A detailed business research on customer loyalty

1. AN IMPACT OF
AFFECTIVE LOYALTY
AND PERCEIVED CARD
BENEFITS ON
CONSUMERS INTENTION
TO CONTINUE TO USE
THE LOYALTY CARD BY: VIJAY KUMAR

2. Introduction
• Loyalty programs/cards have integral part of every retail
business. They aim at:
 increasing sales revenues by raising purchase/usage
levels.
 building a closer bond between the brand and
customers with a hope to maintain the current customer
base.
• Retail fuel companies in India have also become a part of
this league.
• Retail fuel companies in India have been promoting several
kinds of loyalty programs including issue of co-sponsored
debit/credit cards and pre-paid/gift cards.

3. Review of Literature
• Affective loyalty is the second stage while developing loyalty towards
a brand (Oliver, 1999). It is defined as a kind of attachment to the
brand as a result of pleasant past experience.
• The key components for developing affective loyalty include attitude,
satisfaction, trust and commitment.
• Strong and durable affective relationship with the brand drives the
consumer to a feeling of inseparability towards this brand (Touzani &
Temesse, 2009).
• Tietje (2002) focused on the role of rewards offered by loyalty
programs, and concludes that obtaining certain rewards can generate
positive feelings towards the retailer implementing the program.
These feelings linked to the purchase experience involve a greater
satisfaction leading to higher purchase intentions or consumers
intension to continue to use the card.(Price et al., 1995; Oliver et
al.,1997).

4. Management Problem:
What drives the intention of customers to continue to use the
loyalty cards being offered by retail fuel companies in India?
Research problem:
What are the factors that contribute towards the continuous
use of loyalty cards offered by retail fuel companies in India?
Problem Definition:
To study the role of affective loyalty and perceived card
benefits in driving the intension of customers to continue to
use the loyalty cards being offered by retail fuel companies in
India.
Statement of the problem

5. Objective of the study
•Research Objectives:
To identify the impact of affective loyalty and
perceived card benefits on consumers intension to
continue to use the card.
•Research Questions:
What is the relationship between affective loyalty,
perceived card benefits, and intension to continue to
use the Card.?

6. Constructs
Affective Loyalty
• Attitude
• Satisfaction
• Trust
• Commitment.
Perceived Card Benefits
• Ease of payment
• Reward points
• Special offers/discounts
Consumer’s Intention to use the card

7. Conceptual Model
Intension to continue to use the
card
Affective loyalty
Perceived card
benefits (ease of
payment, special
offers/discounts,
feeling of
belongingness and
reward points.
Attitude
Satisfaction
Trust
Commitment

8. Hypotheses
• H10: There is a statistically no correlation between affective loyalty and
consumer intension to continue to use the card.
• H1A: There is statistically correlation exists between affective loyalty and
consumer’s intension to continue to use the card.
• H20: There is a statistically no correlation between perceived benefits of
cards and consumer’s intension to continue to use the card.
• H2A: There is statistically correlation exists between perceived benefits of
cards and consumer’s intension to continue to use the card.
• H30: There is a statistically no significant impact of perceived benefits of
card on consumer’s intension to continue to use the card.
• H3A: There is statistically significant impact of perceived benefits of card on
consumer’s intension to continue to use the card.

9. • H40: Gender and use of card benefits are independent.
• H4A: Gender and use of card benefits are dependent.
• H50: Owing a loyalty card and monthly expenditure on fuel are
independent.
• H5A: Owing a loyalty card and monthly expenditure on fuel are
dependent.
• H60: The mean monthly expenditure on fuel is Rs 3000.
• H6A: The mean monthly expenditure on fuel is not equal to Rs 3000.

11. • Descriptive Research.
• Cross Sectional Study.
• Online Questionnaire.
• Independent variables:
• Affective Loyalty of Customer
• Perceived Card Benefits
• Dependent variable:
• Consumer Intention to Continue to Use the Card
• Unit of Analysis
• Individuals holding loyalty card of oil companies in Delhi & NCR.
Research design

12. Methodology of Sampling & Data collection
• Convenience Sampling
• Required sample size was 110.
• Responses were received from 107 respondents.
• Respondents were in the age range of 18-65.
• 61% of the total respondents were of the age of 26-45 years.
• About 75% of the total respondents have household income in the range of 5-15 lakhs and monthly
spending on fuel is in the range of Rs.2500-7500.
• An online questionnaire was mailed to 110 consumers of retail fuel companies in Delhi & NCR.
107 responses were received within a period of three weeks. The higher return rate of 97.3%
can be attributed to the shortness of the questionnaire and perhaps the consumer’s interaction
with one or the other kind of loyalty cards on day to day basis.

13. Editing & Coding
• The complete responses were checked for any omissions and
consistency. The completeness of responses was ensured. Since, the
responses were collected through online surveys, errors of legitimacy
were removed.
Coding of Data
Strongly
disagree
Disagree Neither Agree
nor disagree
Agree Strongly Agree
1 2 3 4 5

14. Data Analysis
• Factor Analysis
• Correlation & Regression
• Chi Square
• T-test

15. Factor Analysis
• The measures of sampling adequacy Kaiser-Meyer-Olkin was >0.5
• Bartlett’s test of sphericity was significant.
• Anti-image correlations matrix diagonals value were >0.5.
• Variable CI1 needed to be reverse coded.
• Variables like CI4, CI5 and CI6 which were initially considered to be
the part of construct “Consumer Intention to use the card” doesn’t fit
well.
• Variables P4, P5 and P7 do not well explain the construct they were
initially part of.

16. CONSTRUCTS & THEIR SIGNIFICANT VARIABLES
On the basis of Factor Analysis following variables were used to measure
constructs under study:-
• Consumer Intention to use the card – Variables CI1, CI2, CI3 and CI7 were
used to measure it.
• Affective loyalty- Variables A3, A4, A5, A6 and P1 were used to measure it.
• Card Benefits- Variables P2, P3 & P6 were used to measure it.

17. Correlation & Regression
• Before carrying out the calculation of Person’s correlation
coefficient and subsequent significance testing, following
assumptions were tested.
Interval or ratio scale: Since, all the data was collected
on Likert scale, this assumption holds good.
Linearity: Technique used was Scatter plot.
Bivariate normally distributed: Technique used was
Histograph & skewness coefficient.
All the assumptions were found to be hold good.

18. Hypothesis Testing
• H1o: There is no correlation between the consumer intention to use the card and
perceived card benefits.
• H1A: that there is correlation between the consumer intention to use the card
and perceived card benefits.
Correlations
CI PI
CI Pearson
Correlatio
n
1 .334**
Sig. (2-
tailed)
.000
N 107 107
PI Pearson
Correlatio
n
.334**
1
Sig. (2-
tailed)
.000
N 107 107
**. Correlation is significant at
the 0.01 level (2-tailed).
The Pearson correlation coefficient value of 0.334 confirms what
was apparent from the graph; i.e. there appears to be a positive
correlation between the two variables.
SSPS reports the p-value for this test as being .000 and thus we
can say that we have very strong evidence to believe H1, i.e. we
have some evidence to believe that Consumer intension to
continue to use the card and perceived benefits are linearly
correlated for consumers of retail fuel companies.

19. • H20: There is a statistically no correlation between perceived benefits
of cards and consumer’s intension to continue to use the card.
H2A: There is statistically correlation exists between perceived
benefits of cards and consumer’s intension to continue to use the
card. Correlations
CI AI
Spearma
n's rho
CI
(Consum
er
Intension
to use
the card)
Correlati
on
Coefficie
nt
1.0
00
.45
2**
Sig. (2-
tailed)
. .00
0
N 107 107
AI
(Affective
loyalty)
Correlati
on
Coefficie
nt
.45
2**
1.0
00
Sig. (2-
tailed)
.00
0
.
N 107 107
**. Correlation is significant at the 0.01
level (2-tailed).
The Spearman’s correlation coefficient value of 0.452
confirms what was apparent from the graph, i.e. there
appears to be a positive correlation between the two
variables.
SSPS reports the p-value for this test as being .000 and thus
we can say that we have very strong evidence to believe H1,
i.e. we have some evidence to believe that Consumer
intension to continue to use the card and affective loyalty are
positively correlated for consumers of retail fuel companies.

20. • H30: There is a statistically no significant impact of perceived benefits
of card on consumer’s intension to continue to use the card.
H3A: There is statistically significant impact of perceived benefits of
card on consumer’s intension to continue to use the card
Model Summaryb
Model R R Square
Adjusted R
Square
Std. Error of
the Estimate
1 .334a .112 .103 .62637
a. Predictors: (Constant), PI
b. Dependent Variable: CI
The value of R is 0.334 which indicates a low degree of correlation and R2 is 0.112 which means only
11.2% of variation in consumer intension to continue to use the card can be explained by the
independent variable i.e. perceived card benefits.

21. ANOVA table indicates how well the
regression equation fits the data.
The table indicates that the
regression model predicts the
dependent variable significantly well
as value of p<0.005 (i.e., it is a good
fit for the data).
ANOVAa
Model
Sum of
Squares df
Mean
Square F Sig.
1 Regressio
n
5.183 1 5.183 13.21
2
.000b
Residual 41.195 105 .392
Total 46.379 106
a. Dependent Variable: CI
b. Predictors: (Constant), PI
Co-efficientsa
Model
Unstandardi
zed
Coefficients
Stand
ardize
d
Coeffi
cients
t Sig.
90.0%
Confidence
Interval for B
B
Std.
Error Beta
Lower
Boun
d
Upper
Boun
d
1 (Cons
tant)
2.035 .490 4.1
50
.000 1.221 2.849
PI .442 .122 .334 3.6
35
.000 .240 .644
a. Dependent Variable: CI
The coefficient table indicates that
for every one unit change in
perceived card benefits, the
consumer intension to continue to
use the card increases by 0.442
and it contributes statistically
significantly to the model.

22. Chi-Square Test
H40: Gender and use of card benefits are independent.
H4A: Gender and use of card benefits are dependent.
Given a significance level of 10% and df=1, we find the critical value as X2
0.10, 1=2.706. Hence, the
decision rule is to reject H0 if X2 0.10,1>2.706. Since, X2
0.10,1=0.078<2.706, we cannot reject the null
hypothesis. At 10% significance level, we conclude that the two qualitative variables are
independent.
Chi-Square Tests
Value df
Asymptotic
Significance (2-
sided)
Exact Sig. (2-
sided)
Exact Sig. (1-
sided)
Pearson Chi-Square .078a 1 .781
Continuity Correctionb .001 1 .976
Likelihood Ratio .077 1 .781
Fisher's Exact Test .808 .484
Linear-by-Linear Association .077 1 .782
N of Valid Cases 107
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 8.44.
b. Computed only for a 2x2 table

23. H50: Owing a loyalty card and monthly expenditure on fuel are independent.
H5A: Owing a loyalty card and monthly expenditure on fuel are dependent.
Given a significance level of 10% and df=6, we find the critical value as X2
0.10, 6=10.645. Hence, the
decision rule is to reject H0 if X2 0.10, 6>10.645. Since, X2
0.10, 6=13.809 >10.645, we can reject the null
hypothesis. At 10% significance level, we conclude that the two qualitative variables are dependent;
that is, there is a relationship between monthly expenditure on fuel and owing a loyalty card.
Chi-Square Tests
Value df
Asymptotic
Significance (2-
sided)
Pearson Chi-Square 13.809a 6 .032
Likelihood Ratio 14.519 6 .024
Linear-by-Linear Association 6.659 1 .010
N of Valid Cases 107
a. 5 cells (41.7%) have expected count less than 5. The minimum
expected count is .79.

24. H60: Making use of benefits of loyalty cards and monthly expenditure on fuel are independent.
H6A: Making use of benefits of loyalty cards and monthly expenditure on fuel are dependent.
Given a significance level of 10% and df=3, we find the critical value as X2
0.10, 3=6.251. Hence, the
decision rule is to reject H0 if X2 0.10, 6>6.251. Since, X2
0.10, 6=7.561 >6.251, we can reject the null
hypothesis. At 10% significance level, we conclude that the two qualitative variables are dependent;
that is, there is a relationship between monthly expenditure on fuel and making use of benefits of
loyalty cards.
Chi-Square Tests
Value df
Asymptotic
Significance (2-
sided)
Pearson Chi-Square 7.561a 3 .056
Likelihood Ratio 7.520 3 .057
Linear-by-Linear
Association
3.120 1 .077
N of Valid Cases 107
a. 2 cells (25.0%) have expected count less than 5. The minimum
expected count is 2.81.

25. T-Test
H70: The mean monthly expenditure on fuel is Rs 3000.
H7A: The mean monthly expenditure on fuel is not equal to Rs 3000.
Given a significance level of 10% and df=106, we find the critical value as t 0.90, 106= 2.3271. Hence, the
decision rule is to reject H0 if t 0.90, 106>2.3271. Since, t 0.90, 106 <2.3271, we cannot reject the null
hypothesis.
Price
Frequency
middle mf (m-mean)^2 X f
0-2500 7 1250 8750 7468755
2501-5000 59 3750 221250 7.36E+08
5001-7500 26 6250 162500 9.46E+08
>7500 15 8750 131250 1.09E+09
107 523750 2.78E+09
mean 4894.86 variance 44876749 standard deviation 6699.01
H0: u=3000
Ha: u not equal to 3000
df 106
t 2.24510504
Critical values are -2.3271 2.3271
We cannot reject null hypothesis.

26. Recommendations
• Retail fuel companies should focus on creating more awareness about the loyalty cards
amongst its consumers and the benefits that accompany the loyalty card.
• Since, the perceived card benefits have a positive impact on consumers’ intension to use
the card, benefits should be attractive and consumers should be well informed about
them.
• Study suggests that affective loyalty has a moderate positive relationship with
consumer’s intension to use the card. More focus should be on improving consumers
shopping experience and building trust in the relationship.
• Study also reveals presence of relationship between monthly expenditure on fuel and
owing a loyalty card or making use of benefits of loyalty card. Companies should collect
data of their consumers and create awareness about loyalty card among high spending
consumers.

27. Conclusion
• From the collected data it can be inferred that there is less awareness about loyalty card
being offered by retail fuel companies in India and its benefits.
• A Pearson correlation was run to determine the relationship between retail fuel
companies’ consumers’ intension to use the card and perceived benefits of the card.
There was a weak, positive linear correlation between the two (r=0.334, N=107,
p<0.001).
• A Spearman’s correlation was run to determine the relationship between retail fuel
companies’ consumers’ intension to use the card and affective loyalty. There was a
moderate, positive correlation between the two which was statistically significant
(r=0.452, N=107, p<0.001).
• Regression analysis revealed that around 12% of variation in consumer intension to use
the card can be explained by perceived card benefits. For every one unit change in
perceived card benefits, the consumer intension to use the card increases by 0.442 and it
contributes statistically significantly to the model.

28. • Chi-square test was performed to determine whether or not owing a card and monthly
expenditure on fuel are dependent. At 10% significance level, we conclude that there is a
relationship between monthly expenditure on fuel and owing a loyalty card.
• Chi-square test was performed to determine whether or not the gender of a consumer
and use of card benefits are dependent. At 10% significance level, we conclude that no
relationship exists between the two.
• T-test was performed to determine whether the mean monthly expenditure on fuel is Rs
3000. At 10% significance level, we conclude that null hypotheses cannot be rejected and
mean monthly expenditure on fuel is Rs3000.