This project is the result of previous collaboration within the Learning Systems research platform. The suggested project has several subprojects, which all are based on the hypothesis that a generic model with individually adapted parameters can combine information about different marketing activities and use this to predict the outcome of the activities. The projects have the common denominator that they are characterized by the need for individually adapted models, since different products reacts differently to advertising. They are also affected by different parameters, e.g. weather or season. For these reasons Artificial Neural Networks will be used to optimize different aspects of prediction in connection to marketing efforts.
Members
- Lars Niklasson, Professor (Project Leader)
- Rikard König, PhD Student
- Mattias Strand, PhD