Building the systems behind better marketing decisions

I’m Anthony Tsui, a Hong Kong–based practitioner working at the intersection of marketing technology, analytics and AI.

For more than a decade, I have worked across public-health research, digital marketing, enterprise conversational AI and marketing analytics. The common thread throughout my career has been helping teams turn complex data, technology and models into practical systems that support better business decisions.

My career began in public-health research, where I used statistical analysis to investigate real-world questions and co-authored research on the health impacts of air pollution.

That experience shaped how I think about analytics: a model, dashboard or dataset is not valuable simply because it is technically sophisticated. It becomes valuable when it is built on reliable evidence, answers a meaningful question and helps someone make a better decision.

I later moved into digital marketing, applying customer segmentation and performance analysis to improve campaign outcomes. This was where I became increasingly interested in the link between data, technology and commercial impact.

At Standard Chartered, I worked on enterprise conversational AI and digital analytics in a regulated banking environment. My work covered chatbot delivery and optimisation, NLP improvement, model-training processes, vendor coordination, production releases and digital measurement.

It gave me a practical view of AI implementation. A capable model alone does not create value. For AI to work in a real organisation, it needs a clear use case, reliable data and processes, appropriate governance, human oversight, and a thoughtful way to handle the cases it cannot solve.

This experience continues to shape my perspective today: AI should support people in doing better work—not remove the judgement, responsibility and context that good decisions require.

More recently, at EssenceMediacom and WPP Media, I led analytics, measurement, MarTech and data-platform initiatives across local, regional and offshore teams.

My work has included marketing mix modelling, predictive analytics, global BI architecture, automated data pipelines, GA4 and server-side measurement, ad-tech governance, dashboards, and GenAI-enabled analytics solutions.

I enjoy working where commercial questions meet technical delivery: defining the problem, translating it into an achievable solution, aligning stakeholders, guiding implementation and ensuring that the final output is genuinely useful to the people who rely on it.

Whether the work involves measurement architecture, a BI environment, a marketing-mix model or an AI-enabled product, my focus is the same: create solutions that teams can understand, trust and use.

Since May 2026, I took a planned career break to care for my newborn son.

Alongside parenting, I am deepening my knowledge of LLM applications through structured study and hands-on experiments in marketing technology and marketing analytics.

I use these projects to explore how LLMs can reshape MarTech and marketing analytics—from how teams work with data and manage marketing systems to how they generate insights and make decisions. My aim is to identify where AI can create practical value while keeping human judgement, context and accountability at the centre.

I am especially interested in how AI may support areas such as research, data preparation, tracking and measurement quality assurance, knowledge work, insight generation and analytical workflows. But I am equally interested in the limitations: where outputs require validation, where context matters most, and where a simpler non-AI solution may be more reliable.

My approach is also informed by two master’s degrees spanning public health and information technology. I hold a Master of Science in Information Technology, with a focus on Natural Language Processing, from The Hong Kong Polytechnic University (completed in 2026), and a Master of Public Health from The Chinese University of Hong Kong.

Together, they have shaped how I approach technology and analytics: with technical curiosity, statistical rigour, real-world evaluation and a focus on meaningful outcomes.

I believe strong marketing outcomes depend on strong foundations:

• Clear business and measurement objectives
• Reliable, well-governed data
• Technology that fits real operating workflows
• Analytics that leads to action—not just reporting
• AI that augments expertise rather than replacing it

The most important question is not:

How can we use AI?

It is:

What is the simplest, most reliable way to help people make a better decision?

This site is where I share my work, experiments and perspectives on marketing technology, analytics, measurement and applied AI.

If you work in these areas—or simply want to exchange ideas—feel free to explore my writing, connect with me on LinkedIn, or get in touch.