Melbourne Agenda & Speakers

Beat the rush and join us early for complimentary barista-made coffee and breakfast.

Kick off the day with a welcome from your MC and a look at what's ahead.

As customers increasingly ask AI assistants to research, compare and even buy on their behalf, the website and app are no longer guaranteed to be the first point of contact. This keynote examines what it takes to stay discoverable and transactable when the "visitor" may be a machine.

• How discovery is shifting from search results and navigation to conversational AI.
• From structuring product data to agent-ready APIs: critical groundwork enabling AI agents to think and act.
• Why the digital experience still matters and where the human interface continues to win.

As AI-generated answers and AI Overviews increasingly intercept the customer's search journey before a brand's own website is ever clicked, this opening keynote confronts the fundamental shift underway in how marketing teams need to think about discoverability, and what marketing technology needs to look like when the search engine is no longer the primary audience.

• How AI-generated answers are changing the economics of organic visibility, and why traditional SEO metrics increasingly fail to capture whether a brand is actually reaching its audience.
• The practical, structural changes marketing and content teams are making to improve how AI systems surface and represent their brand, distinct from traditional keyword and backlink strategies.
• Which martech investments still earn their keep in an AI-mediated discovery landscape, and how marketing leaders prove ROI when the customer journey itself is harder to trace.

After years of customer experience being championed as a cultural value but funded as a discretionary cost, this opening keynote examines the shift underway as CX leaders build the commercial case that finally earns experience investment a permanent seat at the budget table.

• What's driving the shift in how boards and executives view customer experience investment, and why this moment is different from previous cycles of CX enthusiasm.
• Moving beyond satisfaction scores toward retention, lifetime value, and cost-to-serve metrics that speak the language finance leaders trust.
• What genuinely differentiated experience looks like when every competitor has access to the same AI tools, and how CX leaders prove their work moves the business, not just the survey scores.

Despite years of investment in digital, marketing, and customer experience technology, many leaders still struggle to demonstrate commercial impact in terms that unlock sustained budget and executive confidence.

• Distinguishing between engagement metrics that feel impressive internally and the commercial indicators, such as retention, lifetime value and cost-to-serve, that genuinely influence funding decisions.
• Practical approaches for building the causal link between a better customer journey and measurable business outcomes, rather than relying on correlation and anecdote.
• How leaders are securing sustained investment in experience and brand-building work whose payoff often plays out over years, not quarters.

Despite years of calls for marketing technology consolidation, most stacks continue to grow rather than simplify. This keynote examines the structural and organisational forces driving continued sprawl, and what it actually takes to reverse the trend rather than just talk about it.

• The incremental decision-making that leads to bloated stacks, even among teams who genuinely intended to consolidate.
• Beyond licensing fees, how fragmented tooling quietly degrades data quality, slows execution, and makes AI initiatives harder to deploy consistently.
• Lessons from marketing teams who've genuinely reduced stack complexity, and the organisational conditions that made it possible where others have failed.

As AI-powered service, personalisation, and self-service become table stakes rather than differentiators, this keynote examines where genuine customer experience advantage still exists once the technology itself is no longer a competitive edge.

• Why baseline AI-driven service is rapidly becoming an expectation rather than a differentiator, and what that means for where brands should focus instead.
• Identifying the specific moments in the customer journey where human interaction continues to build loyalty in ways AI hasn't replicated.
• How leading brands are deliberately investing in experience moments that create emotional connection, even where efficiency alone would argue for full automation.

AI is changing what digital experiences can do, and AI agents are starting to search, compare and act on customers’ behalf. But more automation doesn’t automatically make an experience better. This panel explores how digital leaders are designing experiences that stay simple, useful and human, whether a customer arrives directly or through an AI agent.

• What customers genuinely value from digital experiences, and where AI and agents add to that value instead of adding complexity.
• Designing for two audiences: making content, products and services clear and trustworthy for people, and for the AI agents acting on their behalf.
• Keeping the relationship with customers meaningful when AI assistants and agents sit between an organisation and its audience.

With AI reshaping every layer of marketing technology, the stack that got teams here won't be the one that takes them forward. This panel brings together marketing and technology leaders to map out what the modern martech stack really looks like, and how to get there.

• The core capabilities every marketing stack needs in 2027, and where AI is changing what those capabilities do.
• How leading teams are choosing between platforms, specialist tools and AI-native solutions, and making them work together.
• Practical steps for evolving the stack without disrupting the campaigns and teams that depend on it.

AI is taking on an increasing share of customer interactions, from service to sales to support. This panel brings together CX leaders to discuss where they've deliberately kept humans in the loop, and what's driving those decisions.

• Concrete examples of interaction types where organisations have found AI consistently underperforms human judgment, regardless of technical capability.
• Why poorly designed transitions between AI and human agents remain one of the most common sources of customer frustration, and what's actually fixing it.
• How organisations are building frameworks that weigh AI's efficiency gains against its real impact on trust and loyalty.

After years of chatbots that frustrated more customers than they helped, one digital leader launched an AI assistant that now resolves a meaningful share of enquiries on its own and earns better satisfaction scores than the channels it replaced.

• How the team chose the first use cases, focusing on high-volume questions where AI could genuinely resolve rather than deflect.
• The content, data and guardrail work behind the scenes that made answers accurate and on-brand.
• Designing a smooth handover to a human when the assistant reaches its limits, and measuring success beyond containment rates.

Facing a dramatic drop in organic traffic as AI-generated search answers began satisfying customer queries before they reached the company's website, one marketing leader rebuilt their content and technical SEO strategy specifically to improve visibility within AI-generated answers rather than chasing traditional rankings alone.

• How the team realised traffic decline was happening despite stable or improved search rankings, pointing to a structural shift rather than an SEO performance issue.
• The specific content and technical changes made to improve the likelihood of being cited within AI-generated answers.
• How the team developed measurement approaches for brand presence within AI answers, since traditional click-through data could no longer tell the whole story.

After noticing customer satisfaction dropping despite successful AI service deployment, one CX leader discovered the problem wasn't the AI itself but broken handoffs to human agents, and rebuilt the transition to preserve context and eliminate repetition.

• How the team used complaint and satisfaction data to trace declining sentiment back to the handoff moment specifically, rather than assuming the AI itself was underperforming.
• The specific changes made to ensure human agents received full conversation history automatically, so customers never had to repeat themselves.
• How the team tracked the redesign's impact on downstream loyalty and repeat engagement, not just immediate post-interaction ratings.

Recharge with refreshments and structured networking with your peers.

A hands-on, interactive session working through a real digital experience scenario as a room. Details announced soon.

A hands-on, interactive session working through a real marketing technology scenario as a room. Details announced soon.

A hands-on, interactive session working through a real customer experience scenario as a room. Details announced soon.

With customers abandoning the site after failed searches, one digital team replaced traditional keyword search with a conversational AI experience that understands intent and guides visitors to the right product or answer.

• Why traditional site search was quietly costing conversions, and how the team built the case for change.
• Structuring product and content data so the AI could give accurate, relevant answers.
• What changed in engagement and conversion after launch, and what the team would do differently.

As retail media budgets grow, marketers are increasingly questioning results reported by the networks selling the ads. One marketing leader built an independent approach to uncover what that spend was really delivering.

• Why platform metrics were overstating impact, and the case for independent measurement.
• How testing and data sharing separated incremental sales from those that would have happened anyway.
• How the findings reshaped budget allocation across retail media and other channels.

After customer research revealed growing discomfort with how data-driven personalisation felt, one digital experience leader redesigned data transparency and consent experiences to build trust directly into the product, moving well beyond minimum legal requirements.

• How the team used direct customer feedback to understand specifically which personalisation moments felt helpful versus invasive.
• The specific UX choices made to give customers meaningful control over their data without burying them in settings and consent fatigue.
• How the team demonstrated that customers who engaged with the new transparency features showed measurably higher retention and engagement over time.

Facing an ageing app and a roadmap measured in years, one digital leader used AI across design, development and testing to deliver a rebuilt app experience in a fraction of the expected time.

• Where AI accelerated the work most, and where human design and engineering judgement stayed essential.
• Keeping quality, accessibility and security on track while moving faster than ever before.
• How the team reshaped its ways of working, and the results customers noticed after launch.

Moving beyond AI experiments, one marketing team handed parts of real campaign execution to AI agents, from audience building to ongoing optimisation, and measured what changed.

• Choosing the first workflows to hand to agents, and why the team started small.
• The approval steps and brand checks that kept agent-run activity on track.
• The results in speed, cost and performance, and where humans still made the difference.

After discovering frontline staff were routinely working around a newly deployed AI-assisted service platform rather than using it, one operations leader rebuilt the tool around actual frontline workflows, turning adoption resistance into genuine usage and measurable customer experience improvement.

• How direct observation and frontline feedback revealed the platform had been designed around management reporting needs rather than the realities of a live customer interaction.
• The specific redesign choices made to fit the tool into how frontline staff actually worked, rather than requiring them to adapt to the system's original design.
• How the team tracked genuine tool usage as an early signal of the customer experience improvements that followed.

When AI can spin up new pages, features and journeys in hours rather than months, the bottleneck shifts from building to knowing what works. This panel explores how digital teams are rethinking experimentation and measurement to keep pace.

• Why faster build cycles are exposing gaps in testing capability, and how teams are scaling experimentation without drowning in results.
• Choosing what to test and what to ship straight away when the cost of building has dropped close to zero.
• Keeping analytics trustworthy and decision-ready as AI-generated experiences multiply across digital channels.

With cookies fading, privacy rules tightening and AI hungry for quality inputs, the marketing teams that win will be the ones with the strongest data foundations. This panel explores how leaders are building first-party data capability that powers both smarter marketing and more credible measurement.

• What it really takes, organisationally and technically, to build a first-party data foundation that marketing, analytics and AI can all rely on.
• Where data quality, consent and governance are making or breaking AI-driven personalisation and measurement.
• Comparing media mix modelling, incrementality testing and clean rooms, and how to present results finance will trust.

As customers become more sensitive to how their data fuels increasingly sophisticated personalisation, this panel examines how CX leaders are recalibrating their approach to stay effective without eroding the trust personalisation depends on.

• How organisations are distinguishing between personalisation that feels helpful and what triggers discomfort or backlash.
• How some brands are turning transparency about data use into a trust-building feature rather than a buried disclosure.
• Lessons from organisations that have redesigned personalisation around explicit, well-understood customer consent rather than passive data collection.

Small-group, discussion-based sessions where you'll work through real customer technology challenges with peers in similar roles. Roundtable topics announced soon.

Enjoy a complimentary lunch while connecting with fellow attendees.

Put your knowledge to the test in this fast-paced quiz covering real-world trivia, key concepts and emerging trends. Compete for bragging rights, and a travel voucher, as the top scorer takes the crown.

Rather than running scattered AI experiments, one digital leader embedded AI into the team's everyday design, content and optimisation work, lifting output without adding headcount.

• Choosing which tasks to hand to AI first, and building simple guidelines the whole team could follow.
• Bringing sceptical team members along, and upskilling them rather than sidelining them.
• The measurable gains in speed and quality, and the pitfalls the team learned to avoid.

As AI made it possible to target and personalise with far more customer data than before, one marketing leader rebuilt consent and data practices so the team could keep using AI confidently as privacy rules tightened.

• Where AI-driven targeting was creating new privacy risks, from inferred data to how customer information flowed between tools.
• Working with legal and privacy teams to put clear consent, data-use rules and controls into the marketing stack.
• How stronger privacy practices protected performance and built customer trust, instead of holding marketing back.

Facing a finance leader who viewed customer experience investment as unquantifiable cost rather than genuine business value, one CX leader built a measurement framework that connected experience improvements directly to retention and revenue, securing sustained budget where satisfaction scores alone had failed to persuade.

• How the team recognised that satisfaction and engagement scores were never going to win the budget argument, and shifted focus to metrics finance already trusted.
• The specific approach used to connect a defined experience improvement to a measurable change in retention or spend, rather than relying on correlation alone.
• How the framework built for one pilot became the standard approach for justifying future experience investment.

AI is making it possible for interfaces to reshape themselves around each user, changing layouts, content and journeys on the fly. This keynote explores what happens to digital design when the experience is no longer fixed, and how teams keep it usable, on-brand and accessible.

• Where dynamic, AI-generated interfaces are already delivering results, and where they are still more promise than practice.
• Keeping brand consistency and design quality when no two users see the same screen.
• Why inclusive and accessible design matters even more when experiences are generated automatically, and how to build it in from the start.

AI agents that plan, launch and optimise campaigns with minimal human input are moving into practice. This keynote explores how agentic AI is reshaping marketing, and what leaders need to use it effectively.

• Where AI agents are already taking on marketing workflows, from audience building and content to bidding and optimisation.
• The guardrails, approvals and brand controls needed to keep autonomous marketing on strategy and on brand.
• How roles, skills and team structures are evolving as agents take on more execution.

As customer experience increasingly depends on frontline employees empowered by, but not replaced by, AI tools, this keynote makes the case that customer experience strategy that ignores employee experience is building on an unstable foundation.

• Evidence connecting frontline employee frustration, tool complexity, and burnout directly to declining customer experience outcomes.
• The difference between AI deployments that empower employees to deliver better service and those that employees experience as surveillance or added complexity.
• How churn among frontline and service staff quietly erodes the consistency and quality of customer experience over time, even when technology investment continues.

In this interactive closing session, the room designs the digital experience stack of the future together. Attendees pitch, debate and vote in real time on which capabilities make the cut, and the results reveal where the industry thinks digital is really heading.

• Which layers of today's digital stack survive the shift to AI-driven and agent-led experiences, and which are ripe for replacement.
• Live audience votes on the capabilities that matter most, from experimentation and content to data, personalisation and agent readiness.
• A snapshot of priorities to take back to your own roadmap, shaped by peers facing the same decisions.

As AI-assisted content production scales rapidly across marketing teams, this think tank looks at the governance question many organisations have avoided: who is actually accountable for quality, brand consistency, and risk when content is produced faster than traditional review processes can keep pace with.

• Concrete examples of how AI-generated content volume is outpacing existing brand and legal review capacity, and what's slipping through as a result.
• How some marketing teams are designing tiered review processes that maintain quality control without eliminating the efficiency gains AI was meant to deliver.
• Clarifying where responsibility actually sits when AI-assisted content causes a brand or compliance issue, and how that's shaping internal sign-off processes.

With points-based loyalty programs facing growing scepticism amid changing consumer expectations and tighter marketing budgets, this discussion examines whether traditional loyalty mechanics still drive genuine behaviour change or have simply become an expected cost of doing business.

• Honest evidence on whether loyalty program investment is still producing measurable incremental behaviour versus rewarding customers who would have stayed anyway.
• Early results from alternative approaches such as community, experiential rewards, and tiered recognition, and whether they're genuinely outperforming traditional programs.
• How leading organisations are redesigning programs specifically around the customer segments and behaviours most tied to long-term value, rather than broad-based point accumulation.

Wrap-up of the day's key takeaways, and your chance to win some epic prizes.

Unwind with your peers for a couple of drinks on us!

See you at CustomerTech World New York on 5 May 2027.