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Advanced Analytical Market Research Techniques - BDRC Jones Donald

Advanced Analytics

Advanced Analytics

Advanced Analytics is a core part of BDRC Jones Donald's business.  We have a portfolio of approaches that are used to translate quantitative data into meaningful blueprints for clients both at an operational and a truly strategic level.

Our approach
The team’s expertise can be applied to a wide range of scenarios from understanding pricing, to assisting in the developing products and services. Research will determine the optimum balance between different attributes, such as product features and price, whilst segmenting customer groups to identify the most profitable customer types.


We use a full range of research techniques to help companies understand their optimum price points and use modelling techniques to show the likely impact of changes to price. Techniques include TURF analysis, CHAID, Factor Analysis, SIMALTO, van Westendorp Price Sensitivity Meter and the Gabor-Granger pricing technique. 

Understanding the factors that make up customers’ decisions to purchase a product or service is a complex process, especially as consumers may be unable to evaluate all of their purchase decisions effectively. We help companies to understand the decision making process by using trade-off techniques to simulate the evaluation process. Our full range of techniques includes conjoint analysis, discrete choice modelling, maximum difference scaling (Max Diff), paired comparisons and brand price trade-off (BPTO). We can also build client-friendly simulation models to show take up of different products and services and at what price,which can be an aid to setting strategies.
 
Segmentation of markets into different customer types enables companies to understand patterns within their market and the best way to target their products and marketing to meet customers’ needs.  Using k-means segmentation, hierarchical segmentation, CHAID and integrated ensemble tools, we help to identify the customer groups which are most valuable to your organisation and how to maximise the profitability of these groups. 
Key driver analysis allows organisations to understand which factors drive customer satisfaction by using underlying relationships within the data to highlight the factors that have the greatest impact upon satisfaction. Using techniques such as regression models, correlation analysis and structured equation models (SEM), we identify areas of weak performance and recommend effective allocation of resources in order to maximise customer satisfaction.  We can build models to show the degree of change required in identified areas to achieve target levels of overall satisfaction.