Conjoint Analysis

A testing heavyweight, a conjoint analysis is often used when introducing a new product or service into the market. Similarly, whole business models can be compared and shown to potential customers to see their compared value. Conjoint analyses can give you great insights into the mind of your customers and a good understanding of the worth of the various parts of your offering. It can show you where to concentrate in your offer development, who your most likely early adopters will be, and give you limited insight on the willingness to pay. However, its limitations are significant. To be statistically relevant, there needs to be a large amount of test participants (e.g. N=30+), who will most likely need to be incentivized as the test is long and potentially boring. You can only test a few characteristics so not to make the test too complex. Finally, the results might not necessarily be unambiguous. Especially for offerings that target a mass market, the advantages often outweigh the limitations and make this test format a great source of feedback and validation of your hypotheses.

Step-by-Step Guide:

1. Define Objective: Determine what you want to learn (e.g., customer preferences for product features).

2. Identify Attributes & Levels: Select key product attributes (e.g., price, color) and define several levels for each.

3. Create Profiles: Generate product combinations using the attributes and levels.

4. Design Survey: Present respondents with different product combinations and ask for their preferences (e.g., rank or choose).

5. Collect Data: Administer the survey to your target audience.

6. Analyze Results: Use statistical software to calculate utility values for each attribute, showing what customers prefer.

7. Simulate & Optimize: Use the data to model market scenarios and adjust product offerings based on consumer preferences.

8. Validate: Re-test with new data to refine your product or service offerings.

Conjoint Analysis helps you understand what features are most valued by consumers, guiding product decisions.

Example:

British Airways’ Use of Conjoint Analysis:

British Airways applied Conjoint Analysis to better understand the preferences of its frequent flyers regarding various aspects of their flight experience. By evaluating different combinations of features such as seat comfort, meal quality, check-in processes, and loyalty program benefits, British Airways was able to determine which attributes passengers valued most when choosing flights, especially in premium classes.

This analysis helped British Airways:

• Optimize their service offerings by focusing on enhancing features like in-flight comfort and priority boarding, which were highly valued by their target audience.

• Segment their customer base to offer tailored services that met the distinct needs of business and leisure travelers.

• Develop premium pricing strategies by understanding which services customers were willing to pay extra for.

Through the use of Conjoint Analysis, British Airways was able to refine their offerings, improve customer satisfaction, and effectively target different segments with optimized packages and services.

‍

For more information on the topic, please see the source below:

Gustafsson, A., Herrmann, A., & Huber, F. (2007). Conjoint measurement: Methods and applications (4th ed.). Springer. https://doi.org/10.1007/978-3-540-71404-0

Agarwal, J., Desarbo, W., Malhotra, N., & Rao, V. (2015). An interdisciplinary review of research in conjoint analysis: Recent developments and directions for future research. Customer Needs and Solutions, 2(1-2). https://doi.org/10.1007/s40547-014-0029-5  

‍

‍

#ConjointAnalysis #CustomerPreferences #MarketResearch #ProductOptimization #DataDrivenDecisions #ConsumerBehavior