Identifying Target Consumers for Organic Products Using Data Analysis

This assignment focuses on analyzing supermarket customer data to identify the target consumers for a new line of organic products. It involves using Excel to analyze customer loyalty program data, including demographics, spending habits, and regional preferences. The analysis identifies females in the Southeast region as the primary target demographic due to their higher purchase rates and loyalty. Visual presentations of the data further support this conclusion. The report recommends that the supermarket focus its marketing efforts on this demographic to improve organic product sales. The use of big data analytics is crucial for informed business decisions.

ACCOUNTING AND INFO
SYS

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................3
MAIN BODY...................................................................................................................................3
Identifying the target consumers and preparing report...............................................................3
Visual presentation of the data....................................................................................................5
CONCLUSION................................................................................................................................7
REFERENCES................................................................................................................................8

INTRODUCTION
For any business to get successful it is essential that all the work is being done effectively
and efficiently. The reason behind this fact is that when the decisions are not taken effectively
then it will affect the quality of working. The present study is based on supermarket chain that
has recently started offering organic products. The current study will outline the use of data in
order to ensure that which target will be most suitable for the company to get successful. The
study will include the use of analysis of data with help of Excel and various formulas.
MAIN BODY
Identifying the target consumers and preparing report
For the organic product to be successful the most essential aspect for the company is to
analyse its target consumer (Hariri, Fredericks and Bowers, 2019). The reason behind this fact is
that in case started consumer will not be selected properly then it will affect the working and
efficiency of the company.
Total amount spent on basis of gender
Count of Prom
Spend
Dem
Gender
Prom Time Blank F M U Grand
Total
0 7 27 12 3 49
1 173 946 474 129 1722
2 183 868 386 143 1580
3 122 587 281 87 1077
4 276 1460 718 211 2665
5 477 2384 1140 313 4314
6 132 665 264 79 1140
7 158 775 352 111 1396
8 416 1749 863 255 3283
9 207 925 408 118 1658
10 59 299 151 50 559
11 66 366 176 56 664
12 45 207 116 37 405
13 22 107 54 10 193
14 13 69 39 17 138
15 12 59 41 12 124

16 19 70 43 11 143
17 10 45 24 8 87
18 13 49 26 11 99
19 4 33 19 11 67
20 2 21 16 5 44
21 8 41 20 10 79
22 3 14 11 1 29
23 3 22 6 2 33
24 3 16 14 1 34
25 12 22 12 7 53
26 6 24 14 7 51
27 8 28 15 1 52
28 2 17 7 1 27
29 4 24 11 4 43
30 4 21 10 5 40
31 8 24 10 3 45
32 3 17 8 2 30
33 1 3 2 2 8
34 1 1
35 4 4
36 1 3 4
38 1 1
39 1 1
(blank) 29 156 72 24 281
Grand Total 2512 12149 5815 1747 22223
Based on target amount that is number of organic product purchased
Count of Target
Buy
Dem
Gender
Target Amt Blank F M U Grand
Total
0 2283 7944 4849 1642 16718
1 174 3539 821 91 4625
2 47 538 118 12 715
3 8 128 27 2 165
Grand Total 2512 12149 5815 1747 22223
Based on region
Count of Prom Class Column Labels
Row Labels Blank F M U Grand Total

Blank 50 251 128 36 465
Midlands 779 3633 1793 536 6741
North 470 2404 1113 337 4324
Scottish 153 731 376 108 1368
South East 980 4764 2212 678 8634
South West 80 366 193 52 691
Grand Total 2512 12149 5815 1747 22223
With an analysis of the above tables it is clear that the major target of the company will
be over the females. The reason particularly behind this fact is that females are the one who are
having the highest data in comparison to others on every aspect. Whether it be on basis of from
time then also female is having the largest number of count. With the above table it is evident
that the maximum number of time as a loyalty card member is 5 years. In the fifth year as well
the females is having the largest data that is 2384 which implies that female will be a better
target (Ghani and et.al., 2019). Furthermore, on the basis of the number of organic product being
purchased also denotes that maximum is the females. Further on the basis of the geographic
region it is clear that here as well females are the highest. Along with this it is evident that south
east is the region which needs to be targeted. The reason behind this fact is that south east is
having the highest count of sales that is 8634. Hence the major target of the supermarket for the
organic product will be south east region and females.
Visual presentation of the data
Total amount spent on basis of gender

Based on target amount that is number of organic product purchased
Based on region
Also with the help of the visual presentation it is clear that on the basis of all the three
elements female is the one who is having the majority of the customers. Thus it is recommended
to the supermarket that they must focus on female is particularly within the south east region
(Zhu and et.al., 2018). The south east region is been selected because it is having the maximum

count of sale of the product. Hence, the recommendation of targeting the females in south east
region will be beneficial to company in order to improve their sales.
CONCLUSION
In the end it is concluded that Big data analytics is very essential for taking decisions of
the business. This is particularly because of the reason that these data provide some base to the
company relating to its performance. The above report also evaluated that use of excel and its
various function is helpful in order to take some decisions. For the dream report concluded that
term female is the best target for company to improve its sales with a focus on southeast region.

REFERENCES
Books and Journals
Ghani, N. A., and et.al., 2019. Social media big data analytics: A survey. Computers in Human
Behavior. 101. pp.417-428.
Hariri, R. H., Fredericks, E. M. and Bowers, K. M., 2019. Uncertainty in big data analytics:
survey, opportunities, and challenges. Journal of Big Data. 6(1). pp.1-16.
Saggi, M. K. and Jain, S., 2018. A survey towards an integration of big data analytics to big
insights for value-creation. Information Processing & Management. 54(5). pp.758-790.
Zhu, L. and et.al., 2018. Big data analytics in intelligent transportation systems: A survey. IEEE
Transactions on Intelligent Transportation Systems. 20(1). pp.383-398.