MaxDiff vs. Conjoint Analysis: When to Use Each for Market Research?

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In this blog post, learn the main differences between a MaxDiff and Conjoint analysis, and when to leverage each type of methodology in your research objectives. 

 

 


 

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What are the main similarities and differences between MaxDiff and Conjoint?

Do you know your MaxDiff from your Conjoint?


MaxDiff Analysis (also known as Best-Worst Scaling) and Conjoint Analysis (also known as Choice-based Conjoint) have some characteristics in common, but they also have some key differences that are worth understanding so you choose the best method for your research needs.


Both approaches force respondents to make trade-offs between items on a list and can identify which items (or factors, or attributes) drive take-up of a product or service. The factors could be any elements within an offer - for example, product attributes like style, color, and taste. Both also deliver interval-scaled utility scores, which show how important each item is - which is great information to have for optimizing a value proposition.

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What is a MaxDiff Analysis?

While similar to a Conjoint, MaxDiff is a simpler research method. By showing respondents multiple sets of attributes and forcing them to make trade-offs, MaxDiff reveals customer preferences and the relative importance of each item. For example, if you were looking to make sure your range of jeans includes styles that appeal to all sub-groups of your target audience, you might show lists of attributes such as ‘color’, ‘fit’, ‘length’, ‘waistband height’, and ‘price’.


To avoid participants having to assess a long list of items and choose which are most and least important to them, they would instead be shown three or four attributes at a time, with a rotating combination of items on each screen. MaxDiff takes the preference scores for each attribute and presents them in bar chart format, detailing two key metrics: the relative rank of items in order of importance, and the magnitude of those items' importance relative to each other. Typically, MaxDiff will research attributes at one level only - so for our jeans scenario, the trade-offs respondents have made will reveal whether the ‘fit’ is much more of a deal-breaker than ‘color’, or where the aspect of ‘price’ fits into the overall ranking. Variations, or levels, within those attributes (blue/black/indigo/white, skinny/slim/regular etc.) will not be included. That’s where Conjoint comes in...

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What is a Conjoint Analysis?

With Conjoint, respondents are presented with different configurations of products, services, or concepts (e.g. Product A, Product B, and Product C) and asked which one they would opt for. Product A might be a tight-fitting, black, high-waisted pair of jeans with rips in them. Product B could be a baggy, stonewashed, low-rise pair of jeans. Product C might be white, high-waisted, bootlegged pair.


By asking respondents to choose their favorite product (multiple times within the survey), their preferred attributes are inferred, so that it can be deduced which set of attributes are most attractive to them in that product. This methodology means that the data can be presented and modeled in a more versatile way than with MaxDiff; you have the ability to understand the importance of individual attributes so they can be compared, but you can also test different combinations of attributes to evaluate the potential success of a product.

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When to use each research method? 

The question at the core of both MaxDiff and Conjoint Analysis is: how do particular aspects of my product, service, or category (like attributes, price, or competitive set) influence consumer decision making?


Conjoint takes the analysis of attributes within a product or service a step further than MaxDiff. While MaxDiff sheds light on the features or characteristics that are most persuasive in a product or service, Conjoint offers a more nuanced picture of what a successful product or service would look like if it were to be fully developed.


One helpful way of thinking about each technique is that MaxDiff is useful for prioritizing elements of an offer, while Conjoint is useful for optimizing the entire offer. For this reason, MaxDiff is often used as a precursor to Conjoint studies; MaxDiff identifies the attributes that are sought after in a product, while Conjoint Analysis puts those attributes into a package that will optimize the share of preference.


Each method can be used for a number of business areas, including but not limited to:


  • product concept testing
  • brand messaging
  • product development
  • prioritization of product features
  • new product testing
  • competitive landscape research
  • customer satisfaction (including by different customer segments)


Because of its strength in helping the evaluation of product profiles, pricing is often a central question in Conjoint Analysis. Specifically, price elasticity: how potential demand changes in relation to the price, is an effective use of Conjoint. Conjoint also shows which product profiles are appropriate at different price points. So with the jeans example, the question might be ‘What’s the most we can charge for black, tight, ripped jeans without a significant decrease to share of preference?’ or ‘What happens to price expectations if we change the color to dark blue?’

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Automate MaxDiff and Conjoint Analysis with quantilope

Whichever research method you choose, quantilope’s Insights Automation Platform will ensure quick and actionable results.


quantilope’s AI-powered methodologies can be applied with a drag+drop functionality, making it simple and straightforward for researchers of any background to capture advanced research insights. quantilope’s platform also prioritizes user experience, making it intuitive and enjoyable for respondents to provide their valuable feedback.


MaxDiff projects are simple to set up and results are easy to interpret, as you can see in this demo video. In the case of Conjoint, quantilope offers an intuitive market simulator with customizable scenarios (e.g. what happens to expected sales if you change the price or other attributes within your product profile?) as well as an automated product optimization module to help make the most of your research insights. Take a closer look at quantilope’s Conjoint method here.


MaxDiff and Conjoint Analysis can be hugely powerful in guiding the direction of your product or service. If you’d like to learn more about how to leverage these methodologies for your own business, get in touch below: 

Get in touch to learn more!

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