Advanced Analytics
In today’s world of an abundance of information we help client and brands navigate through the sea of data to identify what information is relevant, why it is relevant and how knowledge of this can transform into a competitive advantage.
Drawing on the vast expertise of our analysts our advanced analytics provides an opportunity lens for brands to identify hidden patterns, forecast trends, and make data-driven decisions which are strategically targeted, ahead of competition
Cluster Analysis
Cluster analysis is mainly used to understand the underlying psychographic, attitudinal and life-style impacts on market segments by grouping sets of similar respondents or subjects into “clusters.” Also a great tool for performing a segmentation analysis.
Factor Analysis
Factor analysis is mainly used to capture underlying product attribute relationships from the consumer view-point by condensing a large set of attributes into smaller, related sets also known as “factors”.
Conjoint Analysis
Conjoint analysis is effective in determining the relative importance of various drivers in consumer choice and behavior by asking the research respondents to make a series of product trade-offs to statistically reveal the relative importance of the product attributes, features, and even price.
Correspondence Analysis
Correspondence analysis is a very effective way of presenting a brand or corporate image in the competitive context by displaying the set of data in a two-dimensional graphical form to capture the relative proximity of image to relevant attributes.
Discriminant Analysis
Discriminant analysis is a way of statistically analysing categorical type data or responses (i.e. yes-no type responses) to make predictions or classify respondents. Such techniques also come in handy in certain types of segmentation analyses.
Price Sensitivity Analysis
This is a popular technique used to determine the degree of price sensitivity in market segments. In the mathematical sense, this technique is used to determine the change in demand of a product or service with every unit increase or decrease in price.
Automatic Interaction Detection (AID)
AID is an effective statistical tool to determine the predictive nature of market variables in order to prioritize key issues which segment the market and is also becoming an increasingly popular method to segment markets. Prediction is further enhanced with AID by also using Chi-squared testing (a.k.a CHAID) to allow for a wider range of survey data to be used in the analysis.
Chi Squared Analysis
The use of chi-square test results help to determine the degree of difference between various market groups or segments as well as to determine the validity of performance results in a statistically relevant way.
Multiple Regression
A multiple regression is a convenient analysis used to determine which variables are the best predictors of a particular subject (like sales volume) from a variety of relevant Independent variables in order to capture causal and non-causal relationships between market characteristics and consumer behaviour.
Econometric Modelling
Econometric modelling is applied to derive accurate empirical and future forecasting patterns in the market, considering a wider range of external societal and economic factors which invariably have an impact on the industry and consumer patterns