1) The document analyzes data from a survey of 101 respondents regarding their online food buying behaviors and perceptions. 2) Key factors that influence customer satisfaction with online food buying services are identified through correlation and regression analysis. Variation, convenience, and quality have the highest correlation with customer satisfaction. 3) Recommendations for online food sellers include focusing on fast delivery, quality, variation, convenience, and customer satisfaction based on the regression analysis results. 4) The target market for online food buying is identified as ages 18-28, nuclear families, students and businessmen with incomes below 10,000 TK based on the demographic analysis.

2. Name Id
RAHMAN,MD.MOSTAFIZUR 18-37125-1
Chowdhury Sakib Hasan 18-38290-2
Saha Sourav 17-35809-3
TASLIM HOSSAIN 18-36806-1
Hasan,Sakib 18-36143-1

5. Male Female
68.3% 31.7%
Gender

6. AGE
BELOW 17
18-28
YEARS
29-39
4.0% 91.1% 5.0%
Family type
Joint Nuclear
35.6% 64.4%

7. MARRIED
90.1%
UNMARRIED
9.9%
Level of income
Below Tk. 10,000 68.3%
Tk. 10,001-20,000 7.9%
Tk. 20,001- 30,000 5.9%
Tk.30,001-50,000 7.9%
Tk.50,001 & above 9.9%
Marital Status

8. Occupation
student 89.1
businessman 5.9
service holder 2.0
housewife 2.0
others 1.0

10. In a reliability analysis the standard Cronbach's Alpha
should be more than .700. In our study we found our
Alpha value is .960 which is within acceptable value so
we can say our study variance is reliable.
Reliability Statistics
Cronbach's Alpha
Cronbach's Alpha
Based on
Standardized Items N of Items
.960 .961 42

12. Scale Used?
What will we consider?
Likert Scale
Mean Value over 3.5
Standard Deviation less than 1

13. I prefer foods buying for various categories of food from different types of
restaurants
I can buy different types of food’s from one online shops
I can buy the highest quality food in an online hotel shops, and
restaurants.
The time saving of online food buying from the apps because easy I don’t
need to go at the restaurants
I prefer online food buying because easy buying food accessibility
I can save myself from crowd, chaos of traffic by doing food order by the
apps as pandemic going
I can buy food from anywhere any time by using the apps
I can buy food from anywhere any time by using the apps
I prefer to get online promotion offerings
I prefer online food buying cause various food delivery app are here like
food panda and others food delivery food app
I prefer online food buying cause its I get the food rather then I go to the
restaurant.
I can buy different types of food’s from one online shops.

14. I prefer online Food buying
I referred others to buy from online Food.
If I buy again food, I will buy from online
Over all I am satisfied with online food buying
I can buy the highest quality food in an online shop
I prefer online food buying cause various food delivery app are here like food panda
and others food delivery food app

16. Correlations
App_
Ordering
Coupo
ns
Conve
nience
Vari
ation
Promotio
nal
_Act
Fast
_dlv Quality
Cus_
satisfa
ction
Facebo
ok_
Orderin
g
Delivery
_mn
Time_
saving
App_Ordering Pearson
Correlation
1 .482**
.498**
.651*
*
.763**
.525**
.485**
.673**
.630**
.664**
.886**
Sig. (2-
tailed)
.000 .000 .000 .000 .000 .000 .000 .000 .000 .000
N 101 101 101 101 101 101 101 101 101 101 101
Coupons Pearson
Correlation
.482**
1 .227*
.318*
*
.878**
.524**
.273**
.330**
.341**
.628**
.418**
Sig. (2-
tailed)
.000 .022 .001 .000 .000 .006 .001 .000 .000 .000
N 101 101 101 101 101 101 101 101 101 101 101
Convenience Pearson
Correlation
.498**
.227*
1 .749*
*
.367**
.482**
.983**
.762**
.469**
.592**
.442**
Sig. (2-
tailed)
.000 .022 .000 .000 .000 .000 .000 .000 .000 .000
N 101 101 101 101 101 101 101 101 101 101 101
Variation Pearson
Correlation
.651**
.318**
.749**
1 .503**
.458**
.701**
.980**
.526**
.602**
.590**
Sig. (2-
tailed)
.000 .001 .000 .000 .000 .000 .000 .000 .000 .000
N 101 101 101 101 101 101 101 101 101 101 101
Promotional_Act Pearson
Correlation
.763**
.878**
.367**
.503*
*
1 .552**
.379**
.512**
.550**
.682**
.599**
Sig. (2-
tailed)
.000 .000 .000 .000 .000 .000 .000 .000 .000 .000
N 101 101 101 101 101 101 101 101 101 101 101
Fast_dlv Pearson
Correlation
.525**
.524**
.482**
.458*
*
.552**
1 .510**
.451**
.426**
.864**
.527**
Sig. (2-
tailed)
.000 .000 .000 .000 .000 .000 .000 .000 .000 .000
N 101 101 101 101 101 101 101 101 101 101 101
Quality Pearson
Correlation
.485**
.273**
.983**
.701*
*
.379**
.510**
1 .705**
.424**
.633**
.437**
Sig. (2-
tailed)
.000 .006 .000 .000 .000 .000 .000 .000 .000 .000

17. App
odering Time saving
coupons
promotional
convenience
quality
Variation Customer
satisfaction
88.6%
87.8%
98.3%
98%

18. Promotional
act
Coupons
Fast
delivery Delivery
Quality
convenience
Customer
Satisfaction”
variation
87.8%
86.4 %
98.3%
98%

20. ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 50.404 10 5.040 367.470 .000b
Residual 1.234 90 .014
Total 51.639 100
a. Dependent Variable: Cus_satisfaction
b. Predictors: (Constant), Quality, Coupons, Facebook_Ordering, Time_saving, Fast_dlv, Variation, App_Ordering, Delivery_mn, Promotional_Act, Convenience
In this ANOVA table it is showing that the significant value is .000 which means that the model is fit in
explaining consumer food buying behavior.

21. Coefficientsa
Model
Unstandardized Coefficients Standardized Coefficients
t Sig.
B Std. Error Beta
1 (Constant) .047 .084 .558 .578
App_Ordering .002 .069 .002 .024 .981
Coupons .073 .048 .083 1.523 .131
Delivery_mn .118 .044 .126 2.710 .008
Convenience .638 .104 .725 6.144 .000
Variation .825 .031 .821 26.582 .000
Promotional_Act -.076 .077 -.072 -.991 .324
Fast_dlv -.087 .029 -.103 -2.970 .004
Facebook_Ordering -.030 .025 -.028 -1.202 .233
Time_saving .088 .039 .098 2.269 .026
Quality -.557 .098 -.637 -5.656 .000
a. Dependent Variable: Cus_satisfaction

22. Dependent Variable Customer Satisfaction
Significant
app ordering
coupons
delivery mn
promotional act
Facebook ordering
In this analysis the highest Beta value is .821 which contain with variation factor and the second highest beta
value is .725 then 3rd highest beta value is .98 4th

24. Recommendation from Demographic Analysis
Target Age Group
Target Occupation Group
Target Education Group
Target Income Level
18-28 years old
occupation & businessman
Bachelor
0-10,000 Tk
Family Type Nuclear

25. Recommendation From Descriptive Analysis
Online Food Buying Should Focus on:
Keep various food item.
Maintaining the quality of food is important.
The food buying apps must be user friendly
It is important to provide the customer the most easiest way to order food from their
home
The seller or service provider must offer discount and offer frequently.
It is important to deliver fast as soon as possible.
The satisfaction level of people those are buying from online is high so it important to
keep that satisfaction level and improve it more.
Mean value more
than 3.5
& Std less than 1

26. Recommendation From Correlation
App
ordering promotional
act
APP
ordering Time
saving
coupon
factor Delivery
76%.
88%
62%

27. coupon
factor promotional
convenience
customer
satisfaction
87%
76%

28. Recommendation from regression
Marketers should concentrate more on improving fast delivery ,quality, variation, time saving ,
convenience ,customer satisfaction towards online food delivery services.

29. New Model
Fast delivery
Quality
Variation
Time saving
Convenience
Customer satisfaction

30. Conclusion
This research was objected to find out that how the different variables influence customers perception
about online food buying services and what factor influence them to buy food from online.
Over all this study was able to define the variables that influences customer satisfaction towards online
food buying services in Dhaka city. So from the knowledge of this study marketers can get to know
about their customer’s perception and improve accordingly.