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What is Customer Master Data? Customer Master Data Management Best Practices

04/11/2024

1.56k

Linh Le

Every business collects customer data from website sign-ups and online purchases to social media interactions. But as this data grows, it often becomes scattered across different systems and departments. Sales, marketing, and support may each hold their own version of the same customer, making it difficult to see the complete picture.

Customer Master Data Management (MDM) solves this problem by creating a single, reliable source of truth for each customer. It brings all your information together, cleans and standardizes it, and makes it accessible across your organization.

This article explains what customer master data is, explores the main types of customer data, highlights the benefits and best practices of customer master data management, and shows how to integrate customer MDM with CRM and other systems. You’ll also learn how SupremeTech can help you build a unified data foundation for smarter business decisions.

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What is customer master data management?
Customer Master Data

What is Customer Master Data?

Customer master data is a centralized, comprehensive dataset about a company’s customers. It includes key details such as contact information, billing and shipping addresses, financial profiles, account identifiers, and interaction history. In short, it captures the key attributes that define your customers and how they engage with your business.

This data serves as a single source of truth (SSoT) across the entire organization. It ensures that every department (sales, marketing, finance, and customer service) accesses the same accurate, consistent, and up-to-date information. When correctly managed, customer master data eliminates duplicate records, prevents errors, and connects customer interactions across channels and systems.

Unlike transactional data, which records one-time activities such as purchases or service requests, customer master data remains stable and reusable. It’s the foundation that supports business operations, enhances customer experience, and fuels decision-making.

Effective customer master data management (MDM) helps businesses maintain this centralized accuracy by continuously cleaning, enriching, and synchronizing data across platforms. When managed correctly, it not only improves customer service and marketing performance but also strengthens compliance, analytics, and strategic planning.

what is customer master data?

Types of Customer Master Data

A strong customer master data management strategy starts with understanding the kinds of data you need to unify. Below are the key types that form a complete picture of each customer.

1. Basic identifying information

This includes a customer’s name, address, phone number, and email address, as well as unique identifiers such as a customer ID or account number. These elements are the foundation for matching and merging data across systems.

2. Demographic Data

Demographic details such as age, gender, income, education level, and location help you segment and understand your audience more deeply. They support marketing, personalization, and forecasting strategies.

3. Behavioral Data

Behavioral data captures customer interactions, such as browsing history, purchase frequency, purchase recency, app usage, and social media interactions. This type of data is valuable for predicting future behavior, personalizing offers, and improving the customer experience.

4. Transactional Data

Transactional data shows a customer’s purchase history, payment methods, order frequency, and lifetime value. It connects customer identity with their commercial relationship with your company. Transactional data is essential for analytics, financial reporting, and assessing customer lifetime value.

5. Engagement Data

Engagement data includes information about how customers interact with the brand across various touchpoints. It can be website visits, email opens, ad clicks, social media interactions, customer service inquiries, and loyalty program activity. This helps businesses understand customer engagement and loyalty.

6. Preferences and Interests

This type of data captures what customers prefer or are interested in. It can vary by favorite product categories, language preferences, notification settings, content interests, and communication frequency. It’s handy for personalization and customer experience management.

7. Account and Membership

For businesses with loyalty programs or membership systems, this includes information related to membership tiers, reward points, account status, and customer preferences within the loyalty program. These elements strengthen long-term relationships and are key to customer retention strategies.

8. Customer Feedback

This data includes customer reviews, feedback, survey responses, and sentiment analysis from social media or other platforms. It provides insights into customer satisfaction, product improvement needs, and brand perception.

9. Customer Service and Support Data

Support tickets, chat logs, complaint records, and resolution histories reveal how well you serve your customers. Integrating this data into your customer master record ensures that every interaction is informed and empathetic.Together, these data types create the foundation for a 360-degree customer view—a single, comprehensive record that drives consistent experiences across all touchpoints.

What Is Customer Master Data Management (Customer MDM)?

Customer Master Data Management (MDM) is the process of consolidating, cleaning, and managing all customer-related data to maintain one accurate version of the truth across your organization.

It involves people, processes, and technology working together to ensure that every department — from marketing to operations — uses consistent, reliable customer data.

In practical terms, customer MDM connects data from multiple systems such as CRM, ERP, marketing automation, and support platforms. It then cleanses, standardizes, and synchronizes this information into a single database known as the “master record.”

This master record is continuously updated and shared across systems, eliminating inconsistencies and ensuring that every customer-facing team sees the exact, accurate details.By implementing customer master data management best practices, organizations can reduce data duplication, improve analytics, and deliver highly personalized experiences that build trust and loyalty.

Customer MDM

Why Customer MDM Matters

Customer Master Data Management matters because it ensures that everyone in an organization, from sales to customer service, works with the same, accurate, and consistent customer information. When data is fragmented across systems, businesses struggle to understand their customers, deliver personalized experiences, or make informed decisions. By unifying and maintaining customer master data, companies can streamline operations, improve communication, and build stronger customer relationships.

Here’s why customer master data management is essential for retail businesses:

Improved customer experience

When every system shares the same correct information, customers receive consistent communication, faster service, and more relevant recommendations. For example, a support agent can instantly see a customer’s order history and resolve an issue without asking repetitive questions.

Better decision-making

Good data means good decisions. When your customer information is accurate and complete, managers can plan better marketing campaigns, predict customer needs, and set clear business goals. Reliable data reduces guesswork and supports smart strategies.

Increased operational efficiency

Without customer master data management, teams often spend time fixing data errors or searching for the right information. A single, clean data source removes this problem. Everyone works faster because they trust the data they see.

Stronger compliance and data security

Regulations such as GDPR and local data laws require companies to manage customer data carefully. With strong customer MDM in place, it’s easier to protect sensitive information and ensure all records comply with the correct rules and privacy standards.

Higher profitability

With a complete view of each customer, you can identify cross-sell and upsell opportunities, reduce churn, and target high-value segments more effectively. This often leads to higher sales and stronger long-term relationships.

Best Practices for Customer Master Data Management

Building an effective Customer Master Data Management (MDM) system is not just about technology. It’s about having clear rules, responsibilities, and processes that keep your customer information accurate and useful. Below are key best practices that help organizations create reliable data foundations and deliver better business outcomes.

1. Establish a Single Source of Truth

The first step in customer master data management is to ensure everyone in the company works from a single version of the truth. When customer data is scattered across different systems, errors and duplicates appear. A single, centralized master record ensures all departments—sales, marketing, finance, and support—see the same accurate information. This consistency builds trust, improves teamwork, and helps every team deliver a better customer experience.

2. Define Strong Data Governance and Ownership

Good data depends on good management. Data governance means defining who owns customer data, how it’s created, and when it’s updated. Assigning roles such as data stewards ensures accountability and consistency. With transparent governance, your company can maintain high-quality data over time instead of constantly fixing errors. It also makes compliance and reporting far easier.

3. Focus on Data Quality: Cleanse, Standardize, and Enrich

High-quality customer data is the foundation of every successful business decision. Unfortunately, many organizations struggle with duplicate records, missing fields, and inconsistent formats. Poor data quality not only wastes time but can also lead to failed campaigns, inaccurate reports, and frustrated customers.

To overcome this, companies must continuously cleanse and standardize their customer master data. Deduplication processes remove duplicate entries, while data validation tools ensure that addresses, email addresses, and contact details are correct. Standardization enforces consistent formats across all systems, making integration and analytics far easier.

You can also enrich data with additional information, such as demographics or preferences, to make it more valuable. High-quality data improves decisions, saves time, and helps your teams work confidently.

4. Integrate Customer Master Data Across All Systems

Customer information often lives in many systems, including CRM, ERP, marketing tools, or support platforms. Integrating these systems ensures updates in one place appear everywhere else. This not only prevents data silos but also gives your business a clear, unified view of every customer. Well-planned integration creates smoother operations, faster communication, and a consistent experience at every touchpoint.

5. Protect Customer Data and Ensure Privacy Compliance

With privacy laws like GDPR, CCPA, and others growing stricter worldwide, data protection must be a core principle of customer master data management best practices. Customer master data often includes sensitive information such as contact details, payment preferences, and transaction histories. Mishandling this data can damage your reputation and lead to serious penalties.

Strong security and privacy practices, such as encryption, access controls, and regular audits, help keep sensitive data safe. Compliance with data protection laws also builds customer trust and prevents costly penalties. When customers know their information is handled responsibly, they’re more likely to stay loyal to your brand.

6. Monitor, Audit, and Continuously Improve

Customer information changes constantly. People move, update their email addresses, or change their buying habits. That’s why customer MDM should be an ongoing process. Regular audits and data-quality reports help catch issues early. Collecting user feedback, reviewing governance policies, and adjusting integration flows all help keep your data clean and reliable. Continuous improvement ensures your customer data always supports your business goals.

Customer Master Data Management Best Practices

Integrating Customer MDM with CRM and Data Systems

Integrating Customer Master Data Management (MDM) with CRM and other data systems helps create a complete and accurate customer view. The goal is to make your master record the single trusted source that keeps all platforms (CRM, ERP, marketing, and support) aligned.

Start by identifying where customer data lives and how these systems connect. Clean and standardize records before integration to avoid spreading duplicate or incorrect information. Use APIs or data pipelines to automatically synchronize updates so that changes made in one system are reflected everywhere.

Regularly monitor data flow and fix sync issues early. As your business grows, review and adjust these integrations to include new tools or channels. When done right, integration eliminates silos, improves collaboration, and ensures that every department uses the same reliable customer data.

Challenges in Customer Master Data Management

Managing customer master data comes with several challenges. One major issue is inconsistent or incomplete data collected from different systems. When customer details vary between departments, it becomes challenging to create a single, accurate record.

Duplicate records are another common problem. The same customer might appear multiple times under slightly different names, which leads to confusion, wasted effort, and poor decision-making.

Data quality is also a continuous challenge. Outdated, missing, or incorrect information can damage trust and make analytics unreliable. Regular cleansing and validation are necessary to maintain accuracy.

Integration adds complexity. Customer data often exists across CRM, billing, and support platforms. Without proper synchronization, each system holds a different version of the truth.

Finally, organizational resistance and lack of data ownership can slow progress. Successful customer MDM requires collaboration, clear roles, and strong governance to ensure everyone values and maintains data quality.

How SupremeTech Can Help Your Businesses

At SupremeTech, we understand that managing customer data isn’t just about technology. It’s about creating business value through clarity, trust, and connection.

Our Custom Software Development service helps organizations design and implement customer master data management solutions tailored to their needs. Whether you want to build a centralized MDM system from scratch or integrate your customer master data into CRM, ERP, and analytics platforms, our experts can make it happen.

We combine deep technical expertise with practical business insight to ensure your MDM initiatives deliver measurable impact. From designing clean data architectures to automating validation and synchronization, SupremeTech helps you create a single source of truth for all your customer information.

Our developers work with modern tools and cloud technologies, ensuring your data flows securely and seamlessly across systems. With strong governance frameworks and performance optimization, we help you transform raw customer data into actionable insights that drive growth.

When your data is accurate, your decisions are smarter, your customer experience is stronger, and your operations are more efficient. That’s the power of mastering your customer data, and that’s where SupremeTech can help you lead.

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customer MDM process

Future Trends in Customer Master Data Management

Managing customer master data effectively is more critical than ever, and several trends are shaping how businesses approach it today. Here are the key current trends:

Moving to the Cloud

Cloud-based MDM (Master Data Management) solutions have taken off, and for good reason. With cloud, businesses can scale up (or down) as needed, access data from anywhere, and reduce costs. Plus, it’s easier to keep data up to date in real time, which is a game-changer for fast-paced retail environments.

Using AI to Clean and Understand Data

Artificial intelligence is helping clean up messy customer data by detecting duplicates, filling in blanks, and identifying patterns we might miss. Machine learning tools analyze behavioral trends and even predict what a customer might want next, making personalization much more intuitive.

Real-Time Data Updates

Today’s customers expect immediate responses, and for that, real-time data updates are essential. Integrating systems so that customer data refreshes instantly allows businesses to provide relevant offers or support as soon as it’s needed. In other words, no more outdated data holding back customer experience.

Customer Data Platforms (CDPs) for a Clearer View

CDPs pull customer data from multiple sources into one spot, creating a single, reliable profile for each customer. This unified view allows teams across sales, support, and marketing to deliver a consistent experience. As CDPs become more accessible, even smaller businesses can leverage this organized approach.

In short, companies are aiming to make data more accessible, accurate, and actionable, with a focus on real-time updates, privacy, and smarter, AI-powered insights. The result? Better customer experiences, more efficient operations, and a competitive edge.

>>> Read more: Understanding Key Differences Between Customer Data Platform vs Data Lake

Seeking ways to manage customer data effectively?

Knowing the importance of data sometimes does not mean knowing where to start. Even our clients who built an empire in retail struggle to manage data efficiently. The common pain point, as we translated it, is how to build a data pipeline that runs stably and responsively. Furthermore, trust and security are also the head-wrenching problem, especially when seeking external help.

We proudly offer the best of both. Schedule a meeting with us to know how we can proclaim with such confidence.

Conclusion

Customer Master Data Management is more than a technical exercise. It’s a strategic foundation for every modern business that values accurate insights and personalized customer experiences.

By understanding the different types of customer master data, following proven best practices, and integrating your systems effectively, your organization can build a single, reliable source of truth.

Clean, connected data doesn’t just reduce complexity—it unlocks opportunity. With the right partner, you can turn your customer master data into a competitive advantage that fuels lasting success.

FAQs

What Is Customer Master Data?

Customer master data is a centralized and consistent set of information about your customers, including their contact details, billing and shipping addresses, financial information, and interaction history. It acts as a single source of truth shared across departments and systems.

What Are Common Data Sources for Customer Data?

Common data sources include CRM systems, ERP platforms, e-commerce databases, customer support tools, marketing automation software, and billing systems. Integrating these systems helps create a complete and accurate customer profile.

What Are the Key Components of Customer MDM?

Key components include data integration, cleansing, deduplication, governance, and ongoing quality management. Together, they create a trusted, unified view of each customer across the organization.

How Can Businesses Get Started with Customer MDM?

Start by identifying where customer data exists, assessing its quality, and defining governance roles. Then, integrate data systems, apply cleansing processes, and maintain regular audits to keep data accurate over time.

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Backend Layer: Structured Logic and Data Flow Behind the interface, the team used Prisma ORM to manage the database layer. Its schema-first approach, paired with TypeScript integration, helped them maintain data consistency while iterating rapidly. The backend services were also written in Next.js, utilizing server functions to keep everything unified and easy to deploy. This setup gave the team clear control over their data models and allowed them to focus on the business logic, ensuring that trip creation, feedback collection, and participant interactions all flowed smoothly without manual handling. Infrastructure & Deployment: Stability under Pressure To keep their development-to-demo pipeline fast and reliable, Người Việc deployed their system on AWS using Dokploy - a self-hosted CI/CD solution that automates Docker-based deployments. This environment allowed them to push code, test changes, and release updates seamlessly without dependency conflicts. By using Docker containers, they replicated production conditions from the start, ensuring that the MVP remained stable and demo-ready throughout the hackathon. The setup was simple enough for rapid iteration yet robust enough to be scaled for real client use. AI Tools: A Smarter, Not Faster, Way to Build AI played a key role in the team’s workflow but only after the foundation was set.ChatGPT acted as their assistant for ideation and logic design, helping refine user stories, define acceptance criteria, and clarify user flows. Meanwhile, GitHub Copilot served as their pair programmer, generating clean snippets, suggesting improvements, and handling repetitive coding tasks. Instead of using AI as a shortcut, Người Việc used it as an accelerator by integrating it at the right moments to enhance productivity while keeping control of direction and logic. >>> Read more related articles: AI-Assisted Ecommerce Solution Wins Third Place at SupremeTech AI Hackathon 2025How Human Intelligence and AI Capabilities Can Redefine Software Development | Featuring The 1st Runner-Up of SupremeTech AI Hackathon 2025 Judges’ Feedbacks Business Perspective From a business perspective, the judges saw Team Người Việc as a perfect example of practicality and vision. Their solution showed how AI-driven development can address real client needs, especially in industries like travel and hospitality. However, the judges also provided constructive feedback for future improvement. While the idea covered a broad scope from sales to operations, they suggested narrowing the focus to one specific stage in the travel management cycle. By doing so, the solution could achieve higher feasibility and faster adoption in real-world scenarios. The judges also encouraged documenting the team’s AI-assisted project management workflow as a reference for future AI hackathon journeys within SupremeTech. The final presentation showcased all the best qualities of their teamwork. The judges highlighted Người Việc’s clear storytelling, strong time management, and smooth demo delivery that effectively illustrated how their system worked. The team’s confident, structured presentation left a lasting impression and perfectly captured the spirit of SupremeTech’s AI Hackathon. Technical and Engineering Perspective From a technical point of view, the judges recognized Người Việc as a team that combined strong engineering skill with thoughtful use of modern tools. They developed their product on a well-defined code base with clear development standards, following a structured flow from analysis and design to implementation, which is remarkable under the time pressure of a 24-hour hackathon. The highlight of their approach was the story-based prompting technique, which kept the project’s logic coherent from start to finish. By crafting prompts around user stories rather than isolated tasks, the team ensured that every AI-generated piece of code served a real business purpose. This balance between automation and human reasoning became one of the defining features of their success. Teamwork: Staying Calm When Things Went Wrong No hackathon story is complete without chaos and Người Việc had their moment too. Just before the final presentation, disaster happened: the team’s slide suddenly became inaccessible because their shared drive was locked by the judges. With only minutes left, they borrowed a laptop, rebuilt the slides from scratch, and walked onto the stage calm and composed delivering a confident demo that looked effortless to the audience. The team recalled “After 22 hours of coding, what stayed with us wasn’t exhaustion. It was that moment when everyone looked at each other and said: We'll make it work, no matter what.” Voices from the Winners For Team Người Việc, winning the hackathon was not just about the prize, it was about learning how humans and AI can truly collaborate. Reflecting on the experience, Dũng shared: “We realized that AI isn’t just a tool, it’s a real teammate, if you know how to ‘talk’ to it. Each team used AI differently: some for brainstorming, some for UI design, others for presentation. But the prompts we gave were never the same, and that’s why the results were so different. AI only shows its real power when people know how to guide it.” As winners, the team also offered advice for those who will join future hackathons: “Prepare everything you can beforehand: boilerplate code, deployment setup, tools, and your fighting spirit. Once the event starts, every minute counts. And above all, trust your team” Conclusion Team Người Việc proved that real innovation is not only about technology, but about people working together with purpose. By combining business insight, teamwork, and the smart use of AI, they turned a difficult 24-hour challenge into a real achievement. For SupremeTech, this victory is more than just a competition result. It’s a reminder that the future of development starts with clear thinking, strong teamwork, and the courage to explore new ways of building with AI. Appendix: 1. How the Team Applied AI Throughout the Project StageApproachAI Application/ Tools UsedAnalysis & DesignThe whole team brainstormed together, role-playing as real users to map out workflows and features.No AI used — this was the most human-driven stage focused on critical thinking.User Story writingConverted rough ideas into logical workflows, defined goals, and acceptance criteria.ChatGPT acted as a virtual BA, turning brainstorm notes into professional User Stories and Acceptance Criteria.Coding (User Story Based)Developers implemented each User Story while communicating directly with the AI assistant for suggestions and refactoring.GitHub Copilot served as a coding partner, reading stories, suggesting code, refining syntax, and accelerating implementation.Testing & ReleaseThe PTL and BA acted as real users to test the product, identify bugs, and refine the UX before release.No AI used — manual testing for real-user validation. 2. Team Tech Stack LayerTech StackFrontend & Backend (Fullstack)Next.js 15 (App Router)UI Libraryshadcn/ui + TailwindCSSAI AssistantChatGPT + GitHub CopilotInfra / DeployAWS + Dokploy 📩 Read more articles about us here: SupremeTech’s Blog

        22/10/2025

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        How Team Người Việc Won SupremeTech’s AI Hackathon 2025 with AI-Assisted Development and Agile Thinking

        22/10/2025

        209

        Quy Huynh

        nguoi lao wins third place AI hackathon ecommerce AI

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          AI-Assisted Ecommerce Solution Wins Third Place at SupremeTech AI Hackathon 2025

          SupremeTech’s first-ever AI Hackathon was more than just a competition. It was a thrilling test of creativity, focus, and endurance. For 22 hours, teams of passionate innovators raced against time to turn bold ideas into working prototypes that could bring real business value through AI. Among them was team Người Lào, whose project tackled one of the most relevant challenges in modern retail: building an omnichannel e-commerce and loyalty platform supported by AI. The goal was to create a system that connects online shopping, personalized loyalty programs, and in-store interactions into one seamless customer journey.What made Người Lào stand out was their business-driven mindset. Instead of treating the task as a purely technical challenge, they saw it as an opportunity to transform how Vietnamese cosmetic retailers connect with their customers. Their answer was ViEC Beauty, an innovative AI-powered e-commerce solution built on Zalo Mini App, turning a familiar local platform into a powerful tool for digital commerce. Meet The Team Team Người Lào was formed with the simple spirit of having fun, staying friendly, and learning together. Everyone joined with an open mind, ready to give their best once the challenge began. The team brought together members from different backgrounds, covering all key roles in a real project from infrastructure and front-end to back-end, business analysis, and quality control.Phuoc Pham, the team leader, believed great teamwork mattered more than perfect technical skills. What he looked for were people who knew their strengths and were willing to give their all. With that mindset, Người Lào grew into a team built on trust, respect, and laughter, values that ultimately became their greatest strength. When a Familiar Task Became the Toughest Challenge At first, the assignment sounded simple: create a multi-channel e-commerce and loyalty platform for retail stores. Building e-commerce systems was something most members already did in their daily work. But soon they realized that creating a typical shopping app would not stand out. To impress the judges, they needed something fresh, a solution with clear business impact and technical creativity. In just 22 hours, with five members and the support of AI tools, Người Lào had to deliver a product that was practical, scalable, and market-ready. Finding a Small Idea with Big Impact After a few brainstorming sessions, they decided to focus on a small but meaningful niche: the Vietnamese cosmetic retail market. This idea came from observing how many small cosmetic shops in Vietnam were struggling to keep up with the digital shift. While big players like Shopee and TikTok Shop dominate online sales, a large number of small cosmetic stores still lack proper digital tools to compete. These stores serve a loyal base of middle-aged customers who have strong purchasing power but are often left behind in the rush of digital transformation. They do not need complex apps or flashy platforms. What they need is something simple, familiar, and trustworthy. Người Lào identified three major problems these small retailers face: Losing connection with middle-aged customers who prefer personal interaction but no longer visit the store as often.Lack of customer insights makes it hard for shop owners to understand shopping habits or preferences.Being overshadowed by large e-commerce platforms, which are slowly taking over their loyal customer base. With those challenges in mind, Người Lào saw an opportunity to make a real difference. Instead of competing with big platforms, they wanted to empower small retailers with a digital tool that feels local, personal, and easy to use.That was when the idea of building an AI-powered e-commerce solution on Zalo Mini App, namely ViEC Beauty, was born. ViEC Beauty is a platform that could bring e-commerce and loyalty features right into the ecosystem that Vietnamese users already trust and use every day. It was a smart move that combined business empathy, technical creativity, and a clear understanding of the local market. From Idea to Prototype in 24 Hours Once the idea was clear, the real race began. With only 24 hours to bring ViEC Beauty to life, Người Lào jumped straight into action. The plan was simple: divide roles clearly, trust each other’s strengths, and move fast. Hieu Vo, the dev lead, took charge of integrations and overall coordination. Anh Duong focused on building the back end with Laravel and setting up the admin site. Hieu Cao worked on the front end of the Zalo Mini App. At the same time, Huong Nguyen took on both the Business Analyst and Quality Control roles to ensure everything aligned with the initial vision. Meanwhile, Phuoc Pham, the team leader, acted as the bridge connecting everyone - reviewing ideas, making key decisions, and preparing the final presentation slides. With all the key roles covered, the team had a 360-degree view of the project, from technical implementation to business logic and user experience. They spent the first ten hours coding with AI Copilot and documenting the workflow. It was intense but exciting until the team hit a wall. The AI started producing conflicting UI components due to unclear process design in the initial prompts. What was supposed to save time ended up creating bugs that needed hours to fix. But instead of getting frustrated, the team stayed calm, laughed it off, and worked together to debug and refine the product until everything clicked into place. When the final hour arrived, they had a fully working Zalo Mini App—not perfect, but functional, meaningful, and proudly built within a single sleepless day. The Product: Core Features That Matter ViEC Beauty, an AI-powered e-commerce solution built within the Zalo ecosystem, offered small beauty retailers an accessible and familiar way to sell online and engage customers. Core App Features Product Catalog: An easy-to-browse collection of beauty products directly inside Zalo.Basic Loyalty Point System: Customers earn and redeem points to encourage repeat purchases.Admin Dashboard Prototype: A simple dashboard for store owners to manage products, orders, and sales.Zalo Integration Setup: Allows stores to send personalized notifications, skincare reminders, and promotions through the Zalo Official Account. Super Admin System A more advanced panel included: Real-time data analytics for instant business insightsInventory management to track stock levelsCRM tools to maintain relationships and engagementCampaign and promotion management to run and measure marketing activities Even though some features like Group Orders and AI Skin Analysis were still in ideation, ViEC Beauty already demonstrated how a simple, focused solution could bring AI-powered value to small businesses. Tech Stack The team built ViEC Beauty with React and Zalo SDK for the front end, Laravel for the back end, MySQL for the database, and EC2 cloud infrastructure for hosting. They chose familiar and reliable technologies to move fast and deliver results within 24 hours, prioritizing execution over complexity. >>> Read more related articles: SupremeTech’s AI Hackathon 2025: A blend of Product-Focused Spirit and AI-assisted DevelopmentHow Human Intelligence and AI Capabilities Can Redefine Software Development | Featuring The 1st Runner-Up of SupremeTech AI Hackathon 2025 Judges’ Feedback The judges praised Người Lào’s strategic focus on a niche market and their decision to build on the Zalo Mini App, calling it a practical and high-potential approach. They noted that while the product targeted small beauty retailers, a limited market segment, it had strong potential for real-world implementation. They recommended expanding ViEC Beauty into a multi-store SaaS platform, adding community-driven features, and integrating AI more deeply for personalization and competitiveness. On the technical side, the judges commended the team’s clear planning, fast execution, and AI integration. They encouraged the team to make AI applications more visible and explore scalability for larger projects. Overall, Người Lào left a strong impression with a well-executed prototype and a clear vision for future growth. Teamwork Memorable Moments For Phuoc Pham, the leader, the biggest lesson was simple: strong determination makes anything possible. He learned to stay focused, manage effort wisely, and balance ambition with practicality so the team could deliver on time. To him, the real strength of Người Lào came from teamwork, from every member understanding their own strengths and supporting one another toward a shared goal. Huong Nguyen shared that the hackathon was an unforgettable experience, a test of creativity, patience, and collaboration. From ideation to final delivery, every member gave their best and learned how to manage time, communicate, and step outside their comfort zones. Winning third place was a proud moment, but for the team, the valid reward was the experience itself, learning, laughing, and building something meaningful together. Conclusion For Người Lào, the SupremeTech AI Hackathon 2025 was more than a contest. It was a journey of teamwork, creativity, and discovery. In just 24 hours, they turned an idea into a working Zalo Mini App that blended business insight, AI innovation, and human collaboration. Their story proved that success is not just about winning but about learning how to move fast, stay focused, and create with purpose. ViEC Beauty started as a hackathon project, but it carries the potential to grow into something much bigger for Vietnam’s beauty retail industry. Team Phuoc Pham T. - Senior Infra EngineerHieu Vo H. - Senior BE EngineerDuong Nguyen V. A. - BE EngineerHieu Cao K. - FE EngineerHuong Nguyen T.T. - Quality Control Engineer  Tech Stack Frontend: React, Zalo SDKBackend: LaravelDatabase: MySQLInfrastructure: EC2, Cloud 📩 Read more articles about us here: SupremeTech’s Blog

          21/10/2025

          202

          Ngan Phan

          AI

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          AI-Assisted Ecommerce Solution Wins Third Place at SupremeTech AI Hackathon 2025

          21/10/2025

          202

          Ngan Phan

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