Choice-Based Conjoint Analysis
Marketing managers have found choice-based conjoint analysis unbeatable when they want to select an optimal set of attributes for a new or restaged product.
Conjoint analysis identifies the single best combination of product attributes from the consumer’s perspective, showing the tradeoffs consumers would be willing to make among product features if that optimum were not feasible.
Because of its flexibility and power, researchers have applied conjoint in a number of industries, including:
- Packaged goods. Decide on benefit claims, product features (for example, fat content, flavour, salt content), packaging (can versus bottle), labeling, and pricing.
- Telecommunications. Decide on pricing structures (monthly or per minute pricing) and service features.
- Financial services. Decide on optimal service bundles (for example, credit card annual fees, interest rates, and rewards).
- Tourism. Decide on optimal combinations of attributes for package tours (destination, number of days, number of meals, and package price).
- Consumer electronics. Decide on electronic features and pricing.
- Automotive. Decide on options packages.
Mimic what consumers do in the marketplace:
Choice-based conjoint represents an enhancement of traditional conjoint in that respondents in a choice-based conjoint study provide choice data rather than ratings or rankings. Choice data mimics what consumers actually do in the marketplace.
How does it work?
Choice-based conjoint relies on data from a discrete choice experiment in which respondents choose between sets of products. Each product is a hypothetical combination of attributes chosen by an experimental design procedure and the experiment involves presenting several sets of such products to each respondent and having the respondent indicate which of the products he or she would be most likely to purchase.