MMR Strategy Group conducts surveys and derives customer preferences using advanced statistical methods, such as conjoint, maximum difference scaling (MaxDiff), and discrete choice analysis.
These methodologies are powerful tools that help clients optimize the mix of features and prices for products and concepts. Conjoint and MaxDiff can help managers decide which features to include in a product or service. For example, product development for a vacuum cleaner might need to balance considerations of power, weight, and price.
MMR Strategy Group’s conjoint, MaxDiff, and discrete choice studies help clients make insightful decisions because they:
- Provide a common measuring system: This allows managers to directly compare different types and levels of features.
- Measure implied preference: These studies derive preference, rather than asking consumers to self-report the most important features of a product or service.
- Force choices between options: These methodologies present respondents with different bundles or combinations of features and different levels of each feature, and then ask respondents to indicate their preference for each bundle.
- Estimate market share or willingness to pay: Depending on the specific methodology used, respondents may be asked to indicate which features they prefer, their likelihood to purchase those features, and the price they might pay.
Our expertise includes:
- Traditional conjoint techniques.
- Maximum Difference Scaling (MaxDiff).
- TURF (Total Unduplicated Reach and Frequency), which measures the reach of different combinations of features.
- Latent Class Analysis, which segments consumers according to their interest in different types of features.
- Market simulation analysis, which predicts and compares market shares for different combinations of product features or prices.
Our experience with conjoint and discrete choice includes a wide variety of industries and products, including applications such as advertising messaging, product design, brand equity evaluation, pricing, competitive analysis, and market segmentation.