Advanced analytics & data science

With data science we can go deeper to unlock the value of your data. Using a range of advanced analytical tools and technologies, our team delivers successful research executions. Experts in driving business-relevant insights and providing lasting solutions, we’ll adapt our approach to suit your needs.

Our approach

We can give you the what, the how and the why. From sample and weighting, to data processing, to statistics, to management consulting and scripting, and everything in between. Our broad approach enables us to provide a well-rounded view to help you make better decisions.

By bringing clarity to research findings, we add real value; covering the full spectrum of data management. Combining data sets from various internal and external sources, we create predictive models using R, Python and other software to better signal trends and their implications. Our range of analytical tools and technologies provide a full array of data outputs and complex analysis.

Analytical techniques

Our in-house capabilities enable us to offer a broad range of techniques and benefits

Behavioural economics

Implicit bias testing and implicit preference testing will help you test emotional associations with a brand or concept to uncover potentially unknown biases.

Conjoint

Choice-based conjoint is a powerful tool to understand how consumer’s choices are affected by product features and pricing.

Correspondence mapping

Need to show how closely brands and variables are related to each other? By providing a visual representation of brand territory, we help you visualise relationships between groups, objects, individuals, and variables.

Expectancy analysis

Create a level playing field by identifying where your brand under or over performs against competitors.

Forecasting

Forecast your sales volume in turbulent or opaque markets, facilitating your sales planning, resource allocation and purchase decision-making.

Key Driver analysis

Using a wide range of regression analyses measure and understand the underlying reasons that drive KPIs, to improve processes and maximise performance.

Market modelling

Analyse key drivers for sales and market share performance. Model pricing scenarios. Estimate the size of adjacent industries and new opportunities.

Max-diff trade off

Choice modelling, opportunity sizing, cannibalization, and strategic game theory. Identify preference/importance scores for multiple items from brand preferences and product features to advertising claims.

Pricing analysis

Quantify and understand price elasticity and price optimisation to determine the optimum combination of customer perceived value and price. Complement with views on competitive and substitute pricing models and positions.

Purchase decision making

Map and prioritise decision makers, influencers and purchase drivers in complex purchase funnels. Enable sales teams to target the right stakeholders with the right messages and propositions.