AI and machine learning (ML) can help us understand consumers on a deeper level quantitatively, making time travel possible. How? We can use them to go back and collect data from the past, even when no survey may have been done.  

Join Bradley Taylor for a practical overview of the usefulness of AI/ML in transforming unstructured data into quantitative data - and what this might mean for traditional market research methods. When it comes to analysing large datasets (one million or over data points), there are also several new modelling AI/ML techniques, and these are particularly useful when resources are limited. Learn how the innovation toolset for research is changing – allowing us to hear what consumers desire, unprompted and quantitatively. 

What you’ll learn: 

  • How using AI/ML to transform unstructured data into quantitative data is a way to collect data from the past 
  • How segmentations are changing from limited, prompted attributes to unscripted, consumer-led attributes which can produce superior customer segments based on self-stated behaviours and attitudes 
  • An understanding of the new modelling AI/ML techniques for analysing large datasets 



The Old Trading House, 15 Northburgh Street,London,EC1V 0JR

Bradley Taylor is Owner, GITR Innovation, and Senior Strategist, Converseon. He has over 20 years’ experience in market research and analytics and has pioneered using multiple data sources and different disciplines to understand the consumer’s mind and forecast future outcomes. This work has helped a number of Fortune 500 companies. Recently Bradley co-invented GfKnewron as the Global VP of Product and Global Head of R&D for GfK. He now operates his own consultancy which specialises in bring the latest in AI to market research. 

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