– Explore how organisations are leveraging AI to decode customer behaviour, and the key challenges in transforming raw data into strategic, actionable insights.
– Gain insights into balancing hyper-personalised marketing efforts with data privacy and trust, as businesses navigate the fine line between relevance and intrusion.
– Discover the emerging AI and analytics technologies poised to redefine customer segmentation and engagement strategies in the next few years.
– Understand the importance of cross-functional collaboration—between data scientists, marketers, and privacy teams—to develop AI strategies that are both innovative and ethically responsible.

– Explore how organisations are unifying data across platforms to create a single customer view—while balancing the growing demands of personalisation and data privacy.
– Unpack the tools, technologies, and strategies that act as a “refinery” for raw data, transforming it into meaningful business value.
– Discover how to design data architectures that are scalable, flexible, and ready for the future as AI and real-time analytics become the norm.
– Challenge common data misconceptions and debunk persistent myths that hinder progress in building unified, intelligent customer data ecosystems.

– Understand why high-quality data is foundational to accurate forecasting, better decision-making, and delivering exceptional customer experiences.
– Identify common data quality challenges—from duplication to inconsistency—and their impact on business performance and customer trust.
– Learn how organisations can foster a culture of data ownership, where data quality becomes a shared responsibility across all functions, not just IT.

– Discover how leading organisations are using data to strengthen customer retention, foster loyalty, and build long-term value in competitive markets.
– Learn how to transform real-time data insights into actionable strategies that accelerate customer acquisition and revenue growth.
– Explore the common disconnects between data strategy and business goals—and how to bridge them to enable sustainable, data-driven growth.

– Examine how organisations are implementing personalisation at scale by using data-driven strategies to create seamless, intuitive customer journeys.
– Explore the role of machine learning and journey analytics in anticipating customer needs and enhancing experience delivery in real time.
– Identify the critical data signals that fuel effective personalisation—and how to ensure they are accurate, timely, and relevant.
– Discuss how businesses can strike the right balance between automation and human interaction to preserve authenticity and customer trust.

– Define omnichannel as a strategy that connects all customer touchpoints into one seamless experience, emphasizing consistency across online and offline channels.
– Explain how businesses can bridge physical and digital channels using tools like unified CRMs, identity resolution, IoT, and APIs to ensure data continuity.
– Highlight the key data types—transactional, behavioral, demographic, and sentiment—and show how they can be used to personalize experiences and guide decisions.
– Provide a simple roadmap: audit current systems, set goals, choose the right tech, ensure data compliance, train teams, and pilot before scaling.

– Understand why transitioning from intuition-based decisions to data-driven strategies is essential in today’s competitive and fast-changing business environment.
– Explore how leadership can drive cultural change by championing data literacy, setting expectations, and leading by example.
– Learn how to overcome common barriers to embedding data into daily decision-making, from organisational silos to resistance to change.

– Explore why maintaining clean, accurate, and secure data is essential in today’s digital landscape—and how it directly impacts customer trust and operational performance.
– Learn how a strong data foundation supports consistent hygiene practices across the entire data lifecycle, from collection to usage and storage.
– Discover how data governance practices can be extended to AI systems—ensuring models are trusted, explainable, and compliant with evolving regulations.
– Uncover how AI and intelligent agents can support data stewardship, automate hygiene processes, and improve overall data quality at scale.

– Stay updated on the latest developments in Thailand’s PDPA for 2024–2025 and understand how regulatory changes are impacting business operations.
– Explore practical approaches for maintaining ongoing compliance and protecting customer data in an evolving digital landscape.
– Learn how to effectively respond to data breaches and audits, and build resilience into your data protection strategies.
– Discover how Thai organisations can align PDPA compliance with global data privacy standards such as the GDPR, particularly in the context of cross-border data flows.