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With customer data growing in complexity and volume, how can organizations deliver personalized, predictive experiences while remaining compliant across an increasingly fragmented regulatory landscape?
From implementing deterministic and probabilistic models to navigating evolving privacy laws like GDPR and CCPA, learn how to leverage real-time data architecture and AI to shape adaptive customer journeys.
What you'll learn:
Building flexible architectures to handle state-specific privacy regulations
Using probabilistic analytics to respect customer anonymity while delivering value
Reimagining customer data platforms beyond the hype to power real-time decisioning
Harnessing generative AI for meaningful engagement through email, push, and SMS
Designing gamified, non-intrusive digital experiences that balance business goals with customer preferences
Whether you're just starting your customer analytics journey or scaling your AI and data science capabilities, this session will equip you with practical insights on how to future-proof your personalization strategies without compromising trust.
As finance teams across industries modernize, many are discovering that the real value of AI and predictive analytics isn't just in sharper forecasts—it's in transforming how people work. But turning data into decisions at scale requires more than deploying tools. It takes a shift in mindset, structure, and culture.
Join us for an intimate fireside chat with enterprise finance and analytics leaders who are leading this charge. We’ll dig into the real stories behind AI transformation at scale—from building data marketplaces to rethinking forecasting across hundreds of contributors.
Together, we’ll explore:
How predictive models and GPT-powered tools are streamlining a 400-person forecasting process
Why a self-service data marketplace built with Power BI and Copilot is fueling faster, smarter decisions for 2,500+ analysts
Where organizations get stuck—from tooling limitations to gaps in data literacy and the people side of change
What meaningful return on analytics looks like—and how to measure impact beyond traditional ROI
Whether you’re a CX leader, tech executive, or finance strategist, this conversation will offer a grounded roadmap for building scalable, human-centered analytics across your enterprise.
Please check your 1:1 personalized itinerary located under "My Meetings" in the mobile app to see what's happening now.
With the growing adoption of voice assistants and visual search technologies, businesses are increasingly analyzing customer interactions with these cutting-edge interfaces to enhance the user experience. This session will explore how voice and visual analytics can optimize search and discovery processes, streamline customer interactions, and personalize experiences by tapping into the power of voice and image-driven data.
Effective workforce management is critical to delivering an exceptional customer experience. By analyzing data on call volumes, peak times, and agent performance, businesses can optimize staffing levels to ensure that contact centers are properly equipped to handle demand. This session will explore how leveraging analytics can improve response times, reduce customer wait times, and ultimately drive more efficient, customer-friendly operations.
High-quality data is the backbone of any data-driven strategy, directly influencing CX. This session will explore the critical importance of data quality, focusing on accuracy, completeness, reliability, and consistency. We will discuss how businesses can improve data quality through validation, cleansing, and ongoing maintenance processes, ensuring that data can be trusted to support better decision-making and drive effective customer insights.
Understanding Data Quality: Key attributes of high-quality data and why they matter for CX.
Data Validation & Cleansing: Best practices for ensuring your data is accurate and complete.
Continuous Data Maintenance: The importance of regular data checks and updates to maintain reliability.
Improving CX with Quality Data: How quality data leads to better insights, more informed decisions, and stronger customer experiences.
In an era of accelerating digital transformation, organizations are embracing AI, advanced analytics, and automation to unlock customer insights — but not without risk. Sensitive customer data and proprietary models require robust governance, compliance with global privacy regulations, and a firm cybersecurity backbone.
This session explores how industry leaders are leveraging secure, compliant data strategies while enabling organizational change through employee-driven adoption. Learn how to embed cybersecurity principles into the fabric of your analytics strategy, run cross-functional workshops to align teams, and use internal champions to drive safe experimentation with emerging tech.
Walk away with actionable insights on:
Building a secure data culture without stifling innovation
Operationalizing data governance and privacy by design
Leading employee workshops that demystify AI, analytics, and cybersecurity risks
Scaling new technology rollouts by embedding trust, transparency, and accountability
Whether you’re rolling out customer segmentation tools, generative AI assistants, or real-time personalization platforms, this session will help you navigate the evolving landscape of customer analytics with resilience and confidence.
As AI, automation, and advanced analytics redefine customer intelligence, organizations must navigate an evolving landscape of real-time insights, hyper-personalization, and predictive modeling. This session explores the future of customer analytics in an era where emerging technologies are unlocking deeper customer understanding while raising critical questions about data ethics, privacy, and trust.
Key discussion points include:
How AI and machine learning are shaping next-generation customer analytics
The role of automation in driving efficiency and personalization at scale
Striking the balance between data-driven insights and evolving privacy regulations
The impact of new and emerging technologies on customer engagement strategies
Best practices for building a responsible, future-proof customer analytics strategy
Join industry leaders as we explore how businesses can harness AI-driven analytics while maintaining customer trust in a rapidly changing digital landscape.
Customer expectations are shifting faster than ever, demanding businesses not just react to change—but anticipate it. Yet, while organizations collect vast amounts of data, many struggle to translate insights into meaningful action. The true power of analytics isn’t in complex models alone—it’s in how data is communicated, applied, and used to shape customer journeys. In this session, industry leaders will explore how to bridge the gap between insights and impact, using data to drive innovation, optimize experiences, and fuel business growth. Key Takeaways: • From Data to Strategy: Turn customer insights into a dynamic roadmap for innovation and competitive advantage.
• Making Analytics Actionable: Tailor insights for different audiences, ensuring accessibility and alignment with business goals.
• Journey Mapping with Impact: Identify and eliminate friction points to craft seamless, high-value customer experiences.
• Predictive Insights for Growth: Shift from reactive metrics to anticipating customer needs and behaviors.
• Pilot, Iterate, Scale: Leverage pilot programs to test and refine data-driven strategies before full-scale rollouts.
Join us to learn how leading organizations are harnessing the power of data—not just to understand customers but to transform their experiences and build lasting loyalty.
Craft Texas cocktails like Ranch Water, Texas Mule (with Deep Eddy vodka), and mezcal margaritas, plus Shiner Bock & Lone Star beers.