Thoughtful, educated, questioning, rigorous


Deep skills, domain experience & diverse perspectives

A successful combination of data science, analytics and marketing strategy expertise, 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
  • Strategists
  • Technologists
  • Project Managers
  • Economists
  • Statisticians
  • Engineers
  • Operations Director

Our consulting service provides project leadership and 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 have worked in the following sectors:

  • Financial Services
  • Travel
  • Membership
  • Retail
  • FMCG
  • Utility
  • Charity

We benefit from our geographical location allowing us to access some of the world’s best thinkers on model design and data manipulation. Many members of our team are University of Cambridge alumni, providing close links to academic collaboration and innovation. We also actively participate in the local data and modelling network meetings for the exchange of perspectives and innovation.

Consumer Behaviour Models

Our team of Quants develop and optimise consumer behaviour models to uncover your competitive advantage.  We build consumer behaviour models from company’s 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 statistical analyses of markets for predictive modelling and consumer control group ‘test and learn’ disciplines for feedback to the models.

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 are increasingly deploying neural network and deep-learning tools to produce alternative analysts conventional stats.

We have experience in applying different and relevant model types to many industries or sectors. We also have a fast-growing creative data source research function to help us enquire beyond the popular or common data sources in each market and find different perspectives.

For instance, the Consumer Packaged Goods industry is often focused on econometric modelling, albeit it largely, offline using industry benchmark data from proprietary, established providers. When overlaid or triangulated with other data points, so fresh insight can be found. Similarly, eCommerce transactional retailers, travel and utility industries are concerned with ‘attribution models’ from common technology vendors and these are often too rigid or prescribed in
method to provide hoped-for utility. In B2B sectors, we often deploy propensity models to prioritise sales contact activity.

Common categories of marketing models we work on are:

  • Econometric
  • Attribution
  • Segmentation
  • Propensity
  • Conversion Rate Optimisation (CRO)

Analysis Capability

Many of our clients have Business Intelligence teams and data scientists amongst their customer insight teams, but they use us for rapid deployments or addressing discrete challenges. Equally, some clients chose to delegate the provision of data-driven competitive advantage to us as a trusted partner.

In both situations, we focus on productivity in optimising budgets and reducing waste. Our pre-occupation with productivity from the agile method, means that we deploy our people where and when their skills are needed, so you are not delayed or paying for expensive people to ‘sit on the bench’ or awaiting client feedback.

We will save your company a significant amount of time (or agency costs) in a week, using our semi-automated process to:

  • Prepare the data
  • Analyse it
  • Find insights
  • Recommend actions against your KPIs

Using our analysts recommendations, we will accelerate your data-driven decision making to a state of persistent testing.

We aim to provide knowledge transfer in most areas where we can help clients to become more data-driven in their decision making by driving down the Test & Learn cycle time to create iterative incremental optimisations more frequently.

Most of our models and underlying technology infrastructure are ‘always on’ which means that a great deal of time in data preparation and engineering is saved in the provision of our services.