– What is the role of a CDP in unifying fragmented customer data into a cohesive profile?
– How can a robust CDP support the entire marketing lifecycle, from acquisition to loyalty?
– What are the measurable benefits of CDP implementation – for driving engagement and personalisation?
– How does leveraging first-party data through a CDP drive measurable engagement and personalisation?
– What are the challenges in implementing a CDP, and how is AI shaping its future?

– Why is first-party data now the key to building stronger customer relationships in a privacy-first world?
– What innovative ways can companies leverage first-party data for personalised marketing?
– How can brands maximise ROI through intelligent, data-driven decision-making?

– What are some of the most compelling use cases you’ve seen where predictive models transformed reactive operations into proactive strategies?
– How do you foster cross-functional collaboration between the data teams and business units to ensure predictive models are operationalizable?
– What are the major challenges you have encountered when doing this in your organization, how did you address them?
– How do you see the role of predictive analytics evolving in the next 3–5 years, especially with the growing use of GenAI and real-time data?
– How can we calculate back the predicted engagement trends into estimated monthly ROI (SGD)?

– How can businesses balance cutting-edge AI tools with responsible, privacy-centric practices?
– What are the best strategies for complying with global data privacy regulations without sacrificing personalisation?
– How does ethical AI drive long-term customer trust and loyalty?

– How is AI reshaping the way we collect and utilize customer data to deliver personalised experiences?
– As AI technology enables businesses to gather vast amounts of customer data, what strategies should organisations adopt to address privacy concerns while maintaining customer trust?
– How to strike this balance, and what advanced AI tools are driving real-time, hyper-personalised experiences in your industry?
– How B2B businesses navigate this balance and leverage AI to enhance real-time, hyper-personalised customer experiences?
– What are the biggest challenges in implementing AI for personalisation, and how can we overcome?
– How do you envision AI continuing to evolve and reshape customer experiences over the next five years?

– What are the best practices for mapping the ideal customer journeys across channels?
– How can real-time data enable immediate, impactful customer engagement?
– How does real-time decisioning create adaptive and personalised customer journeys?

– How can customer intelligence be leveraged to refine commercial strategies and ensure a more personalised and effective customer engagement approach?
– In what ways can organizations utilize customer data to identify emerging market trends and anticipate shifts in consumer behaviour that drive commercial growth?
– How can integrating customer insights into the commercial process help businesses increase customer lifetime value (CLV) while maintaining agility in fast-evolving markets?

– What are the new KPIs for evaluating the success of customer intelligence strategies?
– How can businesses effectively measure the impact of customer intelligence on engagement and revenue?
– What frameworks can be used to ensure continuous improvement and value generation from customer data?
– What would be an example of a well-designed AB testing experiment?

– The Rise of Generative AI for Personalisation
– Cookie-less future in Customer Intelligence
– Zero-party data and privacy first engagement