Access, analysis, management or storage of data provided on or off-site. We work with many kinds of data including clinical, financial, survey, longitudinal, or supermarket. Our data manipulation is done with many kinds of modern software. Our expert staff provide consultative and management services for research such as study design, sample composition, planning and survey research. We offer expert staff for on or off-site applications programming services.

Data Analysis

The statistical and marketing technologies used by our company are based on the nature of the data. Our Company is an information enterprise. The company seeks to maximize the benefits of data to your organization by managing and manipulating data for the purpose of producing information. This information then can be used for educational, decision-making or strategic purposes. Using graphical representation, we can for example, show the relationships between attribute importance and customer satisfaction.

Segmentation

Our segmentation techniques include cluster analysis, logistic regression, latent class, and dynamic segmentation. Clusters can be characterized in terms of demographic or lifestyle variables, product consumption, and company size. Segments can help identify markets and evaluate their potentials as targets for strategic marketing. It can provide insights into how to position your products, opportunities for new products, targeting sales efforts, and distribution channels to use.

Discrete Choice/Conjoint Analysis

Our Conjoint analysis includes straight and choice based. We use both classical and Bayesian approaches. Using hierarchical bayes, for example we can obtain respondent level parameter estimates from choice data, which can be used for further analysis, for example segmentation. Conjoint analysis is used to investigate how consumers trade off product attributes when making a purchase decision.

Perceptual Mapping

A product map is a graphical representation of the ways people perceive the product in terms of its underlying attributes, as well as an aid to understanding their preferences. Among other things we do multidimensional scaling (MDS), multidimensional preference analysis, preference mapping, correspondence analysis, and canonical discriminant analysis to generate displays from data matrices. These methods are used to investigate relationships among products as well as individual differences in preferences for those products.

Concept Screening and Optimization

We use Q, TURF and Shapley value analysis to screen, rank and optimize concept/product lines. These techniques are used to optimize product lines and ensure discrimination. For multiple product lines, they are used to assess the strength of each individual item in the line to maximize reach and minimize overlap. These procedures identify those items which appeal to the largest combined audience.

Interpretation and Summary

Interpretation leads to understanding the position of your product in the market. We will be able to identify your customers, your competition and determine what kinds of consumers are buying your products. Plots from different methods may suggest how to reposition your product to appeal to a broader audience. They may also suggest new groups of customers to target.


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