Marketing Science Solutions
At ORC-NW, we go above and beyond simply analyzing survey data and reporting the results. We merge our clients’ marketing data with the results of our custom research to provide actionable insights and recommendations. No matter the place of your product or service in its life cycle, our Marketing Science Solutions can assist your managers in making sound, fact-based marketing decisions. Our experienced team of analysts and marketing consultants provide results from highly complex statistical models in understandable and useful ways.
Product Development
In addition to the idea generation and idea screening offered by our qualitative research solutions, Marketing Science Solutions can be used to make fact-based decisions about price, product/service attributes, distribution strategy, and market projections. A commonly-used tool to achieve these results is conjoint analysis. Our current system for this type of analysis is provided by Sawtooth Technologies and offers many different types of conjoint designs and utility estimation features, including Adaptive Conjoint Analysis, Choice-Based Conjoint, and Hierarchical Bayes Estimation.
Segmentation
Our Marketing Science Solutions offer many multivariate analytic tools for segmentation of the marketplace. Some of these include:
- Correspondence Analysis - determine optimal demographic segments
- Cluster Analysis - determine attitudinal / perceptual segments and compare with current segments
- Discriminant Analysis - determine which product / service attributes differentiate market segments
Clients often use these tools to determine competitive points between segments. For example, the Marketing Science Solutions could suggest clear competitive segmentation of the two primary markets (Pacific and New England) – Competition in the Pacific Market focuses on providing quality and convenience, while the New England market competes on price and value.
Example of using discriminant analysis to determine points of competition
Example of using correspondence analysis to identify target age segments
Example of using correspondence analysis to segment the market by age and income
Positioning and Differentiation
Brand Managers spend a lot of effort and financial resources to align selected attributes with their products and services. The Marketing Science Solutions of Northwest Research Group can be used to analyze the effectiveness of these positioning efforts through the use of perceptual maps.
Perceptual maps are a common tool and offer an easy-to-understand summary of the brand attributes and positioning, both for the client’s brand as well as its primary competitors. The analysis presented in the perceptual map below indicates that the market associates ‘Our Brand’ with price and value while one competitor is associated with quality and service and another is associated with location and convenience.
Example of using a perceptual map to evaluate brand position
Market Response Models
The effect of advertising on brand awareness is not immediate. Often times, managers are interested in determining the amount of time required from the implementation of an advertising campaign to the observed increase in brand awareness in the market as well as the duration of the increase. Our Marketing Science Solutions use Transfer Function Modeling to deliver actionable results. Through a custom research design, we determine a consistent measure of brand awareness in the market. When this data is paired with the brand’s advertising / marketing expenditure data, the result is a powerful and highly-useful tool in evaluating advertising penetration and effectiveness.
Perceptual Analysis
Our Marketing Science Solutions are frequently used to analyze data concerning attribute and brand perception of our clients and their primary competitors. In doing so, varying statistical techniques can be used, including ANOVA, MANOVA, ANCOVA, and regression modeling. ANOVA and MANOVA can be used to determine if a brand is perceived differently or similarly between segments and demographic groups. ANCOVA strengthens these tools by incorporating sales and market share data to achieve the perceptual results, for example. Regression modeling is useful in determining which attributes influence overall satisfaction (linear regression), how changes in perception of your brand affect the market’s decision and /or intent to purchase (logistic modeling), or the seasonality of product sales and how environmental fluctuations affect product sales (autocorrelative time-series modeling).