Sarah Norman

Predictive data modelling has the potential to improve customer satisfaction, reduce customer churn and streamline decision making processes. By unlocking key insights into customer behaviour patterns, predictive modelling allows businesses to strategize and plan for future trends while remaining agile.

Predictive models, however, are only as good as the data on which they are based. The key to getting the most value out of predictive modelling is understanding its limitations and being wary of overreliance on models. Even the most sophisticated models with the best and most complete data will not necessarily be useful without a human component to contextualise analysis and weave meaningful stories from the data.

In this session, we are joined by Sarah Evangeline Norman, Enterprise Team Lead at TikTok and Senior Fellow at the Wharton School as she walks us through the best practices for predictive modelling and shares her approach to data storytelling based on customer insights and stakeholder needs.

Join this session to learn more about:

• Best practices for building impactful predictive data models to galvanise decision-making and unlock key customer insights.
• The limitations of predictive modelling and the importance of the human touch.
• Data storytelling based on stakeholder needs: engaging your audience and empowering teams to stay ahead of the curve.