Companies face two major challenges when launching a new product or entering a new market.

First, they need to understand what customers value. Second, they have to determine how much customers are willing to pay for the features they value.

If a product does not include features customers value, they will not buy it. If a product comes with features customers do not value, the product becomes more expensive without increasing demand. If the price is set too high, customers will not buy the product. If the price is too low, revenue will be lower than it could be.

Understanding what customers value and how much they are willing to pay helps companies design products that satisfy customers and generate more revenue.

One of the most widely used methods to determine what customers value and how much they are willing to pay is conjoint analysis.

What is Conjoint Analysis?

Conjoint analysis is a market research method used to measure how much customers value different features of a product or service.

Conjoint analysis shows customers hypothetical products made up of different combinations of features and asks them to choose one.

ExampleA conjoint on vacation packages might show participants packages with different combinations of price, destination, hotel amenities, and proximity to a beach. Participants choose the package they prefer, allowing researchers to determine which features matter most. Example of a choice-based conjoint survey interface asking respondents to choose a vacation package.

By observing these choices, researchers can identify the features that drive purchase decisions.

Because it measures how customers make trade-offs between features and price, conjoint analysis is widely used for product design and pricing strategy.

When Do Companies Use Conjoint Analysis?

Companies commonly use conjoint analysis when making decisions about:

  • product design
  • pricing strategy
  • feature prioritization
  • product launches
  • competitive positioning
  • market entry.

More specifically, conjoint analysis allows us to determine:

  • which features make customers more likely to buy a product
  • which features make them less likely to buy a product
  • which features have little or no impact on purchase decisions.

Using Conjoint Analysis to Optimize Products

Companies developing products should prioritize features that increase purchase likelihood and avoid those that reduce purchase likelihood or that provide little value to customers.

Conjoint analysis also allows researchers to calculate how much customers are willing to pay for each feature. Companies should then include features that customers are willing to pay more for than their cost to the company. They should avoid features that customers aren’t willing to pay for.

Simulating Market Outcomes

The final step in conjoint analysis is simulating the share of preference for competing products. These simulations estimate how customers would choose between competing products with different combinations of features and prices.

Using such simulations, companies can identify the optimal combination of features and price that maximizes their share of customers’ preferences as well as their revenue and profits.

By learning what customers want and how much they are willing to pay for that, companies can make their customers happy, and they can ensure their product launches are successful.

Have you ever used conjoint analysis to help with a product launch?

Learn more about how conjoint analysis can help optimize product design and pricing strategy.