We build consumer behaviour models from corporations’ internal, partner and public data sources, sometimes so-called ‘big data’ and frequently a mixture of smaller, more structured data.
With different layers of data sources, we create insight and competitive advantage for our clients, often by testing against predictive models, whether from micro insight for budget optimisation or macro for consumer trend observations.
We sample from the best academic economic thinking and alternative perspectives on consumer prediction models. We apply it to common market statistical analysis and predictive modelling for consumer control group ‘test and learn’ disciplines.
We have experience in applying different model types for more relevant domain and industrial sectors. For instance, the Consumer Packaged Goods industry is often focused on econometric modelling, albeit it largely, offline. Alternatively, the eCommerce transactional retailers, travel and utility industries are concerned with ‘attribution models’, whilst in B2B, we often deploy propensity models to prioritise sales contact activity.
We continue to test our belief that a small raft of models trumps one or two algorithms in predicting scenario planning, despite additional complexity brought to projects.
We focus on the exchange of ideas and different perspectives between experienced mathematicians and market strategists; a combination that delivers our clients vital competitive advantage repeatedly. We encourage members of our team to bring fresh progressive perspectives to model building. Our team consists of…
- Data Analysts
- Project Managers
- Operations Director
Our industry domain experts have experience in media buying, CRM, social media network analyses, consumer acquisition and retention strategy. Typically, they have a minimum of 10 years experience in the field and C-suite advisory skills.
We benefit from our geographical location allowing us to access some of the world’s best thinkers on model design and data manipulation. Members of our team are University of Cambridge alumni, providing close links to industry collaboration. We also actively participate in the local data and modelling network meetings for the exchange of perspectives and innovation.