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Functional Salon Website for Service Display and Online Booking
Management for Gold and Gorgeous Salon using Prescriptive
Analysis and K-Means Clustering
Calzada, Christian Kenneth
1
, Cudal, Romnick A.
2
, David, Ivan Christian C.
3
Arellano University, Pasig Campus
DOI: https://doi.org/10.51584/IJRIAS.2025.1010000064
Received: 18 October 2025; Accepted: 24 October 2025; Published: 06 November 2025
ABSTRACT
The system was designed to address issues related to manual booking processes, inconsistent service promotion,
and lack of customer data utilization. By incorporating Prescriptive Analysis, the system provides intelligent
recommendations for staff scheduling, promotional offers, and service optimization based on real-time customer
and business data. The K-Means Clustering algorithm categorizes customers into segments according to their
booking frequency, preferred services, and spending behavior. These insights enable the salon to implement
personalized marketing strategies and loyalty programs that strengthen customer engagement and satisfaction.
Gold and Gorgeous Salon, a local full-service salon located in Pasig City, faces challenges in digital promotion
and appointment handling. The lack of an organized online platform makes it difficult for customers to book
services and for the salon to consistently promote its offers. The business currently relies on walk-ins, referrals,
and manual social media replies, which are time-consuming and prone to missed inquiries. The system also
features a dynamic dashboard and automated report generation that visualizes key performance indicators such
as service demand, booking trends, and revenue distribution. The integration of analytics into the website helps
administrators make data-driven decisions, improving both operational management and customer service
quality. To ensure system effectiveness, a total of 150 participants composed of one owner, ten employees, one
hundred customers, twelve IT professionals, and twenty-seven IT students evaluated the system using the ISO
25010 quality model, focusing on five characteristics: functionality, reliability, usability, efficiency, and
maintainability. Results from the Likert-scale evaluation revealed high satisfaction levels across all dimensions,
confirming that the system met both user and technical expectations.
The findings demonstrate that combining prescriptive analytics and machine learning algorithms can
significantly improve service industry operations, particularly in appointment-based businesses. The developed
system not only digitizes booking and service management but also introduces intelligent insights for business
growth and strategic planning. It also provides a framework for integrating data analytics into small and medium
enterprises (SMEs), encouraging digital transformation in traditional service sectors. Overall, the project offers
a scalable and innovative approach that bridges technology and customer relationship management, positioning
Gold and Gorgeous Salon for improved competitiveness in the digital marketplace.
Keywords: Prescriptive Analysis, K-Means Clustering, Salon Website, Online Booking Management, ISO
25010, Data Analytics, Customer Segmentation, Web-Based System
INTRODUCTION
In the modern digital economy, small and medium enterprises increasingly depend on technology to manage
business operations and improve customer engagement. The salon and beauty service industry benefits from
adopting online platforms that facilitate bookings, service promotion, and customer interaction. Through data-
driven systems, businesses can optimize operations and make informed decisions that enhance overall service
quality. This study introduces the development of a Functional Salon Website for Service Display and Online
Booking Management that integrates Prescriptive Analysis and K-Means Clustering to support efficient
management and customer satisfaction.
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According to Chen et al. (2022), prescriptive analytics transforms data into actionable insights that help
businesses determine optimal decisions by evaluating possible outcomes. Kumar and Singh (2023) emphasized
that machine learning techniques such as K-Means Clustering are effective in segmenting customers based on
purchasing behavior, frequency, and preferences, which enhances targeted marketing strategies. In related
studies, Lopez and Rivera (2021) discussed the importance of automated booking systems in improving service
accessibility and customer convenience in local enterprises. These studies support the application of prescriptive
analytics and clustering models in improving business decision-making, which aligns with the goals of this
research to strengthen salon operations through intelligent data analysis.
Gold and Gorgeous Salon, a local full-service salon located in Pasig City, faces challenges in digital promotion
and appointment handling. The lack of an organized online platform makes it difficult for customers to book
services and for the salon to consistently promote its offers. The business currently relies on walk-ins, referrals,
and manual social media replies, which are time-consuming and prone to missed inquiries. Addressing these
challenges requires a functional and data-driven solution that simplifies operations and improves customer
interaction.
The aim of this study is to design and develop a functional salon website for Gold and Gorgeous Salon that
integrates Prescriptive Analysis and K-Means Clustering to enhance operational efficiency and customer service.
Specifically, it seeks to automate the booking process, generate data-based recommendations for staffing and
promotions, and segment customers for personalized marketing strategies. The system aims to empower
management through analytical dashboards and report generation for data-driven decision-making. This study
intends to establish a digital platform that connects technology and beauty service management to support the
salon’s growth and competitiveness in the digital market.
Scope
The scope of this study focuses on the design and development of a Functional Salon Website for Gold and
Gorgeous Salon that integrates service display, online booking management, and data analytics features. The
system enables customers to view available salon services, schedule appointments online, and receive automated
booking confirmations.
For administrative users, the system includes report generation and a dashboard module that present summarized
insights derived from Prescriptive Analysis and K-Means Clustering.
The report generation feature provides:
1. Booking Reports – summaries by day, week, month, and year; service frequency; peak hour analysis;
and appointment status tracking (pending, accepted, rejected, finished, canceled).
2. Customer Reports – segmentation results from K-Means Clustering, visit frequency and loyalty patterns,
demographic insights, preferred service combinations, and recommended promos based on spending
behavior.
3. Revenue and Promotion Reports – daily and monthly income summaries, service revenue breakdowns,
profit comparisons, and promotional suggestions based on data trends.
The dashboard displays interactive graphs, charts, and key performance indicators (KPIs) that help management
make informed decisions about promotions, staffing, and operational improvements. It consists of:
1. Booking Overview Dashboard – total appointments by period, booking sources, and real-time updates
on upcoming bookings.
2. Customer Insights Dashboard – visual representation of customer clusters, loyalty rates, and spending
behavior.
3. Revenue and Business Performance Dashboard – revenue and profit visualizations, performance
comparisons, and actionable insights from Prescriptive Analysis.
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LIMITATION
The study is limited to the development and evaluation of a web-based system specifically designed for Gold
and Gorgeous Salon in Pasig City. It focuses only on implementing Prescriptive Analysis and K-Means
Clustering for booking management, customer segmentation, and service optimization. The system does not
include additional business features such as online payment integration, inventory tracking, or employee payroll
management, which could further enhance business operations.
THEORETICAL FRAMEWORK
Figure 1: Theoretical Framework
The system is anchored on the theory of prescriptive analytics, which focuses on recommending data-driven
decisions to optimize business performance. Davenport and Harris (2017) explained that prescriptive analytics
provides organizations with actionable strategies derived from analyzed data, while Provost and Fawcett (2013)
emphasized its role in guiding operational and managerial decision-making. Raghupathi and Raghupathi (2014)
highlighted that applying data analytics in business operations leads to improved efficiency and strategic
planning. Liao et al. (2015) found that analytics-driven decision systems enhance customer satisfaction by
enabling personalized services. These studies support the integration of prescriptive analytics in the salon system
to improve appointment management, resource allocation, and service promotions.
The study also applies the K-Means Clustering algorithm to group customers based on booking behavior,
preferences, and spending patterns for better service personalization. Jain (2010) noted that clustering enables
businesses to identify customer segments effectively, and Han, Kamber, and Pei (2012) explained that it
simplifies large datasets for deeper business insights. Xu and Wunsch (2005) supported that K-Means Clustering
is efficient for customer analysis and behavioral prediction, and Chiu et al. (2017) demonstrated that
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segmentation improves customer retention and targeted marketing. These references form the basis for using
clustering in the system to generate insights that strengthen customer relationships and enhance salon
management decisions.
CONCEPTUAL FRAMEWORK
Figure 2: Conceptual Framework
The conceptual framework of this study illustrates the integration of Prescriptive Analysis and K-Means
Clustering within the Functional Salon Website to improve service management and customer engagement. The
system begins with the input phase, where customer booking data, service preferences, and staff availability are
collected through the online platform. These data serve as the foundation for analysis and allow the system to
generate meaningful insights for managerial decisions. Through prescriptive analytics, the system processes
historical and current data to recommend optimal staffing schedules, marketing promotions, and operational
improvements. This analytical process enables Gold and Gorgeous Salon to make data-driven decisions that
enhance efficiency and customer satisfaction.
In the processing and output phase, the K-Means Clustering algorithm groups customers into segments based on
their booking frequency, preferred services, and spending behavior. These clusters are used for personalized
marketing strategies and loyalty programs. The results are displayed through a dynamic dashboard and
automated reports that visualize patterns, trends, and system recommendations. Administrators can use these
outputs to monitor business performance, track service demand, and identify areas that require operational
adjustments.
The system also includes a feedback feature that supports continuous improvement and ensures customer
satisfaction. After each completed service or appointment, customers are encouraged to provide feedback
through the website regarding their experience, service quality, and staff performance. This feedback serves as
additional input to refine system recommendations and improve salon services.
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Significance of the Study
For the Salon Owner and Management
Provides a data-driven tool for managing bookings, staffing, and promotional decisions efficiently.
Reduces manual workload by automating appointment handling and generating insightful reports.
Enhances decision-making through prescriptive analytics that suggest optimal operational strategies.
For the Employees and Staff
Improves work scheduling through automated and balanced staffing recommendations.
Allows better coordination of services by viewing real-time booking updates and customer preferences.
Reduces scheduling conflicts and ensures fair distribution of work hours based on predicted demand.
For the Customers
Offers a convenient and accessible online booking platform available at any time.
Provides personalized promotions and service recommendations based on customer preferences and visit
history.
Minimizes waiting time and enhances the overall salon experience through organized appointment
management.
For Future Researchers
Serves as a reference for integrating Prescriptive Analysis and K-Means Clustering in small business
systems.
Provides a foundation for future studies focused on data-driven service optimization.
Encourages the exploration of advanced analytics to improve customer service and operational
efficiency in the beauty and wellness industry.
REVIEW OF RELATED LITERATURE
Chen et al. (2022) explained that prescriptive analytics helps businesses make better decisions by generating
data-based recommendations for operations and planning. Their study showed that analytics-driven systems
improve efficiency through automated resource management.
Lopez and Rivera (2021) developed an online appointment system for local service businesses and found that
automation minimizes scheduling errors and missed bookings. They concluded that web-based booking
platforms enhance accessibility and service efficiency, especially for small businesses in the Philippines.
Synthesis
Both foreign and local studies agree that integrating technology into business operations improves service
delivery and customer satisfaction. Chen et al. (2022) highlighted the importance of analytics for decision
support, while Lopez and Rivera (2021) emphasized the effectiveness of online booking systems in improving
service processes.
These findings support the current study, which combines a functional salon website with Prescriptive Analysis
and K-Means Clustering. The reviewed literature shows that automated booking and data-driven insights are
effective tools for improving business operations, which aligns with the objectives of this system developed for
Gold and Gorgeous Salon.
METHODOLOGY OF THE STUDY
This study employs an Applied Research design because it focuses on creating a practical technological solution
to address real-world business challenges. It develops a functional salon website that uses Prescriptive Analysis
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and K-Means Clustering to improve service management, booking efficiency, and customer engagement. The
research applies theoretical data analytics concepts to an actual salon setting and transforms them into a
functional system that enhances operational decision-making.
Software Development Methodology
The study adopts the Agile Software Development Methodology, which emphasizes flexibility, collaboration,
and iterative progress in system creation. Agile is suitable for this project because it allows continuous testing,
feedback integration, and refinement throughout the development of the Functional Salon Website for Service
Display and Online Booking Management. This approach ensures that both functional and analytical
components, such as Prescriptive Analysis and K-Means Clustering, are properly evaluated and improved based
on user feedback and performance testing. The iterative nature of Agile promotes adaptive planning and enables
the development team to address changes in salon requirements and user needs effectively.
Figure 3: Agile Software Development Methodology
Planning Stage
This phase involves defining the system requirements, identifying user needs, and setting the objectives of the
salon website. The researchers gather data from the salon management to determine key functions such as service
display, booking, reporting, and analytics integration.
Design Stage
In this stage, the system architecture, interface layout, and database structure are designed. The design includes
modules for customer booking, administrative dashboards, report generation, and analytics algorithms.
Wireframes and mockups are also created to visualize system flow and user interaction.
Development Stage
The actual coding and integration of system modules take place in this stage. Developers build the front-end user
interface and the back-end components that include the database and analytics engine. The Prescriptive Analysis
and K-Means Clustering features are implemented to handle data processing and generate intelligent insights.
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Testing Stage
The system undergoes multiple testing cycles to ensure functionality, accuracy, and usability. Each sprint
delivers a working feature that is reviewed and refined based on feedback from salon users and system
evaluators. This stage ensures that booking, analytics, and reporting modules perform as expected.
Deployment and Maintenance Stage
After successful testing, the system is deployed for actual use by Gold and Gorgeous Salon. The development
team monitors performance, gathers user feedback, and makes updates or improvements as needed. Continuous
maintenance ensures system stability, data accuracy, and user satisfaction.
Survey Instruments
Before creating the system, structured questionnaires are used to collect data from salon staff and customers to
understand their needs, preferences, and challenges in booking and managing appointments. The survey focuses
on identifying common issues such as scheduling conflicts, slow response times, and lack of digital accessibility.
The gathered information serves as the foundation for designing system features that address user requirements
and improve overall salon management.
After the system implementation, a survey questionnaire based on the ISO 25010 quality model is used to
evaluate five key characteristics: functionality, reliability, usability, efficiency, and maintainability. Respondents
rate each characteristic using a 5-point Likert scale ranging from 1 (Strongly Disagree) to 5 (Strongly Agree),
providing quantitative data on the system performance and user satisfaction.
Respondents of the Study
A total of 150 participants were involved in evaluating the system using the ISO 25010 Software Quality Model,
which includes the characteristics of Functionality, Reliability, Usability, Efficiency, and Maintainability. The
evaluators were composed of 1 salon owner, 10 employees or staff, 100 customers, 12 IT professionals, and 27
IT students. Each participant assessed the system using a 5-point Likert scale questionnaire ranging from 1 –
Strongly Disagree to 5 – Strongly Agree. Their evaluation provided insights into how well the salon website met
quality standards in terms of technical performance and user satisfaction.
Development and Evaluation Procedure
The Gold and Gorgeous Salon Web System was developed using a structured web development process to ensure
functionality, usability, and maintainability. The frontend was created using HTML for structure, CSS for design,
and JavaScript for interactivity to provide a responsive user interface. PHP was used for server-side scripting,
while MySQL handled the database operations for storing customer, booking, and service records. Development
and testing were conducted locally using the XAMPP server.
The system also includes analytical features through the integration of the K-Means clustering algorithm, which
helps analyze customer booking patterns for personalized service recommendations. Additional features such as
social media links, contact forms, and Google Maps integration were added to enhance user accessibility and
engagement.
The system was evaluated based on the ISO 25010 software quality model, specifically focusing on
Functionality, Reliability, Usability, Efficiency, and Maintainability. Evaluation was conducted through user
testing and expert validation to ensure performance accuracy and system quality before deployment.
Data Analysis Plan
The study used descriptive statistics to analyze the evaluation results of the Gold and Gorgeous Salon website.
Frequency and percentage distribution were used to summarize the demographic profile of the respondents. The
weighted mean was applied to determine the overall assessment of the system based on the ISO 25010 software
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quality characteristics using a 5-point Likert scale. The results were interpreted to identify the level of
functionality, reliability, usability, efficiency, and maintainability of the system.
The System
Development tools such as PHP, MySQL, HTML, CSS, and JavaScript were used in creating the Gold and
Gorgeous Salon website. The front-end provides a user-friendly interface for customers and an admin dashboard
for salon employees, while the back-end manages reservations, inquiries, and content updates. The system was
developed iteratively to allow continuous improvement based on user feedback. Key features include an online
booking system, customer reviews, and gallery updates, all of which function efficiently across different devices.
Figure 4: Booking Analytics
The Booking Analytics section provides detailed insights about salon appointments. It shows daily, weekly,
monthly, and yearly booking summaries so the admin can track booking volume over time. It also analyzes
which types of services are booked most often and identifies peak hours when bookings are highest. In addition,
it monitors appointment statuses such as pending, accepted, rejected, finished, or canceled, making it easier for
the admin to manage scheduling performance and customer activity.
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Figure 5: Customer Segmentation and Prescriptive Insights
The Customer Segmentation and Prescriptive Dashboard presents results from the K-Means Clustering model,
which groups customers based on total spending, visit frequency, and average spend per visit. It classifies
customers into three clusters: VIP/High-Value, Regular, and Occasional Visitors.
Each cluster’s performance is visualized through customer segment and spending charts, validating the accuracy
of the model. The system also provides recommended promos based on customer tier and spending behavior,
such as exclusive rewards for VIPs and loyalty perks for regular customers. This helps the admin identify high-
value clients and apply personalized marketing strategies effectively.
Figure 6: Revenue and Promotion Performance Overview
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The Revenue and Promotion Performance Overview section focuses on the salon’s overall income and
promotional performance. It provides daily and monthly income summaries to help track financial growth. It
also breaks down revenue by service type to show which services generate the most profit. Based on trends in
the data, the system suggests promotional offers that could increase customer engagement and boost sales.
Assessment: Summary of Respondents on The System
The distribution of respondents along with their size (n) and percentage are shown in the following tables.
Additionally, a combined summary of the participants' evaluations is presented. The ISO 25010 Software Quality
Model was used to assess the system based on Functionality, Reliability, Efficiency, Usability, and Security.
Feedback from both user respondents and technical specialists was gathered to determine the overall
effectiveness and user satisfaction of the developed system.
Table 1: Distribution of Respondents
A total of 150 participants evaluated the system. Out of these, 111 were system users (owner, employees,
customers) and 39 were technical evaluators (IT professionals and students). This ensured a balanced assessment
in terms of usability and technical quality.
Table 2: Summary and Comparison of Evaluations of Respondents
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Figure 7: Comparative Weighted Mean Ratings between User and Technical Evaluators
The results in Table 2 and Figure 7 show that user respondents strongly agreed with the overall quality of the
system (Overall Mean = 3.42), while technical evaluators agreed (Overall Mean = 3.16). Both groups confirmed
that the system is functional, reliable, and user-friendly.
The comparative graph highlights that user ratings were consistently higher across all ISO 25010 criteria,
particularly in Usability (3.52 vs 3.12) and Efficiency (3.38 vs 3.10). This indicates that users found the system
easier and more convenient to use, while technical evaluators identified areas for optimization, particularly in
Security and Performance.
Overall, the assessment results affirm that the system meets the expected software quality standards,
demonstrating positive feedback from both user and technical perspectives.
Ethical Considerations
The study follows ethical research guidelines to ensure the protection, rights, and privacy of all participants. The
confidentiality and integrity of all gathered data are strictly maintained, and no personally identifiable
information is disclosed without consent. Participation in the study is voluntary, and respondents may withdraw
at any time without any penalty. Proper data security measures are applied to prevent unauthorized access, loss,
or misuse of information. The researchers also commit to presenting results honestly and accurately, avoiding
any form of bias or data manipulation to maintain the credibility and reliability of the study.
Summary
The study focused on developing a Functional Salon Website for Service Display and Online Booking
Management for Gold and Gorgeous Salon using Prescriptive Analysis and K-Means Clustering. The system
aimed to address common salon challenges such as unorganized bookings, missed inquiries, and inefficient
promotion handling. Through the integration of Prescriptive Analysis, the system generated data-driven
recommendations for staff scheduling, service optimization, and promotional strategies. The K-Means
Clustering algorithm grouped customers based on booking patterns, preferences, and spending behavior,
allowing personalized service offerings.
A total of 150 participants, including the salon owner, employees, customers, IT professionals, and IT students,
evaluated the system using the ISO 25010 software quality characteristics. The results showed high ratings in
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functionality, reliability, usability, efficiency, and maintainability. The findings revealed that the system
improved customer engagement and streamlined business operations. Overall, the research demonstrated that
applying data analytics in small-scale service industries can support smarter management and enhance customer
satisfaction.
CONCLUSION
Based on the results, the developed salon website successfully met its objectives of enhancing booking
management, service visibility, and customer interaction. The use of Prescriptive Analysis provided actionable
insights that improved decision-making in resource allocation and promotional strategies. The K-Means
Clustering feature helped the salon understand customer segments and deliver personalized experiences.
Evaluation using the ISO 25010 model confirmed that the system performed well in terms of functionality,
reliability, usability, efficiency, and maintainability. Users found the platform easy to navigate, responsive, and
beneficial for both administrative and customer use.
The analytics-driven approach gave Gold and Gorgeous Salon a competitive advantage in digital service
management. It showed how data-driven technologies can transform traditional businesses into efficient and
customer-focused enterprises. Therefore, the developed system serves as a practical and innovative solution for
improving operational efficiency in the salon industry.
RECOMMENDATION
It is recommended that the salon continue using and enhancing the system to automate appointment scheduling,
customer tracking, and promotional campaign management. Additional features such as online payment
integration, SMS or email notifications, and real-time chat support may be added to improve convenience and
user engagement. Future developers may also expand the analytics module by incorporating predictive modeling
for revenue forecasting and customer retention analysis.
Continuous collection of user feedback is advised to ensure that the system adapts to changing customer needs.
Regular staff training must also be provided to improve system usage and data interpretation for better decision-
making. For academic purposes, future researchers may explore combining K-Means Clustering with other
algorithms such as Decision Trees or Neural Networks for more accurate recommendations. The system may
also be tested and applied to other service industries such as spas, wellness centers, or barbershops to assess its
adaptability. Maintaining system updates and integrating advanced analytics will support long-term system
efficiency and effectiveness.
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