Varun Verma, L'Oréal Australia and New Zealand Chief Data Analytics Officer, 40 under 40 Data Scientist 2024 and Top AI and Data Analytics Leader of the Year, is our Opening International Keynote Speaker for Smarter Data Meets AI 2024.
He joins us to talk about the data-driven transformation at L'Oréal, bringing a stronger and more collaborative data culture into the organisation, and embracing new ways of working with AI and ML.
We will hear how L'Oréal is democratising access to data and insights, and how data is helping shape the future of the business. In his talk, Varun will cover:

• Why data democratisation starts with understanding the right business objectives.
• Getting the rest of the company to start consuming data for the purpose of decision making.
• Finding out what is relevant for different profiles and personas.
• Data curiosity + agility – and the challenges of changing mindsets.
• Our data ecosystem and how AI is helping us overcome data silos.
• Successful use cases: How L'Oréal is using data and AI in marketing.

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About Varun

Varun Verma is an Australian expert in AI and Data Analytics, and the current  Chief Data Analytics Officer at L'Oréal Australia and New Zealand.

With a history of leadership in top-tier organisations like L'Oréal, Heineken, PwC, Visa, Accenture, and Allianz, Varun excels in data strategy, Centre of Excellence setup, and driving data-driven transformations. He's an innovator who leverages AI and Machine Learning for growth, and he's passionate about building high-performing teams across various industries.

His analytical skills include digital & data strategy, business intelligence, machine learning, big data, and Artificial Intelligence. His educational qualification includes an MBA in Marketing & Information Systems and a Bachelor of Engineering in Computer Science.

Co-presented with Douglas Nicol

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Generative AI is one of the fastest-growing technologies in human history. In this session we look beyond the hype to examine the impact of AI on the lives of mainstream consumers, 52% of whom are now using AI regularly. This means we need to ask new questions. How are consumers making purchase decisions differently? How is shopping culture changing due to AI? And how is AI breaking some of the traditional principles of the retail path to purchase?

Hear how the Super Retail group is using AI to take advantage of these changes and to improve the productivity of their marketing team.

Regardless of where you are on your AI journey, this session will get you thinking differently about the threats and opportunities of Generative AI. Gain insights from new research on how to adapt and build an advantage by changing your thinking about traditional ‘customer journeys’. 

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About Aaron

Aaron is a highly experienced leader in the art of Customer, Experience & Commercial, helping construct great outcomes for complex organisations with the will to transform and drive customer value. He is driven by performance and speed to value, with deep Customer, Product, Design, Marketing and Scaled Agile experience, wrapped together with a growth DNA, strong business understanding, analytical focus, and technologies across retail, financial services, loyalty, travel, and start-ups. 

He has 30+ years’ experience in orchestrating and embedding change, delivering successful customer propositions and digital businesses. He is a driven leader of multi-discipline, matrix teams with strong financial management capabilities and business acumen. 
Aaron is also a Lecturer in Marketing, Digital & Data at the University of New South Wales Australia (UNSW). 

Fireside Chat with Brian Ferris

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We are delighted to have Lizzy Ryley, CEO of Loyalty NZ (LNZ), join us to discuss key insights from recent research with senior marketers at leading NZ brands, which questions whether we are getting the most out of our data and digital data-driven customer engagement.

Lizzy sits down for a Fireside Chat with Brian Ferris, Chief Data, Analytics & Technology Officer, in which they’ll explore:

1. Using data to deliver meaningful connections with your customers.
2. Why digital transformation is built on data and the ability to leverage it.
3. What do the customers want? Personalisation vs privacy.
4. Why it’s critical that marketers understand the business context.
5. Lessons from LNZ’s own transformation journey.
6. How to nurture a continuous learning culture around data and AI.

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About Lizzy

Lizzy has extensive experience in strategic marketing and building customer loyalty through the innovative use of customer data.

Her extensive expertise comes from working with major global organisations. Prior to joining Loyalty NZ in September 2017, Lizzy held a number of senior roles with Woolworths Ltd, including General Manager (GM) Marketing, and GM Group Loyalty & Data in Australia, and GM Marketing & Corporate Affairs in NZ (Countdown supermarkets).

Prior to this, Lizzy spent 20 years living in the UK, working in senior marketing roles in retail, FMCG and the academic sector.

Lizzy holds an MBA from Sheffield Hallam University (UK) and is a graduate of the Australian Institute of Company Directors. She is a member of Global Women and the Institute of Directors in NZ.

ANZ Group CMO and 2023 Effies Effective Marketer of the Year, Astrud Burgess, says that data is the most fascinating part of her job. We have invited her to lift the lid on the innovative and disruptive work she’s leading at ANZ to strengthen communications with customers and build brand trust.

Astrud will also share how the bank is developing the capabilities needed to achieve their data ambition. And discuss what’s next for the utilisation of data at ANZ. Don’t miss this fascinating keynote which delves into topics such as:

• Achieving growth through a customer-centric, data-led approach to marketing
• The advantages of partnering to unlocking the competitive value in our data
• The challenges to using AI effectively at scale.

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About Astrud

Astrud is responsible for the continued growth and development of New Zealand's leading financial services brand. Her portfolio includes all brand, advertising, marketing and sponsorship activities across ANZ New Zealand's business. She is also responsible for creating strategic competitive advantage from data through the development and deployment of customer insights, delivering better decisions through analytics and ensuring data is well governed.

Astrud has held various marketing and data roles at ANZ. Prior to her time at ANZ she worked in a variety of roles in financial services and advertising in New Zealand and the United Kingdom.

She has a Masters in Marketing Management from Otago University.

Despite telecommunications services now playing an intimate and ubiquitous role in our lives, the category is still highly transactional with minimal customer-relationship building. With their hugely ambitious and multi-award winning Made For You martech programme, Spark NZ set out to change that. With MFYR, each customer gets personalised insights and recommendations, resulting in unparalleled ROI and customer retention.

The scale of this challenge was enormous, with a cross-functional team crunching over 2.6 million rows of data, combining five disparate data sets to deliver backend-decisioning indicators, analysing 52 data points per customer, and serving up 250 variable content versions. Matt Bain joins us to share lessons from this and other projects where Spark has used AI and world-class martech to mine and interrogate complex data.

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About Matt

As Marketing Director, Matt is responsible for Sparks Brand Experience, Experience optimisation, Marketing, and data analytics teams at Spark, and Qrious – Sparks Data Analytics consultancy.

Matt was previously based in Amsterdam as European Managing Director for agency AKQA – one of the world’s leading innovation and brand experience agencies, with responsibility for 700+ consultants and makers across five countries.

Over a 24-year career Matt has built an impeccable international reputation with some of the world’s greatest brands – Nike, Heineken, Mini, Rolls Royce, Siemens, EA Sports, Audi, Phillips, Tommy Hilfiger and KLM amongst others. 

Futurist and exponential tech thinker Ben Reid shares his predictions for the future of AI.

How we interact with technology is heading for a radical shift, changing how we live, work and think - as marketers and as consumers. Will we be marketing to robots, with AI-powered assistants making most or all buying decisions? Will marketing end up as a sea of sameness with everyone relying on the same synthetic data? And what skills and knowledge will be crucial for marketers in a world powered by AI?

There’s no manual for what’s happening right now but Ben does give us a framework for thinking about AI and how to approach it. It’s time to get our feet wet.

• How AI is evolving right now and trying to make sense of it
• Understanding just how big the opportunity is
• Global trends and local implications
• What risks do we need to consider?

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About Ben

Memia founder Ben Reid works as a strategic technology advisor with senior leadership teams across Aotearoa New Zealand, Australia and the Asia-Pacific region, advising on technology strategy, growth planning and innovation.

He is also an experienced commentator and public speaker focusing on new emerging technology trends and their impacts on business and society.

Ben is the author of the Memia newsletter which explores the cutting edge of new emerging technologies and the implications for society and the economy.

 

Fireside Chat with Lizzy Ryley

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We are delighted to have Lizzy Ryley, CEO of Loyalty NZ (LNZ), join us to discuss key insights from recent research with senior marketers at leading NZ brands, which questions whether we are getting the most out of our data and digital data-driven customer engagement.

Lizzy sits down for a Fireside Chat with Brian Ferris, Chief Data, Analytics & Technology Officer, in which they’ll explore:

1. Using data to deliver meaningful connections with your customers.
2. Why digital transformation is built on data and the ability to leverage it.
3. What do the customers want? Personalisation vs privacy.
4. Why it’s critical that marketers understand the business context.
5. Lessons from LNZ’s own transformation journey.
6. How to nurture a continuous learning culture around data and AI.

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About Brian

Brian has worked in information technology for over 20 years, with extensive experience leading data and analytics teams while managing projects and building solutions in a global environment.

He returned to New Zealand in January 2019 after working at Nike leading their EMEA Enterprise Data and Analytics practice, based in Amsterdam. At Nike, Brian was focused on building and leading the team’s capability; migrating the business to the cloud and developing an advanced analytics function to deliver value to the business. Prior to Nike, Brian was the Global Architect for Data and Analytics at Heineken, based in Amsterdam, which followed a senior data role at the European Central Bank, based in Frankfurt.

He joined the Loyalty NZ team as Chief Data and Analytics Officer where he is championing a high performing agile culture and reinventing Loyalty D&A with new platforms and advanced analytics. In 2020, Brian was appointed to the expanded role of Chief Technology & Data Officer.

His specialties include data and analytics architecture and platforms, loyalty and membership analytics, leading data and analytics teams in multi-national environments, cloud migration, and getting value out of data science investments. Brian is the co-author of the book “Transition to Advanced Analytics”

With a strategic and curious mindset shaped by over 40 years of experience across Europe, North America, and APAC countries, Colleen is a pioneering force in the field of insights and planning. As the founder of TRBI, an international research and strategy agency based in the UK, Colleen championed the implementation of insights to guide creative and innovative strategies for clients.

Today, at TRA, Colleen leverages advancements in knowledge across multiple disciplines including cultural sociology, social psychology, behavioural science, and cultural analysis to bring breakthrough insights to bear on brand strategy, creative development, and customer centricity.

Her work helps clients achieve their goals by developing strategies that truly resonate with their audiences.

In recent years, marketers have been inundated with data and forced to find effective means of analysing it. AI’s ability to process millions—if not billions—of data points in near real time has unlocked an enormous potential, but now marketers face another big hurdle in order to use AI effectively: Do I have access to the right data? And am I leveraging my data effectively? 

We have invited a panel of marketing, AI and data professionals to discuss how to ensure data quality with the sheer volume, velocity, and variety of data that organisations deal with today. Questions they’ll consider include: 

• Are modern innovations in data and AI sufficiently able to not only help in analysing data, but also to fill any gaps?
• How do you trust that the AI models you choose to employ are fit for purpose?
• How to best use synthetic data, unstructured data and other sources now available to understand our customers.
• What are the watchouts for marketers when using AI generated data.
• How to safeguard against bias in AI (algorithmic, prompting, data and interpretation biases)?
• Examples of where our panellists have had the best success with leveraging AI capabilities.

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About Kiya

Kiya is a Manager in the Data & Analytics practice at PwC New Zealand. She and her team bring a deeply human and equitable approach to data, Artificial Intelligence (AI) and technology. With a background as a Data Scientist, Kiya has worked with government agencies, NGOs, and businesses to harness the power of data for economic, social and environmental benefit.

Passionate about ensuring ethics in AI, data and emerging technology, Kiya has actively contributed to this rapidly advancing space through her involvement in various advisory groups. She has served on the Prime Minister’s Chief Science Advisor AI Reference Group, Amnesty International Global AI Working Group, Tikanga in Technology: Indigenous Data in AI, Digital Identity New Zealand Biometrics Special Interest Group, and the Coalition for Better Digital Policy New Zealand.

In recent years, marketers have been inundated with data and forced to find effective means of analysing it. AI’s ability to process millions—if not billions—of data points in near real time has unlocked an enormous potential, but now marketers face another big hurdle in order to use AI effectively: Do I have access to the right data? And am I leveraging my data effectively? 

We have invited a panel of marketing, AI and data professionals to discuss how to ensure data quality with the sheer volume, velocity, and variety of data that organisations deal with today. Questions they’ll consider include: 

• Are modern innovations in data and AI sufficiently able to not only help in analysing data, but also to fill any gaps?
• How do you trust that the AI models you choose to employ are fit for purpose?
• How to best use synthetic data, unstructured data and other sources now available to understand our customers.
• What are the watchouts for marketers when using AI generated data.
• How to safeguard against bias in AI (algorithmic, prompting, data and interpretation biases)?
• Examples of where our panellists have had the best success with leveraging AI capabilities.

In recent years, marketers have been inundated with data and forced to find effective means of analysing it. AI’s ability to process millions—if not billions—of data points in near real time has unlocked an enormous potential, but now marketers face another big hurdle in order to use AI effectively: Do I have access to the right data? And am I leveraging my data effectively? 

We have invited a panel of marketing, AI and data professionals to discuss how to ensure data quality with the sheer volume, velocity, and variety of data that organisations deal with today. Questions they’ll consider include: 

• Are modern innovations in data and AI sufficiently able to not only help in analysing data, but also to fill any gaps?
• How do you trust that the AI models you choose to employ are fit for purpose?
• How to best use synthetic data, unstructured data and other sources now available to understand our customers.
• What are the watchouts for marketers when using AI generated data.
• How to safeguard against bias in AI (algorithmic, prompting, data and interpretation biases)?
• Examples of where our panellists have had the best success with leveraging AI capabilities.

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About Andrew

Andrew is passionate about using data to help clients solve their business problems. Highly skilled in all facets of Quantitative research, advanced analytics, market sizing and financial analysis. Extensive experience in Financial Services, FMCG, Utilities, Telecommunications, Social research and Government projects.

Andrew is exceptional in providing clients with the confidence to act based on a sound understanding of the opportunities and issues they face, including the financial implications and ROI of any actions.

In recent years, marketers have been inundated with data and forced to find effective means of analysing it. AI’s ability to process millions—if not billions—of data points in near real time has unlocked an enormous potential, but now marketers face another big hurdle in order to use AI effectively: Do I have access to the right data? And am I leveraging my data effectively? 

We have invited a panel of marketing, AI and data professionals to discuss how to ensure data quality with the sheer volume, velocity, and variety of data that organisations deal with today. Questions they’ll consider include: 

• Are modern innovations in data and AI sufficiently able to not only help in analysing data, but also to fill any gaps?
• How do you trust that the AI models you choose to employ are fit for purpose?
• How to best use synthetic data, unstructured data and other sources now available to understand our customers.
• What are the watchouts for marketers when using AI generated data.
• How to safeguard against bias in AI (algorithmic, prompting, data and interpretation biases)?
• Examples of where our panellists have had the best success with leveraging AI capabilities.

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About Nicola

Nicola is an experienced, passionate, integrated marketing comms professional. Employed across the globe in the UK, Australia, Hong Kong and now New Zealand, has given her the opportunity to work with regional and global brands, covering various digital disciplines.

As the media landscape has become so fragmented, it's imperative that brands focus on human-centric marketing and this is key when developing strategies. Technology can drive efficiency and effectiveness for brands with the right set up of tools and analysis of data. The best strategies are data driven and Nicola aspires to deliver the best insights possible, based on data, to inform strategy, using the latest innovation to develop creative to drive engagement.

In recent years, marketers have been inundated with data and forced to find effective means of analysing it. AI’s ability to process millions—if not billions—of data points in near real time has unlocked an enormous potential, but now marketers face another big hurdle in order to use AI effectively: Do I have access to the right data? And am I leveraging my data effectively? 

We have invited a panel of marketing, AI and data professionals to discuss how to ensure data quality with the sheer volume, velocity, and variety of data that organisations deal with today. Questions they’ll consider include: 

• Are modern innovations in data and AI sufficiently able to not only help in analysing data, but also to fill any gaps?
• How do you trust that the AI models you choose to employ are fit for purpose?
• How to best use synthetic data, unstructured data and other sources now available to understand our customers.
• What are the watchouts for marketers when using AI generated data.
• How to safeguard against bias in AI (algorithmic, prompting, data and interpretation biases)?
• Examples of where our panellists have had the best success with leveraging AI capabilities.

Co-presented with Sean Wiggans

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The advancement of machine learning has made advanced measurement practices - such as Market Mix Modelling - much more accessible. We are growing a far more nuanced appreciation of the importance of the journey to purchase, rather than just giving all the credit to the last step before reaching the destination.

This is not just another talk on data analytics. Whether you're a small enterprise or a large corporation, through these two case studies we will give you a roadmap to understand which of your marketing efforts are truly effective. 

• Overcoming digital and cookie deprecation biases.
• Strategies to enable actionable decision-making using data science.
• Using AI to build confidence in your media mix amidst channel fragmentation.
• Addressing the challenges of mass reach and digital attribution over-reporting.
• What’s changed? Key aspects of Modern MMM vs Traditional MMM.

Case Study 1: Turners Cars 
Turners has been on a multi-year data and analytics journey to better understand the impact of their marketing. Like most, Turners has faced many challenges long the way in getting to the truth of what is effective. GM of Marketing Sean Wiggins joins us to discuss how they have used MMM to help build confidence in their media mix.

Case Study 2: RestoreMe Clinic 
RestoreMe Clinic is a challenger startup and SME with limited resources. Alex Rowley will discuss how they overcame challenges in digital marketing and achieved accurate channel assessment. Find out how they enhanced their marketing efficiency and optimised budgets, all operational within a month. Learn about their strategic digital approach and the significant impact of modern MMM-driven insights in a competitive healthcare market.

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About Alex

Alex Rowley is a results-driven data scientist with a robust background at EY and Quantium, where he leveraged analytics to inform strategic decisions across tech and financial sectors. His expertise in predictive modeling and machine learning has been instrumental in driving performance and delivering data-driven solutions.

Co-presented with Alex Rowley

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The advancement of machine learning has made advanced measurement practices - such as Market Mix Modelling - much more accessible. We are growing a far more nuanced appreciation of the importance of the journey to purchase, rather than just giving all the credit to the last step before reaching the destination.

This is not just another talk on data analytics. Whether you're a small enterprise or a large corporation, through these two case studies we will give you a roadmap to understand which of your marketing efforts are truly effective. 

• Overcoming digital and cookie deprecation biases.
• Strategies to enable actionable decision-making using data science.
• Using AI to build confidence in your media mix amidst channel fragmentation.
• Addressing the challenges of mass reach and digital attribution over-reporting.
• What’s changed? Key aspects of Modern MMM vs Traditional MMM.

Case Study 1: Turners Cars 
Turners has been on a multi-year data and analytics journey to better understand the impact of their marketing. Like most, Turners has faced many challenges long the way in getting to the truth of what is effective. GM of Marketing Sean Wiggins joins us to discuss how they have used MMM to help build confidence in their media mix.

Case Study 2: RestoreMe Clinic 
RestoreMe Clinic is a challenger startup and SME with limited resources. Alex Rowley will discuss how they overcame challenges in digital marketing and achieved accurate channel assessment. Find out how they enhanced their marketing efficiency and optimised budgets, all operational within a month. Learn about their strategic digital approach and the significant impact of modern MMM-driven insights in a competitive healthcare market.

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About Sean

Sean Wiggans, an industry veteran, serves as the GM Marketing at Turners. He’s responsible for brand building, lead acquisition, and enhancing the customer journey across all channels, working closely with Sales, Operations, and IT

Co-presented with Aaron Fuller

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Generative AI is one of the fastest-growing technologies in human history. In this session we look beyond the hype to examine the impact of AI on the lives of mainstream consumers, 52% of whom are now using AI regularly. This means we need to ask new questions. How are consumers making purchase decisions differently? How is shopping culture changing due to AI? And how is AI breaking some of the traditional principles of the retail path to purchase?

Hear how the Super Retail group is using AI to take advantage of these changes and to improve the productivity of their marketing team.

Regardless of where you are on your AI journey, this session will get you thinking differently about the threats and opportunities of Generative AI. Gain insights from new research on how to adapt and build an advantage by changing your thinking about traditional ‘customer journeys’. 

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About Douglas

Douglas is Strategy Partner at The Works which is part of global digital transformation powerhouse Capgemini. He is passionate about data-informed marketing and humanising data. He has twice delivered TEDx Talks, most recently on Emotional Data. In 2016 he founded a start-up sister agency to The Works called On Message, specialising in chatbots, voice and AI.
 
The Works sits at number one in the Great Place To Work Awards for advertising agencies in Australia and counts Destination NSW, VISA, The Smith Family, Qantas, Subaru, CommSec, Goodman Fielder and TAFE among its clients.