Monadic testing 101: How to find winning concepts cost-effectively
• • • • • •
Curious how consumers will react to your product on the shelf? Monadic testing mimics real life, so you can choose the right concept.
How do you ensure a product launch is successful and avoid potential failures? Concept testing. This vital component of the customer feedback loop enables companies to gauge consumer reactions to new ideas, products, or even branding and advertising strategies. Among the various concept testing methodologies, monadic testing, or A/B testing, stands out for brands seeking detailed insights into specific concepts, product designs, or campaigns.
Suzy streamlines this essential process by integrating monadic testing within a broader, consolidated research framework. By leveraging Suzy's platform, businesses can seamlessly connect qualitative and quantitative data collection methods, allowing for a more comprehensive understanding of consumer preferences. This consolidation not only simplifies the concept testing process but also enhances its effectiveness, providing clear, actionable insights that can significantly reduce the risk of product launch failures. Let’s dive deeper into how monadic testing works and how it can be effectively implemented within Suzy’s unified research ecosystem.
What is monadic concept testing?
Monadic testing is essentially A/B testing. In a monadic survey, respondents see one concept in isolation. One respondent may see a blue packaging design, while another is shown red. Neither participant sees the other design. This allows the researchers to determine which packaging design has the absolute best performance.
Essentially, monadic testing mimics real life. Consumers usually only see one version of a product or concept on the shelf. This type of concept testing helps researchers gauge how a product will really perform in the market.
Researchers should use monadic concept testing to:
Narrow down early-stage concept ideas
Select a marketing asset, graphic, or static advertisement from a range of similar options
Choose a package design for a specific product
Monadic testing also helps inform decision-making across all four pillars of enterprise research, from foundational learning all the way to shopper and tracking support.
Finally, monadic testing allows researchers to ask follow-up questions for more in-depth insights while keeping surveys short and sweet. Let's take a look at a few examples to understand how and why monadic testing works.
Examples of monadic concept testing
Example 1:
Pillar: Foundational Research
Company type: Retail
A financial services organization wanted to understand which financing terms work best for a loan. To determine the preferred amount and length of a loan term, the organization ran a monadic test on three different loan terms. After testing, the institution selected the optimal term to offer as a new loan.
Example 2:
Pillar: Innovation
Company Type: CPG
A popular kids’ beverage brand needed overnight feedback on more than 20 new product concepts. Using Suzy, the team monadically tested each concept against 100 parents with young kids at home. After participants viewed the concept, they ranked their purchase intent and need/desire on a 5-point scale, and shared open-ended feedback on what they liked and didn't like about the concept. Based on the feedback the team received, they were able to select a top choice.
Example 3:
Pillar: Innovation
Company: Retail
A large retailer wanted to understand the current perceptions around the online apparel shopping experience across several retailers and test 10 potentially disruptive ideas that could enhance online apparel shopping in the future. Thanks to monadic testing, the team selected two concepts that shoppers were most excited about. They also determined which concepts interested shoppers the least.
Best practices for monadic testing
Write the right survey
Structure questions to help you get quality data so you can succeed during the analysis phases. Picking a winner doesn’t always come down to one key metric. You need to examine the results of every question to find your winning concept and consider the right metrics for the concept category as well as internally used metrics.
Look at your metrics
Start with stat testing to guide your analysis. It’s important to avoid drawing conclusions based on directional differences. For example, let's talk about Top and Bottom Box scoring. Top 2 Bottom (T2B) focuses on consumers with the most favorable perceptions. Compare that to averages, which also take unfavorable perceptions into account. T2B/B2B can help researchers understand more polarizing topics, but either metric can ultimately be used to make decisions. Your final choice should not be driven solely by metrics but should reflect your comfort level and how it fits into an overall direction for the product/concept.
Use open-ended questions to understand “why”
Open-ended questions can help you zero in on the important nuggets of information, including likes and dislikes. From there, you can uncover refinement opportunities to take your concept even further.
Need a tie-breaker?
Turn to forced-choice questions when needed. There will likely be some differences between the results in forced-choice questions versus your metric questions. Forced-choice allows consumers to see all concepts at once and choose their favorite. However, there is often a bias toward the concept they saw first. Because of that, forced-choice questions should be primarily used to break a tie.
Other tips for monadic testing
Be consistent. Even though you’re testing concepts that differ from one another, the variation shouldn’t be significant. The “fidelity” of the concept MUST be consistent across test cells to avoid the introduction of variables to make cross-comparisons impossible. For example, if your concept is testing an image, then all other concepts should also be testing an image.
Use a mix of grid and open-ended questions for a deeper understanding. The combination allows you to discover key details that might not always be evident.
Use a 7-point grid-scale as it leads to more granularity and allows you to find important research nuggets.
Your questions should analyze a variety of data points such as product appeal, relevance, price, believability, uniqueness, and purchase intent.
It's important to keep the confidence level in mind when reviewing the data. At Suzy, our PowerPoint deliverable has statistical testing applied at the 95% and 90% confidence levels to help in evaluating the results.
How expensive is monadic testing?
The cost of monadic testing can vary based on several factors, including the provider, the complexity of the survey, sample size, and the specific requirements of the study. It all depends on the provider you select for monadic testing.
| Feature/Provider | Suzy | DIY Platforms | Agencies |
|---|---|---|---|
| Speed | Fast turnaround, responses in under an hour | Variable, faster for simple surveys | Slower due to manual processes and approvals |
| Quality of Insights | High-quality, actionable insights | Good quality, but dependent on user expertise | High-quality, agency-level rigor |
| Advanced Features | Integrated advanced methodologies (MaxDiff, TURF, etc.) | Advanced features available but at extra cost | Extensive advanced features, expensive |
| Retargeting Capabilities | Powerful, built-in retargeting and segmentation | Limited retargeting capabilities | Strong retargeting, but slower process |
| Audience Quality | High-quality, engaged panel | Good quality, less engaged than Suzy's panel | High-quality, rigorous screening |
| Reporting and Analysis | Comprehensive, user-friendly reports | Basic to moderate, less detailed | Comprehensive, detailed analysis |
| Cost Efficiency | Predictable, cost-efficient pricing. Test up to 10 concepts with just 1 credit. | Variable, can add up quickly | Expensive, especially for custom projects |
In short:
DIY Platforms offer flexibility and a range of advanced features but can be complex and require significant user expertise. Costs can quickly escalate, especially for advanced features and detailed analysis.
Agencies: Known for high-quality, detailed insights with extensive support and advanced features. However, they are slower due to manual processes and approvals and are significantly more expensive.
What makes monadic testing at Suzy different?
Our Monadic Feature and Monadic Templates are a unique solution that:
Offers highly customizable audiences. With Suzy, you can create audience groups that are most relevant to your brand and audience. When you run monadic testing, you can accurately measure performance among those you want to target in the market.
Measure the metrics that matter. Our templates are easily customizable so you can look at the data you need.
Re-targets respondents based on specific question responses to learn more. You can also retarget respondents with Suzy Live sessions for deeper qualitative learnings.
Suzy is one of the most cost-effective monadic tests out there with just 1 credit to test up to 10 different concepts.
Want to see how it works? Book a demo with our team today!
Already a customer? Launch a monadic test today!
Want to learn more? Learn how to launch a monadic test today on Suzy Academy!
