The backbone of Bonamy Finch is our industry-leading expertise in advanced analytics. We provide analytical services to research and insight agencies from all over the globe, as well as working directly with some of the world’s leading brands. Employing the complete arsenal of mainstream analytical techniques – and some special ones we have developed ourselves – our team will apply all of their experience to uncover the hidden stories in your data and explain them in a clear, concise and compelling way.
An impressive toolbox of modern statistical methods
It’s a catch-all term – just not a very catchy one. Multivariate techniques refer to those statistical approaches that explore in some way what’s going on between two or more variables (MULTIple VARIAbles – see what they did there?). There are a huge number of such techniques, each with different applications, suited to answering different types of research questions. They’re the tools of our trade, so we’ve highlighted a few of the different technique areas below.
To understand which customers to target with what propositions, you need to segment your market. Bonamy Finch is a world leader in segmentation analysis (also known as cluster analysis) and you may well have seen us present our thinking at ESOMAR, MRS and CIM industry events. We’ve conducted 900+ segmentations since 2005 and continuously develop and refine our techniques and approach..
Key Driver Analysis
We use Key Driver Analysis to establish the relative influence of an attribute or attributes in a causal relationship, such as what brand characteristics drive the market, or what drives purchase intention in a particular category. We tailor our approach to Key Driver Analysis from a range of multivariate techniques such as Kruskal’s relative importance, logistic regression, Structural Equation Modelling, CHAID and canonical correlations, depending on your objectives, type of data and how the results will be used.
Originally designed to identify the number of users reached by a media campaign, Total Unduplicated Reach and Frequency or TURF analysis is now used to take into account the ‘overlap’ in appeal of different features. If two products appeal to similar consumers, there is limited justification for launching both.
Brand Fit & Positioning
To understand which brands meet the needs of different segments, we apply Brand Fit Analysis, augmented with a category-based SWOT analysis. To determine relative positioning, we use our proprietary OCEAN~Brandscape™ brand personality framework to identify brands emotional positions in a given category and across the global brand landscape.
Conjoint Analysis is a powerful statistical technique to help understand what combination of a limited number of attributes or features is most influential in the consumer’s decision-making process. Respondents might be asked to trade off, or ‘consider jointly’, two similar products with different features. Their choices can then be modelled to understand the relative importance of each feature, and determine what the optimum product mix might be.
In a nutshell, pricing analysis determines the impact of price on financial performance. We use a range of techniques including Choice Based Conjoint, Price Sensitivity Measures, Gabor Granger, Brand/Price Trade-off, Brand Equity Modelling and Price Premium Analysis. Our proprietary simulation tool enables us to run ‘what if’ modelling across multiple subgroups to estimate profit in various hypothetical scenarios.
In a world where we can’t have everything, Maximum Difference Scaling, or MaxDiff, is used to identify the best of many options (e.g. brands, packaging, features, performance attributes or benefit statements). Respondents choose the most and least important (or appealing) from a single list of items at a time, in various combinations. MaxDiff analysis provides a transparent measure of absolute and relative importance or appeal for each component.