CzxCXZCZX

1. SHOPEE AS A DATA SOURCE FOR CONSUMER
PREFERENCES IN THE CONTEXT OF BUSINESS
INTELLIGENCE
Denice Ann D. Dela Cruz
+63 915 825 9289
delacruzdeniceann@gmail.com
Cedrick I. Dela Cruz
+63 921 584 1631
cdrckdc4500@gmail.com
Harlene Leharn G. Dusaran
+63 965 228 2629
leharndusaran@gmail.com
Lyca R. De Leon
+63 905 743 0906
lycadeleon026@gmail.com
ABSTRACT
This study examines the Analysis of Consumer Preferences in
using Shopee Data as a Data Source of Business intelligence.
The study concentrated on the consumer preferences and
business intelligence of the data. The respondents are the experts
and owners of Peachy Keen Decors. A standardized
questionnaire was used to gather this study's data sent to the
respondents through Facebook Messenger and e-mail. The coded
data were processed using descriptive statistics and analyzed to
get the present findings. Consumer preference reflects consumer
demand because it dictates what items consumers will purchase
within their budget. Forecasting sales, orders, visits, and
pageviews enable sellers to meet their objectives by identifying
early warning signs in their sales pipeline and allowing them to
course-correct before it is too late. It demonstrates that by
understanding each customer's purchase cycle, the future market
may be forecasted more precisely utilizing historical data. The
findings indicate that forecasting may assist a business in
making more informed decisions through planning. It
contributes to strategic planning, budgeting, and risk
management. Forecasting enables businesses to accurately
anticipate their expenditures and income, enabling them to
foresee their short- and long-term performance. It is concluded
that the demographic dashboard could be used as a data source
of business intelligence to inform, become a more effective
marketing strategy, give and provide better decisions to guide
the business operation thoroughly.
Keywords
Business Intelligence, consumer preference, forecasting,
dashboard, business
Permission to make digital or hard comes of all or part of this work for personal or
classroom use is granted without fee provided that copies are not made or
distributed for profit or commercial advantage and that copies bear this notice and
the full citation on the first page. To copy otherwise, or republish, to post on
servers or to redistribute to lists, requires prior specific permission and/or a fee.
Conference”10, Month 1-2, 2010, City, State, Country,
Copyright 2010 ACM 1-58113-000-0/00/0010 ...$15.00.
1. INTRODUCTION
The current state of business is substantially challenged by the
global economic downturn, globalization, and the current nature
of demand. Demand and technology are also pushing
competitiveness to the limit, pushing the industrial-age
management strategy of running businesses to make way for the
information-age method. There have already been several
significant developments in the 21st century. The consistency of
change in the advancement of technology made its way to be
part of everyday living. Especially the rapid growth of the
Internet caused numerous changes in the form of social
communication and interaction. However, the discovery of e-
commerce and business intelligence (BI) also impacted
everyone's life [2].
Nowadays, with developments in internet technology, online
transactions are every day. In recent years, the world's Internet
penetration rate has accelerated, especially in the Philippines. By
establishing e-commerce, the growing number of internet users
creates a new business opportunity with a good market share.
Businesses or transactions handled electronically are referred to
as e-commerce [3]. Shopee is a popular e-commerce app in the
Philippines established among millennials. Shopee began its e-
commerce adventure as a customer-to-customer (C2C) company
but later evolved to a hybrid C2C model. Consumers make
decisions for the best level of happiness by distributing their
limited income among all accessible commodities. Executives
recognize the value of customer reference in corporate
marketing [7]. Business intelligence can help companies better
understand, forecast, and influence their customers' behavior by
providing clear insights into how they think, behave, and spend
their money using Big Data [5]. Businesses can better serve their
customers and increase profits from existing customers while
attracting new customers who are more focused on their needs,
wants, and behavior.

2. This research aims to develop a dashboard that can be used as a
data source of business intelligence to inform and give better
decisions to guide the business thoroughly and become more
effective marketing. Specifically, it aimed to answer the
following questions:
1. How may the consumer’s preference dashboard be
described in terms of sales, orders, visits, and
pageviews?
2. What is a forecast of future sales performance?
3. What is a projection of future orders?
4. What is the prediction of future visits?
5. What is the forecast of future pageviews?
6. What is the expert’s evaluation of the dashboard in
terms of usability, sustainability, and maintainability?
7. How may the main design features of the dashboard be
helpful in the decision-making process?
8. What are the comments and suggestions of the expert
evaluators?
The research findings on that objective would improve the
business intelligence to assist CEOs, company managers, and
other operational employees in better and more informed
company decisions. Companies may also use business
intelligence to reduce expenses, uncover new prospects, and
detect wasteful business processes. The help of Business
Intelligence directly impacts an organization's strategic, tactical,
and operational business choices. Instead of guessing and
intuition, BI fosters fact-based decision-making based on
historical data. It may effectively benefit the following group of
people: entrepreneurs, students, and future researchers.
2. METHODOLOGY
This study used a convergent mixed-method approach to gather
and evaluate data and simultaneously collected qualitative and
quantitative data. Because a mixed-method design can provide
complete and comprehensive data to meet the research aims and
answer the research questions, mixing qualitative and
quantitative methods has become more prevalent in recent years
in research. Data gathered used descriptive analytics, a branch of
statistics concerned with collecting and summarizing raw data to
be easily analyzed. Descriptive analytics generally focuses on
historical data, providing the context needed to comprehend data
and numbers. The study's respondents are experts and owners of
the Peachy Keen Decors.
The data of this capstone research was collected using a survey
questionnaire in a google form. The survey was created using
relevant questions adopted from the Software Evaluation:
Criteria-based Assessment by Mike Jackson, Steve Crouch, and
Rob Baxter (2011). The researchers assured confidentiality of
their survey sheets since the identities are not necessary. Expert
evaluators and business owners were given time to respond, and
then the researchers collected the surveys. There were no
incentives offered for participating in the capstone research.
After the data gathering, the researchers collected it for the
tallying and tabulating of scores and applied the statistical
treatment needed for the study.
2.1 Statistical Analysis of Data
The researchers used the PowerBI, where the gathered data were
encoded and analyzed. The data collected were tallied, tabulated,
analyzed, and interpreted.
The forecast of future sales performance, orders, visits, and
pageviews
Forecast is used to forecast a future value using simple linear
regression. In other words, a forecast predicts a future value
based on historical data along a line of best fit.
Step 1: Create Calculated Columns and Measures
The formula for the equation of a line is y = mx + b.
Where:
y = How far up the y axis
m = Slope (Change in y divided by change in x) =
x = How far along the x axis
b = b-intercept (The value of y when x = 0) =
After finding out m and b with some calculations, we
can input any data point for x, and the output will be y.
We are going to create this formula using DAX
calculated columns and measures. These are the
Calculated Columns we need to make and their DAX
syntax:
Math Formula DAX Formula
x² xsq =Table Name[x]^2
xy xy =Table Name [x]* Table
Name [y]
xy
These are the Measures we need to make and their
DAX syntax:
Math Formula DAX Formula
n n = COUNTROWS(Table
Name)
∑xy xysum = SUM(Table Name
[xy])
∑x xsum = SUM(Table Name
[x])
∑y ysum = SUM(Table Name
[y])
∑x² xsqrsum = SUM(Table
Name [xsq])
(n(∑xy)-
(∑x)(∑y))/(n(∑x²)-
(∑x)²)
m (Slope) =
DIVIDE(
[n]*[xysum]-
[Xsum]*[Ysum],
[n]*[xsqrsum]-

3. [Xsum]^2,
0
)
((∑y)(∑x^2)-
(∑x)(∑xy))/(n(∑x²)
-(∑x)²)
b (Intercept) =
DIVIDE(
[ysum]*[xsqrsum]-
[Xsum]*[xysum],
[n]*[xsqrsum]-
[Xsum]^2,
0
)
Step 2: Setting up a What-if parameter
Now that calculations have been performed, for any
number inserted into x, the formula will predict y. A-if
parameter with a slicer shall be used to demonstrate
this. A What-if parameter allows creating an
interactive slicer with a variable to visualize and
quantify another value in the report.
Name: x (x)
Data type: Whole Number
Minimum: 0
Maximum: 0
Increment: 1
Add slicer to this page: Yes
Step 3: Complete the measure for the equation of a
line and visualize
Finally, create the Predicted Value measure that
contains the complete formula for the regression
equation of a line y = mx + b, using the previous
components.
Math Formula DAX Formula
y = mx + b Predicted Value =
([m (Slope)]*
‘x (x)'[x (x)Value]+
[b (Intercept)]
)
2.2 Presentation and description of the
system
The researchers devised a plan to give the clientele firm a
Demographic Dashboard, which they dubbed Peachy Keen
Decors Demographics Dashboard. Demographic dashboards
visualize purchasers' demographic information. It allows
organizations to understand their consumers better and address
their demands more efficiently. It enables businesses to sell
more strategically and precisely. Since individuals have unique
interests, a one-size-fits-all marketing plan is unlikely to appeal
to every target market member. Businesses may establish highly
targeted marketing efforts by segmenting their customers into
several demographic groups. They can optimize resource
allocation and maximize the return on marketing spending.
Shopee sellers may utilize the demographic dashboard to
construct personalized brand narratives that connect with
targeted market groups to advertise and sell their products or
services. Consumers readily identify with customized brand
narratives and are prepared to support firms that share them.
Also, the forecasting features were added to the demographic
dashboard. Business forecasting refers to the tools and
techniques used to predict business developments such as sales,
orders, visits, and page views. Business forecasting aims to
create better strategies based on accurate predictions using
historical data to forecast the company's future performance.
Historical data includes the company's financial statements,
client invoices, and any other information with relative
predictive value for the company's future success.
3. RESULTS AND DISCUSSION
3.1. Consumer’s Preference Dashboard of
Sales, Orders, Visits, and Pageviews
Figure 1. Consumer’s Preference Dashboard described in
Sales, Orders, Visits, and Pageviews
These are the results of the sales, orders, visitors, and page views
of the Peachykeendecors Demographic Dashboard. Php142
000.00 are earned over the last six months from July to
December when it comes to sales. This data shows that the
average per month is Php23 666.00, and it is surprisingly good
for an online seller of home decorations. There have been 269
orders in total, with an average of 45 shipments each month. A
total of 200,000 people has visited the shop's website averaging
33,333 visitors per month; this indicates that the number of visits
is continually increasing. The shop's page views have reached
60,000, with an estimated 10,000 views per month. As a result,
the data presented above has achieved a satisfying outcome
during the last six months.
By establishing measurable goals and deliverables, businesses
can better plan for demand changes in the coming business
cycle; no more wasting time with BI dashboards that generate
reports from multiple systems. Instead, information is gathered
from a single source and presented in a simple visual overview.
3.2. Forecast of Future Sales Performance

4. Figure 2. Forecast of the subsequent six-monthly sales
Figure 2 presents a simple linear regression to predict sales value
for the next six months from January to June 2022 with the
historical data from July to December 2021. As shown, the
results of this linear regression analysis and expected forecast
that the number of sales is top-down. The sales performance is
forecasted to be Php 47,710 in January. It depicts that January
shows the highest number of goods sold in a given targeted time
on Peachy Keens Décor. That also shows the decreasing trend
by the next five months. Begin by considering how many
potential customers the business might contact through
advertising, sales calls, or other marketing methods, which will
help generate more revenue. A solid sales strategy or plan
outlining the milestones must be met to increase sales. This
strategy is a set of actions to promote the sale of a product or
service. The goal should be tailored to the customers' specific
requirements. Every successful business has a strategy for
increasing sales. After developing and implementing the
process, it can examine the sales figures and adjust the approach
if sales are not growing. Use the sales strategy to understand the
customers' needs better, how they intend to sell to them, and
how the competitors succeed or fail to reach them.
Increasing the visibility to potential purchasers is one of the keys
to increasing Shopee sales. The Shopee My Campaigns feature
allows placing specific products in high-traffic areas of the
website.
3.3. Projection of Future Orders
Figure 3. Forecast of the next six-monthly orders
Figure 3 presents a simple linear regression used to predict the
value of orders for the next six months from January to June
2022 with the historical data from July to December 2021. As
shown, the results of this linear regression analysis and expected
forecast that the number of orders is top-down. It depicts that
January shows 87.82 predicted orders, the highest number
ordered on Peachy Keens Decor. That also shows the decreasing
trend by the next five months. Give the customers a broader
range of products or services. Market research is required to
determine whether there is a demand for the proposed offering.
As a test group, consider using some of the current customers.
Receiving feedback from a test group can assist in reducing risk
and learning how to improve the product or service. To be aware
of new products or services, pay close attention to marketing and
promotion.
Shopee created top Picks from Shop to encourage cross-selling.
This tool allows sellers to create collections of four to eight
products to display on their product pages. Customers will be
more likely to add more products to their shopping carts,
increasing Shopee sales.
3.4. Prediction of Future Visits
Figure 4. Forecast of the subsequent six-monthly visits
Figure 4 presents a simple linear regression used to predict the
value of visitors for the next six months from January to June
2022 with the historical data from July to December 2021. As
shown, the results of this linear regression analysis and expected
forecast that the number of visitors is top-down. It depicts that
January shows the 6,680 highest number who visits the Peachy
Keens Decor. That also shows the decreasing trend by the next
five months. The result suggests becoming a preferred seller to
attract more buyers who consider the emblem a guarantee of
high-quality products and services. Preferred Sellers also get
higher search ranks, which means customers may find them
more easily. Their products receive greater attention, which
leads to more orders and increased shop sales.
3.5. Forecast of Future Pageviews
Figure 5. Forecast of the subsequent six-monthly pageviews
Figure 5 presents a simple linear regression used to predict the
value of page views for the next six months from January to
June 2022 with the historical data from July to December 2021.
As shown, the results of this linear regression analysis and
expected forecast that the number of pageviews is top-down. It
depicts that January shows the 22 620, the highest number who
viewed the page on Peachy Keens Decor. That also shows the
decreasing trend by the next five months. Suggest that one key
strategy to boost total page views is to increase the number of
pages per visit and lower the bounce rate. Because the other
measure always moves in the opposite direction in response, a
company only needs to focus on one.

5. 3.6. Evaluation of the Dashboard
Figure 6. Experts’ Evaluation
(a) Usability
Based on the evaluation by the experts in usability,
understandability is the concept that a dashboard should be
presented so that one can easily comprehend it. The more
understandable a dashboard is, the easier it will be for the owner
or user to change it predictably and safely. The dashboard's
success is dependent on good documentation practices. An
interactive User Experience, Information Architecture, and a
thorough understanding of your target audience are all required
components of documentation. Learnability signifies how
quickly a new user can begin interacting with a dashboard in an
efficient and error-free manner. The learnability of such a
dashboard is determined by how quickly and easily users can
understand its design layout to achieve their goals.
The majority of the expert evaluators assess the Dashboard as
usable, sustainable, and maintainable; however, it can be noticed
that the highest red bar in a graph relates to how easy it is to
learn to use its functions. This result gave an overall idea of how
to measure the quality and characteristics of the Dashboard.
(b) Sustainability and Maintainability

6. Based on the evaluation by the experts, the capacity of the user
to recognize and understand the specific figures, patterns, and
trends associated with the data being represented should be
considered when evaluating the dashboard’s success.
The demographic dashboard depicts a mathematical and
graphical tool for integrating complicated sustainability impacts
and supporting decision-making through brief analyses. The
dashboard allows rig operators and maintenance employees to
make more strategic decisions that extend asset life and reduce
downtime according to the results.
This can only be accomplished through various design
considerations that go beyond aesthetics. Even the most
appealing display can be rendered worthless by busyness,
confusing or incongruent images, and language lacking clarity or
meaning. The user must engage in prolonged decoding to grasp
the represented data [1]. As a result, the quality of a dashboard’s
design determines its effectiveness. Enhance the user experience
by improving the design.
Overall, this is the result of the assessment for the dashboard
answered by the target respondents, which has seven expert
responses, including the end-user. It comprises two significant
indicators with underlying questions, answered yes or no. This
result gave an overall idea of how to measure the quality and
characteristics of the dashboard.
3.7. Main Design Features of the Dashboard
Deemed Helpful In The Decision-Making
Process
The dashboard displays the most important metrics that provide
information about the store’s performance and the customers’
behavior. The metrics are displayed numerically as well as
graphically when appropriate. The percentage change from the
previous date range can be said for all metrics. A short video
demonstration is viewable on this link:
https://www.youtube.com/watch?app=desktop&v=RKdsA8sNB
sM&feature=youtu.be&fbclid=IwAR1bIauprCtwzDus0hTl7Ta0
xXPvKVdtasH1_Qr_z_I9qAlQfpodtUlmu5c
The Overview page comprises five areas of information display
(see Figure 7): (1) sales, (2) orders, (3) visitors, (4) page views,
and (5) key metrics.
Figure 7. Overview of Sales Trends and Performances
The focus of the overview page displays critical data such as
sales, orders, online store visitors, and page views. It can see
how the store is doing in a single glance, across all sales
channels and for any period. The shop’s conversion rates and
sales performance are displayed by product category, order, and
buyer composition in the sales report. Total charges show the
total number of orders placed. Any time a visitor arrives at the
website from a domain other than own, it is referred to as a visit.
That means they were on another website when they clicked on
a link, or they typed the website’s URL into their browser
directly. When a visitor comes to the site from another domain, a
new visit is created to track the visitor’s activity across the
environment’s pages. Only when a visitor leaves the part by
visiting another website or closing their browser window do
their visitors come to an end [8]. Pageviews are the number of
visitors to the store’s page. If a customer visits multiple pages in
the store, the total number of page views increases. More traffic
usually means more conversions, and more modifications
directly translate into higher search and product ranking [4] [9].
Key Metrics are statistics that measure an organization’s overall
performance based on its value. All organizations, from non-
profits to multinational corporations, must track critical metrics
to picture what is going on accurately. Simply looking at key
metrics can provide an organizational reading that would
otherwise necessitate sophisticated data analysis.
Product Sales Page provides an in-depth analysis of the store’s
performance. Select a month range to view the statistics for each
separately. The owner can view individual item stats and see the

7. most sales from the top product graph. Top products by units
sold display the best-selling items in the store. This is valuable
information to have for marketing and inventory purposes.
These products can also be recommended to new customers or
mentioned in social media promotions. Product sales refer to the
act of selling a product or service in exchange for money,
compensation, or a service. Product sales occur when a customer
purchases a product or service that fulfills a need. The number of
products sold in a given time contributes to product sales.
Figure 8. Product Sales Page
The Demographic Page provides a detailed view of indicator
performance at a local scale and information on-demand in
various parts of the Philippines. This page makes dataset
exploration easier by allowing the user to look into the
demographic profile of each indicator’s consumer. Businesses
can create personalized marketing strategies that appeal to
specific consumer preferences with demographic pages. As a
result, customers will quickly identify with the brand across
multiple touchpoints, improving the overall customer experience
and increasing customer loyalty. They can better understand the
target market’s needs and develop their product or service by
segmenting them into demographics. It can, for instance, create
different product packages to appeal to other age groups of
customers. When it comes to segmenting by location, there are
many options. A province, a district, or a region are all
possibilities. This can also help a company find a new
geographic area to expand. This increases sales and strengthens
the customer-company relationship. Reducing the time and
effort required to locate relevant items gives customers a better
user experience.
Figure 9. Demographic Page
Overall, demographic segmentation assists focus and a more
effective streamlining of resources for companies and marketers,
in addition to helping them better understand current and future
customers. Demographic segmentation is also one of the primary
ways businesses segment their users, giving them one of the
most straightforward methods to analyze statistics that can be
used to group entire populations [6].
Figure 10 and 11 shows the forecast of the Peachy Keen Decors
for the next six months from January to June 2022 with the
historical data from July to December 2021. These are the
statistical treatment embedded in the dashboard that may help
the user in decision making by determining the predicted sales,
orders, visits, and pageviews on the next six months using linear
regression. As you can see, both charts show the direction of
trendlines.
Figure 10. Predicted Sales and Orders
It shows the predicted sales output for January is 47,710, same
goals for the orders with the expected result of 87.82.
Figure 11. Predicted Page views and Visitors
It applies the same statistical treatment with the predicted output
pageviews. It reached 22,620, and for the visitors, the expected
output is 6,680.
The Forecasting page uses historical data to make informed
predictions about future trends of sales, orders, page views, and
visits. Businesses use forecasting to determine how to allocate
their budgets or plan for anticipated expenses in the future. This
is usually based on the expected demand for the goods and
services provided.

8. This forecasting page in the dashboard aims to develop better
strategies based on these informed predictions, thereby
preventing potential failures or losses.
3.8. Expert Evaluators’ Comments and
Suggestions
Overall, this is the result of the assessment for the dashboard
answered by the target respondents, which has seven expert
responses, including the end-user. It comprises two significant
indicators with underlying questions, answered yes or no. This
result gave an overall idea of how to measure the quality and
characteristics of the dashboard.
Table 1 contains actionable tips, comments, and suggestions
regarding the Peachy Keen Decors Demographic Dashboard that
can be used to improve the value or effectiveness of the
dashboard—creating an engaging dashboard to effectively
communicate metrics and assist the users in making
decisions—providing the appropriate types of charts that are
simple to read and provide crucial information at a glance.
Table 1. Comments and Suggestion by the Expert and End-
user
Expert 1 It should provide the user with quick access to
information that can be used for analysis and
decision-making. They are less time-sensitive
and are not concerned with immediate results.
The primary goal of this type of dashboard is to
assist users in making the best sense of data,
analyzing trends, and driving decision-making.
Expert 2 Context is one of the most critical elements
missing from dashboards. Your dashboard will
be less effective if it lacks context. Compare
your figures to your company’s goal. Listing the
plan on the chart is one of the most common
ways to provide context. This not only tells you
how you’re doing, but it also gives you a goal to
aim for.
Expert 3 My experience suggests that you should choose
no more than seven indicators to display on your
dashboard anymore, and your dashboard will
become visually cluttered, rendering it
ineffective at communicating information ‘at a
glance.’ You want to make sure that the
indicators you choose are specific, valid, and
reliable measures of the desired change(s) and
that they can be measured regularly.
Expert 4 The dashboard is clear, interactive, and user-
friendly. Efficient data visualization will enable
users to extract actionable insights and find
improvement opportunities.
Expert 5 The dashboard is good but generates more data
points and variable cross-analysis data.
A word cloud was utilized to present these comments and
suggestions, resulting in Figure 12.
Figure 12. Word Cloud for the Experts Comments &
Suggestions
When it comes to building a product that offers value and
displays actionable information, the audience comes first.
Creating a good dashboard necessitates regular adjustment and a
desire to improve the design and aesthetics over time. Thus, the
Dashboard will provide context and goal as the most numbered
responses generated by the word cloud.
4. CONCLUSION
The study’s objective is to determine the demographic
dashboard that can be used as a data source of business
intelligence to inform and give better decisions to guide the
business thoroughly and become more effective marketing.
Based on the results derived from this study, the following
conclusions were drawn.
 Results revealed that understanding consumer
preference would indicate consumer demand because
it dictates what consumers will buy within their
budget. This information will assist in ensuring to
have enough products to meet demand and determine
the product’s price. With a better understanding of
each customer’s purchase cycle, the futures market
may be predicted more precisely using historical data.
 Forecasting sales, orders, visits, and page views,
according to the findings, helps sellers achieve their
objectives by detecting early warning signs in their
sales pipeline and correcting course before it is too
late. Forecasting can help any company make more
informed decisions. It helps with long-term planning,
budgeting, and risk management. Forecasting allows
businesses to accurately estimate costs and revenue,
allowing them to predict short- and long-term
performance.
 Bringing all the design and activity elements together
into a cohesive whole during the design process will
complicated decision-making activities which have a
significant impact on the design solution, the business,
and the design process. The main design
features/functions helpful in improving the decision-
making process are (1) Data visualization and
analytics (Graphs, charts, indicators), (2)
Customization, (3) Historical view of data, (4) Data
filtering capabilities, and (5) Integration with the data
warehouse (external applications).

9.  Demographic dashboards present a consolidated view
of all data from across the organization, providing
valuable insights into Peachy Keen Decors’ entire
business. The user can look at and analyze data, see
the company’s key performance indicators (KPIs),
evaluate performance metrics, and generate actionable
insights. Thus, with a good BI dashboard, the user can
monitor and measure business performance and
metrics. BI dashboard tools truly provide users with
centralized, real-time access to data, allowing them to
interact with and evaluate data to make better data-
driven decisions.
5. RECOMMENDATION
With the conclusion stated above, this study provides a better
understanding of each customer’s buying cycle. Historical data
can help predict future demand more accurately by delivering
reporting and analysis for the entire organization or specific
functional areas. Visualized interactivity aids in communicating
large amounts of data simply and understandably. Better
business decisions can be made to identify what the information
means quickly. It focuses on the views of the expert respondents
and the analysis of data. The following recommendations are
proposed:
 Provide critical reporting and metrics information to
entrepreneurs to enlighten their minds on the
importance of dashboards in Business. Like the
dashboard in cars, Dashboards display essential
metrics and performance indicators in real-time,
assisting in making decisions and navigating the
environment. Furthermore, this research must apply
the knowledge to become more competent in real-life
business contexts and situations.
 Use the demographic Dashboard for Peachy Keen
Decors to analyze the given data and provide new
meaningful insights that can be used in the decision-
making process of their business.
 Communicate and suggest to Shopee to have a
forecasting system to easily track their store's
statistics. This would be helpful for them to easily
monitor, analyze, and find a solution for every
problem they might encounter.
 Utilize the results as a guide to the I.T. students to 1)
increase self-awareness, reflective, and self-regulation
learning dispositions, and 2) cultivate connective
literacy towards business intelligence using credible
data sources.
 Apply the fundamental framework set forth by this
study as a reference for future researchers on their
study with the same discipline.
6. ACKNOWLEDGEMENT
The researchers would like to extend their deepest gratitude and
sincerest MUCHAS GRACIAS to all who had given their
whole-hearted support and valuable assistance in the success of
this Shopee as a Data Source for Consumer Preferences in the
Context of Business Intelligence in Bulacan State University-
Bustos Campus.
To our parents who supported our financial needs in doing this,
for extending their any form of support during the time of doing
this. Thank you for always being there to guide us and back us
up physically, emotionally, mentally, socially, and financially.
We thank them for being an inspiration for us to finish this
study.
We thank our friends and peers for those who inspire our daily
lives.
The College of Information Technology Community including
the school department teachers and students, especially those
who completed this study.
To Dr. Bernie Malang, the College of Information Technology
and Engineering department head, for allowing and extending
his support to conduct this study.
Big thanks to our instructor and hardworking mentor, Dr.
Florinda Garcia-Vigonte, who has been our motivation in this
study; for his patience and kindness in providing comments,
reviews, directions, and encouragement for enriching the papers
and who equally shared his precious time for valuable
suggestion.
Lastly, we would like to thank the Lord for giving us the
wisdom and guidance that made the success of this study a
reality. May this study bring glory to God’s name.
7. REFERENCE
[1] Usability Evaluation Basics | Usability.gov. (2022).
Usability.gov. https://www.usability.gov/what-and-
why/usability-
evaluation.html#:~:text=Usability%20Evaluation%20focus
es%20on%20how,related%20to%20a%20new%20site
[2] ‌Azeroual, O., & Theel, H. (2018). The Effects of Using
Business Intelligence Systems on an Excellence
Management and Decision-Making Process by Start-Up
Companies: A Case Study. Retrieved from
https://arxiv.org/ftp/arxiv/papers/1901/1901.10555.pdf
[3] Benyoucef, M. & Huang, Z. (2012). From e-commerce to
social commerce: A close look at design features. Retrieved
from https://edisciplinas.usp.br/pluginfile.php/2342499
/mod_resource/content/1/from%20ecommerce%20to%20so
cial%20commerce%20-%20Huang.pdf
[4] Berger, M., Beijer, G. & Gelder, P.V. (2002). Statistical
Analysis Of Pageviews On Web Sites. Retrieved from
https://www.witpress.com/elibrary/wit-transactions-on-
information-and-communication-technologies/28/1301
[5] Conrad, A. (2019). BI vs. Big Data vs. Data Mining: A
Comparison of the Difference Between Them. Retrieved
from https://www.selecthub.com/business-intelligence/bi-
vs-big-data-vs-data-mining/

10. [6] Formlus (2020). Demographic Segmentation: Examples,
Advantages + [Variables]. Retrieved from
https://www.formpl.us/resources/marketsegmentation/demo
graphic/
[7] Handrijaningsih, L., Mariani, S., & Alam, P.C. (2019).
Improving Purchase Decisions of Shopee Online Stores in
Tangerang City. Retrieved from
http://ugefic.gunadarma.ac.id/file/Proceeding+UGEFIC%2
02019.pdf#page=79
[8] Munroe, M. (2021). Page Views vs. Visits: What's The
Difference? We Break It Down. Retrieved from
https://blog.hubspot.com/customers/marketing/understandin
g-the-difference-between-a-page-view-visit-and-session
[9] Rubin, C. (2017). Amazon Seller Reports: Sessions, Page
Views, & Everything Else You Need to Know. Retrieved
from https://www.skubana.com/blog/amazon-seller-reports