• Extracting Real-Time Insights: Leveraging advanced AI techniques to gain immediate insights from customer data and improve decision-making processes.
• Predictive Analytics for Proactive Engagement: Using predictive analytics to anticipate customer needs and behaviours, enabling proactive and personalized interactions.
• Scalable AI Solutions: Implementing scalable AI solutions that can handle large volumes of data and deliver real-time personalization at scale.

• How deploying AI can streamline operations, reduce costs, and enhance decision-making
• Integrating AI across the organization to drive value, operational excellence, and customer satisfaction in today's competitive landscape.
• What is the return of investment when it comes to AI-powered personalisation in terms of superior customer experiences, engagement and brand revenue?
• Examine real-world examples and case studies that highlight successful AI implementations in consumer brands, demonstrating measurable value and outcomes.
• From broad audience targeting (1 to many) to 1:1 hyper personalisation: How it can add value" and touches on recommendations?

Jim Edwards

Global Innovation Capabilities Leader
Kimberly-Clark

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• Integrating Disjointed Data Points and Breaking Down Silos: Utilizing Customer Data Platforms (CDPs) to unify data and eliminate internal silos for accurate personalization.
• Mapping the Customer Journey: Overview of key touchpoints and the importance of consistent personalization across all interactions.
• Leveraging Automation and Real-Time Responses: How marketing automation and real-time data enable efficient, personalized customer experiences.
• Enhancing the Customer Proposition: Building cross-functional teams and selecting the right partners to strengthen data-driven personalization efforts and improve customer propositions.

Eszter Morvay

Head of Customer Data Platform
Aviva

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• One of the pillars of success of any personalization initiative is the scale and accuracy of customer journey data. Technology and Machine Learning (ML) have increased the breadth and depth of always-on customer journey data to drive personalization at scale. However, this is true only for industries with access to customer purchase data. Without access to deterministic customer purchase data, the business value of personalization is difficult to establish and is subject to many assumptions.
• This session will talk about how to harness passive consumer deterministic online behavioural data including sales to understand consumer journey data at scale. This will enable personalization at scale even in industries without access to customer sales data at an individual customer level. This will also enable the move from customer to consumer journeys which is relevant in any industry with repertoire purchase behaviour. This will enable integration of customer retention with customer share of wallet and with consumer acquisition strategies rather than being isolated.

Sunando Das

Global Head of Predictive Analytics
Unilever

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• Tailoring the Journey: Leveraging multiple interactions for personalized customer experiences and mapping key touchpoints.
• Boosting Customer Loyalty: Exploring the relationship between personalization efforts and enhanced customer loyalty metrics.
• Engaging Through Personalized Content and Advanced Data Strategies: Techniques for creating resonant content and leveraging collaborative teams and partner ecosystems for enhanced personalization.
• The Role of Marketing Automation and Data-Driven Personalization: Utilizing automation tools and diverse data sources to refine personalization efforts efficiently.
• How sophisticated personalization tactics lead to increased revenue per customer.

• What is personalisation?
• What are the pre-requisites for personalisation?
• When does it make sense for organisations to personalise experiences?
• Harnessing Customer Data for Personalisation: Employing analytics to tailor online customer journeys effectively.
• Personalising Complex Customer Journeys: Utilizing customer data to identify and address complexities in customer paths, enhancing navigation and satisfaction.
• Building meaningful experiences which creates loyal and long-lasting relationships: Using customer data to create deep, long-term customer loyalty, leading to repeated engagement.
• Exploring technologies and methodologies that utilize real-time data for dynamic adjustments to personalisation strategies.

Jivesh Juneja

Customer Journey Director
Nissan Motor Corporation

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Aryan Aras

Global Customer Experience Lead
IKEA

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Billy Cheng

Senior Manager - Global Consumer Data & CRM Analytics
Costa Coffee

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• Personalised Digital Experiences: Leveraging AI and changing search behaviors to tailor customer acquisition strategies.
• AI-Driven Customer Engagement: Utilizing chatbots and AI tools for real-time, personalized interactions across digital channels.
• Data-Driven Growth Hacking: Implementing data analytics to create highly targeted and effective marketing campaigns.
• Lifecycle Personalization: Enhancing customer satisfaction and loyalty with personalized experiences at every stage of the customer journey.
• Continuous Feedback Adaptation: Refining personalization strategies based on customer feedback to improve overall digital experiences.

Indul Hassan

Head of Engineering, Digital as a Channel
BT

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At Eon Next, it’s on us to make new energy work.

‘New Energy’ is an electricity grid which constantly balances

renewable electricity generation, storage and usage.

Personalisation is the way to make this work. Deepest understanding

of consumers will deliver experiences that balance convenience, practicality

and cost, by evolving the roles of efficiency technology (solar panels, batteries,

electric heating), energy tariff cost structures, software & automation, and

behaviour change.

Taking an example of charging an electric car at home. Households may

have the same car and annual mileage, but knowing different daily or weekly

mileage patterns, and if a customer has solar panels, could mean it’s better for

one customer to have a small cheaper off-peak time every day, or a longer

slightly more expensive off-peak time at weekends

Andy Sage

Head of Partnership Propositions
E.ON Next

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• Defining Meaningful Personalisation: What constitutes meaningful personalization across acquisition and retention phases? Exploring key metrics and indicators of success.
• What are the key technology capabilities needed to deliver personalisation at scale
• Role of Content Supply Chain in delivering personalisation at scale? Strategies for automating content personalization to maintain relevance and engagement across vast customer bases.
• Managing Multiple Audience Channels: How do large customer-facing brands handle diverse audience channels and content distribution? Best practices for ensuring consistent engagement.
• Role of measurement and importance of integrating insights to ensure consistent and effective personalisation across various customer touchpoints
• 
  

Varun Vashist

Head of Marketing Technology Portfolio & Transformation
Sky

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Anthony Cockburn

Product Director – Consumer Experience (Digital & Tech),
Haleon

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• Mapping the Customer Journey: Analysing the customer journey through key stages—pre-purchase, purchase, and post-purchase. Highlight the importance of consistent personalization across all interactions, particularly on delivery platforms.
• Data-Driven Personalization: Utilizing data from various sources such as order history, website analytics, and social media to refine personalization efforts, enhancing each stage of the customer journey.
• Engaging Through Personalized Content: Techniques for creating content that resonates personally with different customer segments throughout their ordering journey. Emphasize the importance of touchpoints like social media platforms and advertising in raising awareness and engaging with customers.

Eli Abramovitch

Head of Engineering, Personalization & Core Experience
Deliveroo

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• Overall goal of personalisation is to create a more relevant, engaging, and quality experience for the customer. But we need to narrow that overall goal into a more defined objective
• Overcoming challenges with understanding our customer and setting our Personalisation strategy; developing a plan for accomplishing our Personalisation goal
• Building a MarTech stack that will support our strategy – customer consent, Customer Data Platforms (CDP), marketing automations, Customer Relationship Management (CRM) Systems, AI and Machine Learning

Katy Baker

Product Owner, Personalisation
Victoria's Secret

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• Collecting and Labeling Feedback: Gather and categorize customer feedback to understand their values and preferences, integrating this data with AI for deeper insights.
• AI-Driven Segmentation: Use AI to quantify psychological values and segment customers, creating personalized offers and engaging content that resonate with different groups.
• Experimenting with Personalization: Implement A/B and multivariate testing to refine personalization strategies, continuously improving based on results and evolving customer preferences.
• Applying Martech Systems: Integrate martech tools to streamline personalization efforts, maximizing ROI through data-driven and automated marketing strategies.

Jad Freiha

Head of Analytics and Insights
Sweaty Betty

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• Building Resilient Strategies: Ensuring that personalization efforts remain robust against market disruptions and continue to deliver high ROI.
• Optimizing for ROI: Techniques for continually refining personalization tactics to maximize returns, including A/B testing and customer feedback loops.
• Anticipating Market Shifts: Adapting personalization strategies in response to changes in consumer behavior and privacy regulations.
• Success Stories: Sharing case studies from brands that have seen tangible improvements in revenue and loyalty as a result of their personalization strategies.