
Summit agenda is subject to change.
– How do you identify the customers and moments that matter most for retention, and where should brands focus their investment?
– What signals tell you a customer is at risk of churn, and how do you turn those insights into timely, relevant interventions?
– How do you prove the commercial value of retention and get the wider business to prioritise it alongside acquisition and growth?
– Why leading brands are moving beyond all-in-one platforms and adopting flexible, best-of-breed architectures to increase agility, reduce complexity and accelerate time-to-market.
– How connecting specialised solutions across customer data, engagement, commerce, personalisation and communications can create a more powerful and adaptable marketing ecosystem.
– How an open, interoperable technology stack can help organisations maximise existing investments, improve speed of execution and demonstrate stronger ROI from MarTech.
– If you were advising a marketing leader today, where would you tell them to orchestrate these touchpoints to turn discovery into meaningful customer acquisition?
– What does effective personalisation look like in your organisation, and how are you using data and technology to make it happen in real time? How do we make omnichannel personalisation truly useful, rather than simply more targeted?
– What do you believe drives genuine loyalty today? Beyond points, promotions and discounts, what keeps customers coming back?
– What agentic AI means for marketers and how AI is changing the way customers discover, evaluate and engage with brands.
– How AI agents are becoming the middle layer in customer engagement and why real-time customer context matters for staying relevant.
– Where marketers should start, what to prioritise and how to move from AI ambition to confident action over the next 12–24 months.
– Traditional personalisation often focuses on “the right message, at the right time”. How can brands move beyond transactional interactions and design experiences that create genuine emotional connection and loyalty?
– With more customer data available than ever, how can organisations identify the signals that truly matter and use them to create more relevant experiences?
– AI is transforming how brands understand and engage customers. How can organisations use AI to enhance human experiences rather than make interactions feel automated?
– How can marketing leaders determine whether AI investments are creating meaningful business value rather than simply increasing experimentation?
– What are the biggest barriers preventing teams from adopting AI consistently, and how can leaders overcome them?
– What practical approaches can organizations use to embed AI into everyday marketing workflows and drive sustainable integration across teams?
– Explore how AI is reshaping customer experience and redefining how brands engage, personalize and deliver value in real time.
– The shift to AI-driven, conversational journeys and what it means for how customers discover, research and engage.
– Rising expectations for real-time, highly relevant and authentic experiences across every touchpoint.
– Closing the gap between AI ambition and execution, turning AI-powered experiences into measurable business impact.
– Can you share a moment when a specific piece of data, not a report, a specific signal that led to a real decision, and what happened after?
– How are you piecing the customer journey together with data, and where do most marketing teams still get it wrong?
– Understand how to align marketing metrics with commercial outcomes that leadership cares about
A relaxed networking buffet, giving attendees time to connect and recharge between sessions.
– Why large volumes of customer data do not automatically translate into AI readiness, and where organisations typically get the foundation wrong.
– How to establish trusted data through quality, governance, consistent definitions and scalable architecture before deploying AI at scale.
– How data leaders can connect AI investment to measurable business outcomes rather than treating data and AI transformation as purely technical initiatives.
– How do you keep one brand identity while adapting to different markets, audiences, and channels?
– How do you give teams creative freedom while keeping content consistent and approvals fast?
– How do you connect content online & offline experience to drive bookings, enquiries, or sales?
– Customer Intelligence powers the middle, connecting data, AI and decisions with teams and touchpoints that
make up the marketing ecosystem. It turns fragmentation into flow and complexity into confidence.
– When the middle works, marketing works.
– What makes someone move from “I like this” to “I’ll buy this”? Where does creator influence actually sit in your customer’s decision?
– Your loudest audience and your paying audience usually aren’t the same people. How do you find the overlap?
– What did you stop doing this year, something that used to work?
– Thai consumers move between LINE, WhatsApp, Viber and Zalo throughout their daily journeys, yet many marketing stacks still manage each channel as a separate integration, vendor and reporting system.
– Discover how one omnichannel API can transform fragmented messaging channels into a single, connected and trackable customer conversation.
– See how LINE Official Account, LINE Official Notification and SMS work together to help Thai brands deliver trusted two-way engagement, while extending seamlessly across WhatsApp, Viber and Zalo without rebuilding the technology stack.
– Built for Thailand, designed to help brands scale customer engagement anywhere.
– Legal Landscape: Key obligations businesses face when handling children’s data, and when parental consent or other safeguards are required.
– Good Practice in Action: Real-world examples of age verification, parental consent, and privacy-by-design in practice.
– Enforcement Trends: Lessons from recent enforcement actions and common compliance pitfalls to avoid.
– When driving digital transformation, how do you decide what needs to change first across people, processes and technology, and what should remain unchanged?
– Where does AI fit into your broader digital transformation roadmap, and how do you integrate it into existing systems and processes rather than treating it as a standalone initiative?
– How do you move transformation from strategy to measurable business and customer impact while bringing different teams and stakeholders along the journey?
– What counts as a high-value lead in your world and how differently do B2B logistics and B2C property define it?
– Where do your best leads from? What’s one channel that looked good on paper but didn’t deliver?
– What moves a lead from MQL to closed? Which AI or automation tools are helping you today?
– What are the biggest challenges and opportunities you see in lead generation right now?
– How can marketing leaders determine whether AI investments are creating meaningful business value rather than simply increasing experimentation?
– What are the biggest barriers preventing teams from adopting AI consistently, and how can leaders overcome them?
– What practical approaches can organizations use to embed AI into everyday marketing workflows and drive sustainable integration across teams?
– How can marketing leaders determine whether AI investments are creating meaningful business value rather than simply increasing experimentation?
– What are the biggest barriers preventing teams from adopting AI consistently, and how can leaders overcome them?
– What practical approaches can organizations use to embed AI into everyday marketing workflows and drive sustainable integration across teams?
– Why large volumes of customer data do not automatically translate into AI readiness, and where organisations typically get the foundation wrong.
– How to establish trusted data through quality, governance, consistent definitions and scalable architecture before deploying AI at scale.
– How data leaders can connect AI investment to measurable business outcomes rather than treating data and AI transformation as purely technical initiatives.
– Why large volumes of customer data do not automatically translate into AI readiness, and where organisations typically get the foundation wrong.
– How to establish trusted data through quality, governance, consistent definitions and scalable architecture before deploying AI at scale.
– How data leaders can connect AI investment to measurable business outcomes rather than treating data and AI transformation as purely technical initiatives.
– Legal Landscape: Key obligations businesses face when handling children’s data, and when parental consent or other safeguards are required.
– Good Practice in Action: Real-world examples of age verification, parental consent, and privacy-by-design in practice.
– Enforcement Trends: Lessons from recent enforcement actions and common compliance pitfalls to avoid.
– Legal Landscape: Key obligations businesses face when handling children’s data, and when parental consent or other safeguards are required.
– Good Practice in Action: Real-world examples of age verification, parental consent, and privacy-by-design in practice.
– Enforcement Trends: Lessons from recent enforcement actions and common compliance pitfalls to avoid.
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