Using statistical techniques in conjunction with both Excel and specialist statistical/econometric software (@Risk, SAS, SPSS & EVIEWS) to model the relationship between different variables for forecasting purposes and other key techniques of marketing analytics such as conjoint analysis and cluster/segmentation analysis
Multivariate statistical analysis including market response graphs, pricing elasticity analysis: Using regression analysis with variations such as logistic regression to determine the influence of independent factors in determining particular variables such as sales, market share
Econometric Analysis: Multivariate statistical analysis with particular reference to time series, taking account of auto correlation (the influence of one period on the next) , stochastic variance (random variances), volatility and co-integration (the relationship between variables and their simultaneous influence on each other)
Conjoint Analysis: The statistical technique of using customer surveys to evaluate the relative importance of different attributes are in decision making by consumers, most frequently relating to willingness to buy. This is frequently used to determine price elasticity
Cluster Analysis/Segmentation: Analysing a large number of data points (market research questions) social and demographic details on a large population in order to split the population/market into clearly identifiable segments based on common attributes
Data Visualisation: Producing detailed numerical analysis is often not enough. For the analysis carry weight producing a strong graphical presentation can make a great difference. Whether this is through using the graphing functionality in Excel and through add-ins like Power Map, or by using specialist Data Visualisation software such as Tableau, we can produce powerful visualisations to accompany to accompany our data analysis.