Advanced Analytics Innovation Symposium

ADAN - the Advanced Analytics Network - aims to help identify, develop and disseminate research industry best practice in the general area of advanced analytics.

This covers mainstream multivariate approaches such as conjoint and regression, through to more recently adopted techniques such as random forests and cluster ensemble analysis. We also aim to lead the way within the research industry in identifying optimum approaches for analysing multiple source data.

In this inaugural event, a range of speakers will present four short papers that each demonstrate an innovative application or development of multivariate analytical techniques (shown specifically in relation to research data).

The themes of the presentations are:

• Applying Bayesian analysis to model main and interaction effects in drivers of customer satisfaction: Adele Gritten and Graham Williams, LRW Europe
• Exploring Real-time Experience Brand Tracking data using linear mixed effects regression
  Shane Baxendale, Cranfield School of Management and Fiona Blades, MESH
• Using a portfolio of techniques (including choice-based conjoint) to improve accuracy in product volume estimation within markets with changing price scenarios
  Soumya Mukhopadhyay and Sreeram Sreenivasan
• Using regression modelling on multiple source data to generate “space elasticity curves” – to help show retailers how to maximise sales from their store space
  Kalle Backlund, Nepa UK