9 April

07:30 - 08:50

Registration & Morning Coffee

08:50 - 09:00

Conference Opening 

Casper Haring CEO ECU 

09:00 - 11:40


09:00 - 09:30

Personalizing the Shopping Journey: Case Studies of Data-Driven Success

  • Detailing Success Stories: Emphasize on innovative case studies where AI and machine learning have been pivotal in personalizing the online shopping experience.
  • Discussing Challenges Overcome: Focus on the specific challenges e-retailers face when implementing AI-driven personalization and the innovative solutions that have proven effective.
  • Exploring Impact on Sales: Examine how AI-driven personalization strategies directly impact online sales figures and customer retention

09:30 - 9:50

Revolutionizing E-commerce Search with AI-Driven Solutions

  • Enhancing Search Accuracy: Implementing AI and machine learning algorithms to improve search result relevance and accuracy on e-commerce platforms.
  • Personalizing Search Experiences: Utilizing user data to tailor search results, offering personalized product recommendations and enhancing user engagement.
  • Innovating with Voice and Visual Search: Exploring the integration of voice and visual search capabilities to offer intuitive and convenient search options for e-commerce customers.

9:50 - 10:10

Integrating Data Analytics in Localized eRetail Marketing

  • Utilizing Data for Regional Insights: Harnessing data analytics to gain deep insights into regional consumer behaviors and preferences, guiding localized e-commerce marketing strategies.
  • Optimizing Localized Campaigns: Implementing data-driven approaches to tailor and optimize marketing campaigns for specific local markets, enhancing relevance and effectiveness.
  • Measuring Local Engagement: Employing sophisticated data tracking and analysis tools to measure the impact and ROI of localized digital marketing efforts in e-commerce.

10:10 - 10:40

Maximizing eRetail Efficiency through Marketplace Data Insights

  • Analyzing Marketplace Dynamics: Utilizing data analytics to understand consumer trends and seller performance on the e-commerce platform.
  • Optimizing Product Listings: Implementing data-driven strategies to enhance product visibility and attractiveness in a competitive marketplace.
  • Personalizing Customer Experiences: Leveraging customer data to create tailored shopping experiences, boosting engagement and conversion rates on the e-commerce platform.

10:40 - 11:00

Business networking over Coffee

11:00 - 11:30

Leveraging Big Data for Smarter eRetail Operations"

  • Harnessing Big Data: Discussing how big data can be used to optimize e-commerce operations, from logistics to customer experience.
  • Integrating Data Analytics: Exploring the integration of analytics tools in eRetail for real-time decision-making and improved operational efficiency.
  • Balancing Automation and Human Insight: Addressing the importance of human oversight in interpreting big data analytics for more strategic decision-making in e-commerce.

11:30 - 11:50

 Leveraging CRM Data to Transform eRetail Strategies

  • Enhancing Customer Relationships: Utilizing CRM data to build stronger, more personalized connections with e-commerce customers.
  • Driving Sales with Data-Driven Insights: Analyzing customer data to identify sales opportunities and optimize marketing strategies in e-commerce.
  • Streamlining Operations with Integrated CRM Solutions: Demonstrating how integrated CRM systems can improve operational efficiency and customer service in e-commerce environments.

 11:50 - 15:30


11:50 - 12:10

Driving eRetail Growth with AI-Powered Personalization

  • Implementing Personalization at Scale: Leveraging AI and machine learning to provide real-time, personalized experiences to e-commerce customers.
  • Enhancing User Engagement: Utilizing data-driven insights to customize content, recommendations, and offers, increasing engagement and customer loyalty.
  • Measuring Personalization Impact: Employing advanced analytics to track the effectiveness of personalized strategies and continuously optimize e-commerce experiences.

12:10 - 12:30

Analyzing Customer Behavior through Advanced Analytics

  • Investigating Behavioral Analytics: Utilizing advanced analytics tools to gain a deeper understanding of customer behaviors and preferences.
  • Forecasting Trends with Predictive Analytics: Exploring the capabilities of predictive analytics in anticipating customer needs and market changes.
  • Segmenting Audiences for Targeted Engagement: Applying analytics-driven insights to segment customers effectively for personalized marketing strategies.

 12:30 - 13:00

Experimenting for Enhanced eRetail Performance

  • Conducting A/B Tests and Controlled Experiments: Examining the role of A/B testing and controlled experiments in refining e-commerce strategies.
  • Interpreting Experimentation Data for Optimization: Analyzing data from experiments to inform and guide e-commerce enhancements.
  • Balancing User Experience with Innovative Features: Striking a balance between innovative feature deployment and maintaining optimal user experience.

13:00 - 14:00

Business networking over Lunch

 14:00 - 14:30

 Governancing Data and Ensuring Compliance in eRetail

  • Adhering to Data Privacy and Regulations: Strategizing to stay compliant with evolving global data privacy laws in e-commerce.
  • Implementing Effective Data Governance Practices: Exploring robust data governance frameworks to ensure data accuracy and security.
  • Fostering Trust through Transparent Data Practices: Emphasizing the role of transparency in data handling to build and sustain consumer trust

14:30 - 14:50

Transforming eRetail: Leveraging Customer Data Platforms for Enhanced Engagement

  • Unifying Diverse Data Sources: Discussing strategies for integrating varied customer data to create a comprehensive and actionable customer profile.
  • Activating Real-Time Insights: Demonstrating the use of real-time data to tailor marketing efforts and boost customer engagement in e-commerce.
  • Ensuring Data Compliance: Addressing the critical role of data privacy and security in e-commerce, highlighting best practices for regulatory adherence.

14:50 - 15:10

 Enhancing eRetail Effectiveness: Advanced Data Analytics and Digital Marketing Strategies

  • Utilizing Advanced AI for Market Trends Analysis: Delving into how cutting-edge artificial intelligence can predict market trends and consumer behaviors in the e-commerce sector.
  • Streamlining Digital Advertising Campaigns: Showcasing strategies for targeted and efficient digital advertising to boost e-commerce engagement and sales.
  • Optimizing User Experience Through Analytics: Exploring the impact of sophisticated analytics in understanding and improving the e-commerce customer journey for enhanced conversion rates

15:10 - 15:30

Revolutionizing eRetail with Strategic Media and Marketing Insights

  • Crafting Data-Driven Media Strategies: Delving into the creation of effective media plans based on comprehensive data analysis to maximize eRetail impact.
  • Enhancing Customer Engagement through Technology: Exploring innovative technological approaches to boost customer interaction and loyalty in e-commerce.
  • Integrating Marketing Insights for Business Growth: Demonstrating how to leverage marketing insights to drive business growth and consumer satisfaction in the digital retail space.

 15:30 - 18:00


15:30 - 16:00

Elevating AI Maturity in eRetail

  • Assessing Data Infrastructure: Evaluating current levels of data management sophistication and identifying barriers to AI deployment.
  • Ethical AI Utilization: Discussing the ethical aspects and responsible use of AI in eRetail.
  • Enhancing AI Readiness: Addressing the gap between data richness and AI maturity, focusing on the necessary steps to enhance organizational readiness for AI implementation.

16:00 - 16:30

Optimizing Operations with Generative AI

  • Improving Data Quality Assurance: Exploring AI-driven solutions for automated data quality checks and predictive analytics in eRetail.
  • Preempting Data Anomalies: Utilizing machine learning algorithms to identify and correct data inconsistencies before they impact operations.
  • Predicting Retail Trends: Discussing the use of AI in forecasting market trends and customer behaviors for proactive business strategies.

 16:30 - 17:00

Coffee Break

 17:00 - 17:30

Integrating AI-Generated Data for Enhanced Applications"

  • Balancing Personalization and Privacy: Emphasizing the importance of balancing personalization efforts with privacy and data protection in AI-integrated applications.
  • Ensuring Data Quality and Security: Delving into the challenges of maintaining data integrity and security standards in AI-integrated applications.
  • Facilitating Rapid Application Development: Discussing the role of AI in accelerating the development and deployment of e-commerce applications.

17:30 - 18:00

Navigating Data Management Complexities in AI Implementation

  • Streamlining Data Cleaning Processes: Addressing the challenges and costs associated with preparing accurate data for AI models.
  • Achieving Effective Data Integration: Exploring solutions for integrating data from varied systems and ensuring cohesive data governance.
  • Breaking Down Functional Silos: Tackling the issue of data-rich but insights-poor environments in retail, focusing on enterprise-wide data utilization for informed decision-making.

18:00 - 19:00


19:00 - 20:00

Evening Gala & Retailer of the Year Ceremony

20:00 - 0:00

After Party, Live Music, Networking, Drinks