Want to test a new product, concept, or service?
Two common methods used in market research are:
While these two tests sound similar, there is an important difference that stems from whether one new product or concept is shown vs. multiple.
Learn more about monadic testing, sequential monadic testing, how it works, and the pros and cons of using each.
For a name that seems complicated, monadic testing is pretty simple. It means market research participants are only shown one new product, concept, or service idea at a time.
For example, suppose an engineering team wanted to test two new concepts:
The engineering team then decided their research methodology of choice would be an online survey.
One option would be to field an online survey of 300 respondents. The survey would ask questions regarding the current concept, concept A, and concept B.
However, when using monadic testing each concept is tested individually.
Continuing with this example, the study is fielded to 300 respondents.
This is how a monadic test in market research would be set up:
Each of the surveys would ask essentially the same questions, except for the concept shown. The idea is to test appeal, price, and collect feedback on each concept independently.
The goal is to use the data gathered to decide which concept to move forward with.
In a monadic test, your sample is split into separate groups, and each group only sees one concept or product idea. You’ll also want to include a control group that sees your current product to serve as your benchmark.
Here’s how it breaks down:
Say you’re testing two new product concepts against your current offering. You recruit 300 participants for your study. Those 300 people are randomly divided into three equal groups of 100. Group 1 evaluates only your current product. Group 2 evaluates only Concept A. Group 3 evaluates only Concept B.
Each group answers the same set of questions about the product they’ve seen. The questions are about appeal, purchase intent, pricing, features, and anything else you want to measure. Since each participant only sees one option, their feedback is completely unbiased by comparison to other concepts.
Once all the data is collected, you compare the results across the three groups. This shows you which concept performs best on the metrics that matter most to your business.
The beauty of this approach is its simplicity. Participants aren’t overwhelmed with options, and you get clean, unbiased feedback on each concept independently.
Unlike monadic testing, sequential monadic testing shows participants the current concept as well as Concept A and Concept B.
Again, suppose we are testing the original concept against two new concepts. This study would randomly show each of the concepts to participants.
Here’s another easy example…
If a study was fielding a survey to 300 participants, this is how a sequential monadic test would be set up:
The idea again is to test appeal, price, and collect feedback on all of the concepts. Still, the goal of this study is to use the data to decide which concept to move forward with.
There are some pros and cons to monadic testing and sequential monadic testing.
An advantage of using monadic testing is that participants only see one concept. This eliminates bias or preferences made based on awareness of the other concepts being tested.
However, making participants aware of each concept and testing their preferences can also be a pro to sequential monadic testing.
In some cases, it may be better for an organization to test all concepts in a randomized order.
Ultimately, the decision comes down to the type of product, concept, or service being tested as well as the goals and objectives of the research.
A market research company, like Drive Research, will be able to guide you through making the right decisions throughout the process.
Split-cell monadic testing is essentially the pure form of monadic testing. Each respondent sees only one concept and answers a series of questions about it. If you’re testing three concepts, you’ll need three separate groups of respondents (one for each concept). This approach has some clear advantages.
Since respondents only evaluate one concept, you can ask more detailed questions without worrying about survey fatigue. Completion rates tend to be higher because the survey is shorter and more focused. And because concepts are shown in complete isolation, you eliminate any bias that might come from comparing options.
The trade-off? You’ll need a larger overall sample size since each concept requires its own group of respondents.
A/B testing is a specific type of monadic testing commonly used in digital marketing. It compares two versions of something (like a webpage, email, or ad) to see which performs better.
In an A/B test, you have a “champion” (your current version that’s proven to work) and a “challenger” (a new variation you want to test). Each version is shown to a different group of people, and you measure which one drives better results, typically through conversion rates.
The key to successful A/B testing is keeping it simple. Test one change at a time. It could be a different headline, button color, or call-to-action. If you change too many things at once, you won’t know which specific element made the difference.
A/B testing requires careful sampling. Both groups need to have similar characteristics, otherwise you’re just measuring differences between audiences, not differences between your variations.
Discrete choice analysis takes a different approach altogether. Instead of showing one complete concept, respondents see several options at once, with each option broken down into specific features or attributes. They then choose which option they prefer.
For example, if you’re testing a new restaurant concept, you might show respondents different combinations of cuisine type, price point, ambiance, and location. By analyzing their choices across multiple scenarios, you can determine which features matter most.
This method mirrors real-world decision-making more closely since people rarely evaluate products in isolation. The surveys tend to be shorter too, typically 8-12 questions. However, you need to be careful not to overwhelm respondents with too many choices or features, which can lead to confusion and fatigue.
Drive Research is a market research company located in Upstate New York. Our team assists businesses across the country with both quantitative and qualitative research studies.
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