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CONJOINT ANALYSIS 

Conjoint analysis is one of the most widely-used analytical tools in marketing research. It helps inform various strategic decisions related to new product development, copy/claims development, pricing and portfolio optimization. We have strong expertise in two areas of conjoint analysis:

Discrete Choice Modeling and MaxDiff.

DISCRETE CHOICE MODELING

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WHAT IS IT?

Most versatile analytical tool to measure attribute tradeoffs​

  • Measures how buyers/consumers value components of a product/service bundle

  • Optimizes product/service offering

  • Simulator allows for scenario planning

  • Can combine with pricing and margin data for financial planning

HOW DOES IT WORK?

  • The product/service is broken down into its component parts and the different offerings within each part.

  • Different product concepts are created by varying those offerings.

  • Respondents are shown 3-4 product concepts at a time and asked to pick the concept they prefer. This task is repeated many times, showing a different set of product concepts in each task.

  • Based on respondents' evaluations of the concepts, we figure out how much unique value (utility) each feature adds.

COMMON APPLICATIONS

Discrete choice modeling has many applications for marketing, sales, new product development, and corporate program development.

  • Product redesign and line extensions

  • Pricing

  • Packaging development

  • Communications

  • Quantifying purchase decision hierarchy (Consumer Decision Trees)

  • Optimizing corporate programs

MAXDIFF
(BEST-WORST SCALING)

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WHAT IS IT?

A simple and efficient form of conjoint analysis to measure buyer/consumer preference toward a list of items/features/ benefits

  • Forces item tradeoffs through simple choice tasks

  • Allows better discrimination between items

  • Provides hierarchy of item preference

HOW DOES IT WORK?

  • A list of items to be tested is created.

  • Respondents are shown 4-6 items at a time and asked to indicate the one that is their TOP pick and the one that is their BOTTOM pick.

  • This task is repeated many times, showing a different set of items in each task.

  • Based on the respondents' evaluations of the items, we figure out how much unique value (utility) each item commands.

COMMON APPLICATIONS

MaxDiff applies to any situation that requires prioritization of items.

  • Copy/claims development

  • Prioritizing items for product development

  • Input for TURF (for portfolio optimization)

  • Uncovering distinct market segments

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