B) (Ghosal, 2018).
According to Priya Chauhan (2015) the main e-commerce shopping websites in India
are:
Flipkart: - This ecommerce site’s foundation was laid by both Sachin and Binny Bansal. It
is based in Bengaluru, India. It started selling books online and after some time they grew
up and start dealing with other new products/ services like electronics products, fashion,
lifestyle products, etc. “In March 2017, Flipkart held a 39.5% market share in India's e-
commerce Industry”.
Amazon: - Amazon was established in Bellevue, Washington July 5, 1994, by Jeff Bezos.
It has started selling the books online, and after some time they expanded their business
and start selling products like electronics, software, videogames etc.
It is the greatest American company in India and a global venture that’s established in
Seattle, Washington. This ecommerce giant has many roles to play from brandishing
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global goods marketing to cloud support, digital stream and AI support. It has considers in
technology companies like: - Google, Facebook, Apple. It is the largest company in the
world, in the e-commerce market place and it has generated the largest revenue in the
world.
Snapdeal: - Snapdeal was also established by two people Kunal Bahl and Rohit Bansal.
The company came into existence in February 2010 at Delhi. It has the largest online
market place in India, it deals in many products and services, till time over 3, 00,000
sellers is registered, 3 crore products are available in Snapdeal website, and overall
1,25,000 retailers have sold the different national and international brands in Snapdeal.
Many celebrities had promoted the Snapdeal website in India.
According to Sujata & Menachem, (2017) the festival season e-commerce portal has
promoted the websites like- Big billion sales by Flipkart, Great Indian festival sales by
Amazon, Unbox Zindagi by Snapdeal. E-Commerce portals have provided the heavy
discounts and cash back offers, free delivery for consumers during a festival season/
special occasion. Consumers remain very excited to purchase the products for this time.
Discounted Products: - Normal days, E-commerce portals have provided more discounts
for specific products. Then discounts are very attractive to consumers, and they are ready
to purchase the products at an affordable price.
Extra Cash Back with bank tie-up: - E-commerce portals have provided more discounts
and cash back offer during festival season, consumers are attracting for purchasing the
products. E-Commerce portals have also tied up major banks in India.
SBI (State bank of India), HDFC Bank, Axis Bank, etc. are provided 10-20% extra
discounts for purchase the minimum amount of product.
Free shipping / Free Returns: - E-commerce portals has provided more facilities during
the festival season like free shipping and free returns of the product.
2. Literature Review
Online Shopping Buying Behavior:-
The literature reviewed on the subject shows that online shopping is one of the ways to
change consumer perception and to study buying behavior. Mostly consumers preferred
online shopping for many reasons. It was available on the different types of product
categories, national or international brands to easy search, price comparison or product
features etc. Then e-commerce companies had to understand the consumer’s perception
related to online shopping (Thakur., 2015). Consumer behavior is influenced by many
factors like information related to product/ service, convenience, experience, trust for the
vendor, no time-consuming shopping (Bhandari & Kaushal, 2013). Online retailers had
given more importance on price factors and after-sales factor (Saravanan & Devi, 2015).
Consumer behavior had influenced four major key factors, like website design (updated
information’s are available in the website to related products/ services), product variety
(different- different types of product variants are available in e-commerce portals),
reliability, and delivery performance of products/ service (Alam & Yasin, 2010).
The study had investigated the socio demographical factors (age, income, occupation),(
Hernandez et al, 2011) pattern of online buying behaviour (types of usage the product/
services experience), buying perception ( product perception, risk, consumer services),
these factors are affect the consumer buying behaviour related towards online shopping (
Jusoh & Ling, 2012).
This study indicated that the behaviour of the consumers involved some factors, which
included in social class, sub culture, reference group, social culture and family factors,
including the infrastructure (Keisidou & Sarigiannidis et.al, 2011). This all means that the
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consumer would easily purchase the advertised products. Hence these advantages of
internet buying through online market goods proved effectively useful.
Women buying perception towards online shopping:-
Women buying perception towards online shopping has drastically changed. It is
observable that mostly the younger generations from (18-25 age group) are much too
interested in online shopping. The main reason is their knowledge about current
technology. In India, most of the members of these groups prefer to go for online
shopping of their preferred products (Anitha, 2017).
Buying motives:-
Indian people have heartily celebrated every festival in its own culture and tradition.
Cultures and festivals have a huge impact on every consumer buying behavior in Indian
market (George & Chandrasekhar, 2015).like Diwali (the festivals of lights, and
celebrated mostly by Hindu families). Durga pooja ( this festival is famous in Bengal,)
then every marketers or retailers has provided the heavy discounts, gifts, vouchers,
coupons or extra quantity, etc. during a festival season(Ramanuj Majumdar, 2010). Every
retailer or marketers had adopted these strategies for attracting the consumers, and
increase the shopping; more varieties are available in different types of product range,
nation or international brands, and increase the awareness of products and services also
(George & Chandrasekhar, 2015). Consumer behavior has been changed according to
change in the lifestyle of the consumer or culture and taste and preference. (George,
2015)
Reference model:- Price-Quality- value Model
Perceived
Savings
Price Discounts Purchase
Price Perceived Intention
Discount offers Effects Value / shopping
buying
behaviour
Perceived
Quality
Price Discounts offers effect:-
In the earlier methodology on marketing research, it was observed that discounting offers
both constructive and undesirable influence on consumer’s mind or consumers buying
behavior. The consumer has spent more time to find the best deals or best offers. The
promotion has been very helpful for consumers to save time or energy to related search
the best deals or best offers (Lee and Chen, 2018). A positive monetary affect the
consumers, like producer reduce some amount in the actual price of the product and
services, and the negative impact of the consumer mind, like: - a consumer have
consumed the time for search the best deal or best offers (Perreault et.al, 2017).
Perceived savings:-
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In the earlier studies, an impressive gainful trend can be seen between apparent savings
and price discounts offers. Online retailers or producers have provided a higher level of
discounts for many products then consumers have perceived a higher level of saving also.
A discount means that retailers have reduced the original price (Grewal & Monre et.al,
1998b).
Perceived Quality:-
Product quality measurement is very difficult for every consumer. Perceived quality has
depended on the company reputation/ producers, a consumer has been purchasing the
product for the basis of brand value, price of the product, and advertising level of the
product (Zeithaml, 1998). There is a positive connection between price discounts and
perceived quality or perceived savings.
Perceived Value:-
In the recent study, the perceived value is refereed only to the price measurement of
products, were as most of the studies on pricing define the value of money and use
perceived value different from quality and emotion.
The present study intends to propose that the price discount effect has a positive influence
on the price measurement of the perceive value (Lee & Chen-yu, 2018).
Purchasing Intention/ shopping Buying Behavior:-
Internet has to change the consumer buying behavior (Thakur, 2015), the lack of trust,
inconvenience (Bhandari & Kaushal, 2013) it has included some major factors affecting
the buying behavior/ shopping buying behavior like website design, product variety
(different types of products variety are available in e-commerce portals), delivery (easily
reachable product to consumer in short duration ) (Alam & Yasin, 2010).
In the festival season, online retailers have provided the heavy discounts for attracting
new or old consumers (Schiffman & Kanuk, 2010), they are reducing some amount in
actual price/ face value of the product in a specific period of time (Kolter, 2010).
Marketers have provided the various types of discounts for consumers like cash back
offers, Extra Quantity of the product, buy one get free offers, seasonal discounts (Kolter et
al, 2014). Discount has famous sale technique to affect the consumer behavior/
purchasing intention of the consumer (Neha & Manoj, 2013).
Former studies show that price discounts and perceived savings or perceived quality has
affected the consumer buying intention/ shopping buying behavior. Apparent savings are
impacted positively by product quality and discounted pricing
3. Proposed Research Model
Consumers buying motivation techniques
Discounts offers
Coupons Motivators for buying
behaviour of
Loyalty programs consumers
Price pack
Free shipping
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Discount:-
Discounts are the most important marketing strategy for attracting the consumers; they
can purchase the product easily and at an affordable price (Amanah & Harahap, 2018).
The buyer had shared the price list for consumers and they can reduce some amount of
actual price of product/ service, which had benefits both buyers and sellers (Perreault
et.al, 2017), Retailers had provided the price discounts in many forms like- cash discount,
a quantity discount, facilities discount, seasonal discount, price discount, etc. ( Kotler &
Armstrong, 2014).
Coupons:-
Coupons had no major effect on quantity of purchasing by the consumers (Gilbert &
Jackaria, 2002) but Malaysia has disproved this statement (Ndubisi & Chiew, 2006) then
coupons promotion was least used this promotion techniques by consumers, then this
research proved that mostly women are preferred to other than men (Doston’s, 2001).
Loyalty Programs:-
E- Retailers have provided many offers to customers, who can purchase the products/
services frequently then it is called loyalty. They are giving to customer unique id number
or membership card, by presenting the card for every purchase or purchaser by provided
the special discount or allotment some points for future purchase (Nagadeep & selvi et al,
2015).
Price Pack:-
Price pack promotion had influenced the consumer buying behavior along with other
factors like direct price discounts, buy one get 1 free, buy one and get another product
free, publicity, media advertising etc. (DAS, 2011) The research study proved that price
discounts and other promotion techniques had influenced the consumer buying behaviour
towards online shopping/ offline shopping (Rizwan et al, 2013).
Free shipping / free Delivery:-
In a normal day, if a consumer has purchase the product/ service; they had to pay shipping
charges like consumer has place order the product, then they have to extra pay 70 to 150
Rs or more for shopping cost. Shipping cost is expensive, but during a festivals season all
retailers have provided this facilities. Then free shipping/ free delivery is also effect the
consumer buying behaviour during a festival season (Sujata & Menachem et al, 2017).
Objectives of the study
1. To evaluate the different forms of online sales promotion on consumer shopping
behavior with special reference to women
2. To comprehend the positive and negative elements of online sales promotion
schemes on consumer shopping behavior.
Population: - Target the customers who have bought the products through online portals
like Amazon, Flipkart, and Snapdeal.
Research design: - The study has been based on the descriptive method or primary data.
Tools for data collection: - Collect the data through a questionnaire; it is based on 5
points Likert scale method.
Sampling size: - An aggregate number of 260 questionnaires are circulated among the
customers in Delhi & NCR.
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Data Collection:-
Primary Data: - This data was collected through questionnaires from a customer who
buys the product through online portals like Amazon, Flipkart, and Snapdeal.
Secondary data: - This data was collected from secondary sources, such as books,
internet sources, journals, and research studies, etc…
4. Data Analysis methodology
The data was collected the specific cities Delhi & NCR, then fill the questionnaire who
buy the products through online.
Descriptive Statistics
N Range Minimum Maximum Mean Std. Variance
Deviation
Statistic Statistic Statistic Statistic Statistic Std. Statistic Statistic
Error
P.Q1 260 3 2 5 4.00 .057 .911 .830
P.Q2 260 4 1 5 3.79 .060 .964 .930
P.Q3 260 4 1 5 3.57 .065 1.054 1.112
P.Q4 260 2 3 5 4.20 .047 .760 .578
P.Q5 260 4 1 5 4.14 .053 .854 .730
P.Q6 260 4 1 5 3.90 .059 .944 .890
P.Q7 260 4 1 5 3.88 .063 1.012 1.024
P.Q8 260 3 2 5 4.07 .054 .865 .748
P.Q9 260 3 2 5 4.10 .059 .951 .904
P.Q10 260 3 2 5 4.11 .047 .765 .586
D.Q1 260 3 2 5 3.98 .056 .909 .826
D.Q2 260 3 2 5 3.63 .049 .793 .629
D.Q3 260 4 1 5 4.07 .048 .773 .598
D.Q4 260 4 1 5 4.21 .061 .985 .971
D.Q5 260 4 1 5 3.78 .058 .938 .880
D.Q6 260 3 2 5 4.03 .054 .863 .744
AVERAGE 3.96
The mean value of the all the statements is 3.96 which is good.
Identification of Primary Contributory Components in price discount by using
Factor Analysis
An instrument consisting of 16 statements to measure the e-commerce portals has
provided the many different types of discounts to the consumers and creates the consumer
awareness. The people were asked on survey to give their testimonies by ratings on a five-
point Likert scale.
This scaling log above is a 5-point rate maker identified by digits ranging anywhere
between 1 and 5. We arrive at an aggregate score by adding the total statements from each
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responding customer including their distinct statements that are helpful to recognize a
proper factor analysis using the Multivariate method.
Table – 1:- Case of process summary
N %
Cases Valid 256 98.5
Excluded 4 1.5
Total 260 100
a. List wise deletion based on all variables in the procedure.
Reliability of the Instrument
To look for variance and adopt consistent measures along with a reliability check to
accurately measuring e-commerce results, portals have provided the many different types
of discounts to the consumers and create the consumer awareness. The popular marketing
Alpha Coefficient of Cronbach was analysed through SPSS. This methodology of
Cronbach Alpha is depicted below:
Table – 2:- Reliability statistics
Cronbach's Alpha N of Items
.868 16
Reliability Statistic: - Using the Cronbach’s Alpha approve, the analyzed result comes to
0.868 (Over 0.7), hence it is acceptable for current analysis.
Table – 3:- Sample Design and Data Analysis
Sample size 260
Sample unit e-commerce portals provided the online discounts during a
festival seasons
Sample frame Cities Delhi & NCR
Test Regression
Identification of Factors
The impact of Ecommerce portals and their influence on the Web has been clearly
elucidated in a different module which bears the 16 statements to validate approach meant
to showcase the different discounting patterns during the season of festivity. We provide
our verdict based on the study of the 16 closely linked variables that have been read and
analyzed throughout in the questionnaire to reflect the behavior of ecommerce portals.
Thus, the plethora numbers of closely linked 16 variables are clubbed by factor analysis
because the factor approach drastically reduces redundancy in variable count by taking in
only the selected ones to factorize (Nargundkar, 2005). Hence, a 5-factor approach
successfully done using SPSS. Both the principle component analysis and Varimax
rotational method is employed. However, before this approach, the validity of data set
was performed using Kaiser Meyer Olkin (KMO) and it happened to provide the 0.794
value exceeding the desirable value 0.5. So the association between the pairs of variables
is shown by other variables, so Factor analysis is a desired technique for the same. Using
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Bartelt's-test of sphericity, the null hypothesis of variables are uncorrelated, and so the
correlation matrix is identity matrix. Even the table beneath validates chi-square at 0.05
level. Hence, the application of factor analysis becomes valid.
Table – 4:- KMO and Bartlett’s Test
Kaiser-Meyer-Olk in Measure of Sampling
Adequacy. 0.794
2070.9
Approx. Chi-Square 51
Bartlett's Test of
Sphericity
Sig. 0
The five element solution provided herein by SPSS elucidates
67.444% variance which was extracted employing rotated
component matrix and hence, the recorded digits were marked as
per the greatest loading values in a specific factor. This
component matrix sows the load value digits specifically in the
below mentioned table:-
Total variance Explained
P.
Q P.
1 Q2
Extraction Sums of Rotation Sums of
Initial Eigenvalues Squared Loadings Squared Loadings
% of % of % of
Compo Tot Varian Cumula Tot Varia Cumulati Tota Varia Cumula
nent al ce tive % al nce ve % l nce tive %
1 5.9 33.168 33.168 5.9 33.16 33.168 3.32 18.44 18.444
70 70 8 0 4
2 2.1 12.109 45.276 2.1 12.10 45.276 2.84 15.83 34.274
80 80 9 9 0
3 1.5 8.632 53.908 1.5 8.632 53.908 2.31 12.84 47.123
54 54 3 9
4 1.2 7.006 60.915 1.2 7.006 60.915 1.86 10.34 57.466
61 61 2 4
5 1.1 6.529 67.444 1.1 6.529 67.444 1.79 9.977 67.444
75 75 6
6 .81 4.516 71.959
3
7 .74 4.141 76.100
5
8 .63 3.549 79.649
9
9 .59 3.307 82.956
5
10 .53 2.984 85.940
7
11 .45 2.526 88.465
5
12 .44 2.484 90.950
7
13 .39 2.197 93.147
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5
14 .32 1.795 94.942
3
15 .27 1.530 96.472
5
16 .25 1.435 97.908
8
17 .21 1.204 99.112
7
18 .16 .888 100.000
0
Extraction Method: Principal Component Analysis.
Rotated Component Matrix
Component
1 2 3 4 5
D.Q3 .802
P.Q9 .678
D.Q6 .667
P.Q5 .643
D.Q5 .623
D.Q8 .844
D.Q7 .809
D.Q2 .681
D.Q1
P.Q3 .851
P.Q7 .652
P.Q2 .644
P.Q6 .519
P.Q1 .796
D.Q4 .591
P.Q10
P.Q4 .867
P.Q8 .523
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 10 iterations.
The variables or statements of questionnaire clubbed under factors were as under:
Factor 1 (Discount): This factor has Total Initial Eigenvalues of 5.970 and
explains 33.168% of total variance. This factor includes five variables or five
different dimensions namely:
Online shopping offer for special discount in festival season.
The price is important when you shopping online
Watch online advertisement for discounts and sales deals.
Price discounts on top selling branded products in festival season are
welcomed
Always make purchase during discount periods
Factor 2(Coupons): This factor has Total Initial Eigenvalues of 2.180 and explains
12.109% of total variance. This factor includes three variables or three different
dimensions namely:
I Like the notifications for use of Online coupons
While doing online shopping I use GET THIS COUPON
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Coupon Deals in online shopping are attractive
Factor 3(Loyalty Programs): This factor has Total Initial Eigenvalues of 1.554 and
explains 8.632% of total variance. This factor includes four variables or four different
dimensions namely:
The fees for Online Loyalty programs are worth paying.
Loyal members get preferred treatment.
More choices for Loyal customers in online shopping.
More discounts for purchasing more is an advantage for loyal customers
Factor 4(Price Pack): This factor has Total Initial Eigenvalues of 1.261 and explains
7.006% of total variance. This factor includes two variables or two different dimensions
namely:
Price pack offers of online shopping are attractive.
Price pack offers in online shopping are good deals.
Factor 5(Free Shipping): This factor has Total Initial Eigenvalues of 1.175 and explains
6.529% of total variance. This factor includes two variables or two different dimensions
namely:
While buying online I always take into account the shipping charges.
Free shipping is a great lure for a customer.
Relationship between different forms of online sales promotion and buying behavior
of consumers.
Ho1: Under this category the online sales promotion does not affect the Consumer
Shopping Behavior of women.
Ha1: Under this category the online sales promotion affects the consumer shopping
behavior of women.
Consumer Shopping Behavior is measured by the cumulative responses of consumers
about the different forms of online sales promotion. Individual different forms of online
sales promotion i.e Discounts,Coupons,Loyalty programs, Price Pack and Free shipping
is measured by the responses of consumers about these dimensions.
Here, Consumer Shopping Behavior is taken as dependent variable and Individual
different forms of online sales promotion i.e Discounts, Coupons, Loyalty programs, Price
Pack and Free shipping are reserved as independent variables. The relationship between
these three is measured through Multiple Linear Regression with suitable assumptions of
Linearity, and Multi collinearity.
Table 1:Variables Entered/Removed
Variables Entered Variables Method
Removed
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Discount, Coupons, Loyalty Programs, Price
. Enter
pack, Free shipping
a. Dependent Variable: Consumer Shopping Behavior
b. All requested variables entered.
In the above table 1, there is only one model with Consumer shopping behavior as
dependent variable and Discounts, Coupons, Loyalty programs, Price Pack and
Free shipping as independent variables and during fitting the regression line no
variable was removed and the method was Enter
Table 2:Model Summary
Model R R Square Adjusted R Square Std. Error of the
Estimate
1 .961a .923 .922 .1338457
a. Predictors: (Constant), Factor-5, factor-2, Factor-4, factor-3, Factor-1
The summarized data provided in the model gives relevant info on R, R2, adjusted R2,R2
change and the typical error count of the estimate which adjusts to the regressive line limit
between we seemingly find observation of direct association between the detected and
anticipated value of various channels of online sales promotion studied individually. The
normal error approximation judges the distribution coming via distinct forms of online
sales... Hence, this presents the customary aberration of the error expression and the
square root of the Mean square for the residuals in the ANOVA table.
Table 3:ANOVAa
Model Sum of df Mean Square F Sig.
Squares
Regression 54.817 5 10.963 611.983 .000b
1 Residual 4.550 254 .018
Total 59.368 259
a. Dependent Variable:
b. Predictors: (Constant), Factor-5, factor-2, Factor-4, factor-3, Factor-1
The ANOVA is given in the Table 3 and the significance value is 0.000 which is less than
critical value of 0.05. Therefore the Consumer shopping behavior has significant different
mean than Individual different forms of online sales promotion i.e Discounts, Coupons,
Loyalty programs, Price Pack and Free shipping and consequently, has linear relationship.
Henceforth, the null hypothesis that Different forms of online sales promotion do not
affect Consumer Shopping Behavior is rejected. The Sum of Squares associated with the
three sources of variance, Total, Regression and Residual. The Total variance is divided
into the variance which is possibly explained by the Individual different forms of online
sales promotion i.e Discounts, Coupons, Loyalty programs, Price Pack and Free shipping
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i.e. 54.817 and the variance which is not explained by the Individual different forms of
online sales promotion i.e Discounts, Coupons, Loyalty programs, Price Pack and Free
shipping i.e. 4.550.
Table 4:Coefficients
Model Unstandardized Standardized t Sig.
Coefficients Coefficients
B Std. Error Beta
(Constant) .393 .078 5.060 .000
Factor-1 .391 .020 .452 19.957 .000
factor-2 .026 .015 -.032 -1.735 .014
factor-3 .308 .016 .396 19.860 .000
Factor-4 .261 .017 .330 15.644 .000
Factor-5 .096 .019 .102 5.058 .000
a. Dependent Variable: V7
The t value is statistically significant being less than 0.05 for Individual different
forms of online sales promotion i.e Discounts, Coupons, Loyalty programs, Price
Pack and Free shipping. The coefficients of the Individual different forms of
online sales promotion represents the change in the mean response for one unit of
change in Consumer shopping behavior, while the other terms in the model are held
constant. The relationship between Discounts, Coupons, Loyalty programs, Price
Pack and Free shipping and Consumer shopping behavior can be expressed in the
equation form as:
Consumer shopping behavior =.391 Discounts + .026 Coupons + .308 Loyalty
programs+ .261 Price Pack+.096 Free shipping
The equation (1) is defined when Consumer shopping behavior is measured on five
point Likert Scale.
5. CONCLUSION
The women consumers do witnessing and exhibit a change in consumer shopping
behavior in online sales promotions. This study aims at evaluating different forms of sales
promotion in the online shopping.
1. Discount
2. Coupons
3. Loyalty programs
4. Price Pack
5. Free Shipping.
All the five forms of online sales promotion –Discount, Coupons, Loyalty programs ,Price
Pack and Free shipping significantly contribute to the overall consumer shopping
behavior of women.
As stated by P. Khanna & B. Sampat 2015, The ways of Diwali festival season 2014 e-
retailers are now buying the same techniques with regards to Christmas season. They have
shifted their attention to explore other channels such as mobile apps to permit their
medium of sales during Christmas. Amazon has also started serval schemes for the
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Christmas season on their mobiles apps and their websites. Barring three major festivals
like Diwali, Raksha Bandhan, and Valentine’s Days no other festivals attracts e-
commerce transactions. Most of the Websites have offered some the other offer running
all through the year. There is still a used potential in India the e- trailer stalwarts can
choose to limit their sales to the major festivals like Diwali. They can also take
advantages of tapping special days like Children’s Day, Father’s Day or Mother’s Day to
keep women consumers consistently interested in them.
6. Limitations
There are if you limitations to this study. First, the sample is focused to if you states of
India. Future researches may in corporate more comprehensive sample collection. In this
study, we shall try to indenfy few forms of online sales promotion which effect
consumer final buying and could not take into account other sales promotion forms which
are part of online shopping.
7. References
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