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.

Australian brands across retail, financial services, healthcare, and the public sector are racing to unify digital, marketing, and customer experience into a single connected discipline. This keynote opens the day by naming the gap between how customers experience a brand and how most Australian organisations are still structured to deliver it, and sets the questions the day's sessions will return to again and again.

• From omnichannel retail to digital-first banking and government services, Australian consumers now expect seamless, personalised, real-time interactions regardless of channel, and the organisations closing that expectation gap fastest are the ones treating digital, marketing, and CX as one connected capability, not three competing budgets.
• What Australian leaders across retail, insurance, banking, and the public sector are learning as they consolidate legacy platforms, unify customer data, and redesign journeys around real behaviour rather than tidy funnels.
• As AI-driven personalisation and decisioning become standard practice, Australian organisations face particular scrutiny given the market's growing sensitivity to data use and algorithmic decision-making, making trust a genuine competitive differentiator rather than a compliance checkbox.

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 — retention, lifetime value, 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.

As digital, marketing, and customer experience functions converge around shared data and shared customers, unresolved questions about ownership, budget, and decision rights are creating friction that slows execution.

• Concrete examples of how unclear accountability between teams leads to duplicated effort, conflicting customer messaging, or stalled initiatives.
• What leading organisations are trying — shared KPIs, unified customer councils, merged teams — and what's actually holding up under pressure.
• How resolving ownership questions is directly tied to unlocking sustained investment, since finance teams hesitate to fund initiatives without a clear accountable owner.

As marketing leaders face pressure to rationalise bloated technology stacks built up over years of point-solution adoption, this panel examines the real decisions being made about what to keep, what to cut, and what replaces the tools that don't survive the review.

• Beyond cost, what factors are determining which tools survive consolidation and which get eliminated.
• Real trade-offs organisations are experiencing between flexible, best-of-breed architectures and unified platform consolidation.
• How marketing operations leaders are handling the internal disruption and retraining that comes with retiring tools teams have built workflows around.

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 acquisitions and disconnected platforms left customer data scattered across dozens of systems, one digital leader built a unified customer data foundation that finally let marketing, digital, and CX teams see the same customer at the same time, without a multi-year rip-and-replace project.

• How the team prioritised which data sources genuinely mattered for near-term use cases, rather than attempting a complete data unification upfront.
• Why the solution connected and normalised existing systems rather than requiring their retirement, dramatically shortening time to value.
• How access to the same customer view changed daily workflows across marketing, digital, and CX teams that had previously operated on different assumptions about the same customer.

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.

Facing scepticism from finance leadership about funding experience improvements with no clean, direct revenue attribution, one leader built a business case approach that secured sustained investment by reframing the conversation entirely.

• How the team moved away from engagement metrics and toward retention, cost-to-serve, and churn indicators that resonated in financial terms.
• How a series of contained, measurable pilot projects built the credibility needed to unlock larger, longer-term investment.
• Building a standing framework for demonstrating experience ROI, rather than rebuilding the argument from scratch every funding cycle.

Facing budget pressure and a sprawling, overlapping technology stack built up over years of incremental tool adoption, one marketing operations leader led a consolidation effort that significantly cut costs while maintaining, and in some cases improving, the team's actual capability.

• How the team discovered significant overlap and underused licences across the stack before making any cutting decisions.
• The framework used to distinguish tools that could be eliminated outright from those that needed to be merged into a single platform.
• How the team navigated internal resistance from colleagues attached to specific tools, and got alignment on the new, leaner stack.

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.

With customer journeys spanning increasingly non-linear paths across channels, one leader moved beyond traditional funnel-based journey mapping to build an adaptive framework that other teams across the organisation could apply to their own customer segments.

• Recognising that customers weren't following predictable linear paths, and that forcing journey design into that shape was actively obscuring real behaviour.
• How the framework was built to be adapted by other teams and business units rather than remaining a one-off project specific to a single customer segment.
• The change management work required to shift teams away from familiar funnel thinking toward a more adaptive, behaviour-driven approach to journey design.

Facing looming dependence on third-party data sources that were rapidly disappearing, one digital marketing team built a first-party data capability from a standing start, creating a sustainable foundation for personalisation and targeting independent of external signals.

• How the team identified what value proposition would genuinely motivate customers to share first-party data directly, rather than assuming goodwill alone would suffice.
• The practical integration work required to capture first-party data through natural customer interactions, rather than creating separate, friction-heavy collection moments.
• How the team validated that first-party data could support personalisation and targeting effectively before fully weaning off third-party sources.

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.

Years of point-solution adoption have left many marketing and digital teams managing bloated, poorly integrated technology stacks. This panel explores how leaders are deciding between consolidating onto fewer platforms, embracing composable architecture, or rebuilding from scratch.

• Beyond licensing fees, how fragmented tooling is quietly eroding data quality, team velocity, and the ability to deliver connected customer experiences.
• What organisations are learning about the flexibility-versus-complexity trade-off between best-of-breed composable stacks and unified platforms.
• Practical lessons on consolidating or replatforming martech infrastructure without stalling the customer-facing work the stack is supposed to enable.

With cookie deprecation, privacy regulation, and fragmented customer journeys making precise attribution increasingly impossible, this panel explores how marketing leaders are adapting measurement practices and rebuilding credibility with finance in an environment of permanent data uncertainty.

• Comparing the practical strengths and limitations of media mix modelling, incrementality testing, and first-party data strategies as attribution alternatives.
• How marketing leaders are communicating confidence and uncertainty honestly to finance stakeholders who are used to exact attribution numbers.
• What it's actually taking, organisationally and technically, to build first-party data capability robust enough to reduce dependence on third-party signals going forward.

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.

With a lean digital team unable to keep pace with personalisation demands across dozens of customer segments and channels, one leader built an automated personalisation framework that scaled output without proportionally scaling headcount.

• How reusable rules and content frameworks let a small team support far more personalised variation than manual execution ever could.
• Identifying which personalisation decisions still required human strategic input, and building clear handoff points between automated and human-led work.
• How the team ensured that scaling volume didn't come at the cost of relevance, building feedback loops to catch personalisation that missed the mark.

With cookie deprecation eliminating a core input to their existing attribution model, one marketing analytics leader rebuilt measurement around first-party data and incrementality testing, restoring confidence in marketing ROI reporting that had been thrown into question.

• How the team moved past attempting to patch the old model and instead built measurement around a fundamentally different, less granular but more durable approach.
• The specific methodology used to triangulate marketing impact from multiple imperfect signals rather than relying on any single measurement method.
• How the team communicated the shift to stakeholders accustomed to precise attribution, and what it took to restore trust in a necessarily less exact measurement approach.

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.

As AI enables hyper-personalised experiences at unprecedented scale, customers are growing simultaneously more receptive to relevant engagement and more wary of how their data is being used to achieve it. This keynote explores how leading organisations are navigating that tension without sacrificing either growth or trust.

• Why more sophisticated targeting and customisation can just as easily erode trust as build loyalty, and how organisations are learning to read the difference between helpful and unsettling.
• How forward-thinking brands are making data use visible and controllable to customers as part of the experience itself, turning a legal requirement into a trust-building feature.
• As AI increasingly mediates the relationship between brand and customer, what that means for accountability when personalisation gets it wrong.

With privacy regulation, cookie deprecation, and AI-mediated search all fragmenting the data trail marketing has traditionally relied on for attribution, this closing keynote examines how marketing leaders are rebuilding the case for their budgets when precise, full-journey tracking is no longer possible.

• Revisiting the limitations of traditional attribution models, and why current disruption is accelerating a reckoning that was overdue regardless.
• Emerging approaches that marketing teams are adopting to demonstrate impact without complete journey visibility.
• How marketing leaders are reframing ROI conversations with finance around confidence intervals and directional evidence, rather than the precise attribution numbers that are becoming harder to produce.

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.

With growing pressure to justify technology and experience investment in commercial terms, leaders are re-examining which metrics genuinely predict business outcomes and which have simply become comfortable habits.

• A candid look at which long-standing engagement and satisfaction metrics are losing credibility with finance and executive stakeholders.
• How leading teams are moving from correlating experience improvements with outcomes to demonstrating direct commercial impact.
• As AI becomes embedded across personalisation, content, and decisioning, how organisations are isolating and proving its incremental value rather than crediting it for gains that would have happened anyway.

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 Sydney on 18 March 2027.