CHOICE MODELING
Best Suited For:
Quantifying product demand based on different feature sets of the product of interest and/or competitors, understanding the value of individual product features (e.g., for pre-launch products, provide direction on the value of different clinical trial endpoints)
Appropriate For:
All respondent types
How It Works:
Choice modeling, also called decision modeling or tradeoff analysis, models the likely behavior of respondents based on exposure to different product scenarios. The number of scenarios to which a respondent is exposed depends on the complexity of the scenario and/or the type of tradeoff to be made.
The power of a choice model is the use of an experimental design, which systematically defines the feature sets a respondent evaluates by minimizing overlap and correlations between the scenarios. Because of the experimental design, respondents need only evaluate a limited number of feature sets, but affords the researcher the data necessary to model interest in any configuration of the product tested, and, importantly, identify the specific product features that provide the greatest interest in the product.
SEGMENTATION
Best Suited For:
Identifying key targets and market understanding, pre- and post-launch
Appropriate For:
All respondent types
How It Works:
Segmentation is the division of the market into distinct groups of customers with similar characteristics. As much art as it is science, this can be achieved focusing on different types of data. At Lucid Health, we typically utilize demographic, behavioral, or attitudinal data when developing an actionable segmentation scheme.
To identify the best segmentation scheme, Lucid Health focuses on answering three core questions for each segment:
- How much opportunity does the segment represent?
- What are the needs and barriers of the segment, and can these needs be fulfilled or barriers overcome by the product offering?
- How do you reach the segment? In essence, what are their key channels of contact?
- Additionally, for a segmentation to be actionable, the segmentation must support a classification algorithm that predicts segment membership (to a high degree of accuracy) among customers who did not participate in the market research.
POSITIONING/LANDSCAPE ASSESSMENT
Best Suited For:
Understanding the market, in terms of:
- Current positioning of products
- Areas of unmet needs and strengths of the individual products
- Impact of a new product entrant(s)
Appropriate For:
All respondent types, though some exercises differ by respondent type
How It Works:
A positioning study typical includes several techniques to assess the market landscape. One notable technique is the individual attribute assessment, which is a multivariate analysis that reveals the natural positioning for each product in the market. It identifies the specific strengths and weaknesses of the product of interest (in relation to its competitors).
This attribute-based perception analysis complements derived and stated importance techniques. Using these techniques together captures the key attributes that drive product choice and highlights whether the product of interest is perceived as having an advantage or disadvantage with these attributes. Consequently, the product of interest’s strengths and weaknesses can be assessed in light of the product’s anticipated positioning, and direct the marketing team on whether the customer perceptions will support the intended positioning.