Conjoint analysis is a powerful method used in market research to understand how people make decisions when presented with a mix of product features. In AYTM’s conjoint module, survey participants are shown different product configurations and asked to make choices – similar to how they'd compare options in a real-world buying scenario.

What makes conjoint analysis unique is its ability to uncover not just which features consumers say matter most, but which ones actually drive their preferences. This helps businesses answer questions like “Which features are worth the investment?” or “If we remove this feature, how much preference will we lose?”

How AYTM's Conjoint Tool Works

In an AYTM conjoint study, you set up your product attributes (like size, color, features, or price) and list the different levels for each one. Then AYTM generates combinations of these levels into product scenarios that respondents evaluate.

For example, a laptop brand might test attributes such as battery life, screen size, processor, and price. Each respondent is shown various combinations and asked to choose which product they’d buy or prefer – mimicking a trade-off decision.

What Conjoint Analysis Reveals

The true power of conjoint analysis lies in its ability to distill preferences into measurable data points. Some of the key insights AYTM's conjoint tool provides include:

• Feature trade-offs: Learn which features consumers are willing to give up to gain something else, like choosing a higher price for better performance.
• Relative importance: Understand which product attributes matter most in decision-making, helping your team prioritize based on actual consumer behavior.
• Simulators: Use the built-in simulator tool to model various product scenarios and see predicted consumer choice shares for different feature combinations.

Decoding Real-World Preference Drivers

AYTM’s intuitive platform makes conjoint research accessible for many teams, even with limited experience. However, interpreting the outcomes still requires thoughtful analysis. Numbers alone don’t tell the whole story – knowing why consumers behave a certain way and what it means for your product strategy takes discernment.

This is where seasoned insights professionals come in. SIVO’s On Demand Talent can help bridge this gap by guiding teams through setup, analysis, and strategic interpretation, ensuring outputs lead to clear feature prioritization and business action.

Once your AYTM conjoint study is complete, the platform delivers several valuable outputs. Two of the most critical are utility scores and attribute importance scores. Understanding these results is key to making informed, data-backed product decisions.

Utility Scores Explained

Utility scores measure the relative value respondents place on each level of a feature. Think of them as a kind of internal “point system” for preferences – the higher the utility, the more desirable the feature level is relative to others.

Let’s say you tested three price points for a product: $10, $15, and $20. You might see results like:

• $10 – Utility: 1.2
• $15 – Utility: 0.4
• $20 – Utility: -1.6

This implies that most respondents favor the $10 option, and have a clear drop-off in preference as price increases. While this may seem obvious, utility scores provide similar insights for less intuitive attributes, such as design styles or specific features.

Attribute Importance Scores

These scores tell you how much influence each product attribute had on choice decisions. They are expressed as percentages and always sum up to 100% across all attributes.

If your study measured attributes like storage space, camera quality, and price, you might see something like:

• Price: 45%
• Camera: 35%
• Storage: 20%

This means price had the most weight in consumers' decision-making, followed by camera quality.

How to Use These Scores for Feature Prioritization

By combining utility and importance scores, you can prioritize resources to focus on the features that truly drive consumer preference. For example:

• If an attribute has a high importance score and some levels with very high utilities, that’s a strong area of influence and value to emphasize in product development.
• If a feature has low importance and flat utility scores, it likely doesn’t impact decisions – and may not need investment.

Avoiding the Pitfalls of Misinterpretation

It’s easy to view utility and importance scores as black-and-white answers, but context matters. A low utility score might not mean a feature isn’t valuable – it could mean it performs well across all levels, or isn’t presented with the right variants.

This is where involving experienced consumer insights professionals can make a significant difference. SIVO’s On Demand Talent support teams in getting beyond the raw data and crafting stories that align findings to customer needs and business goals. They can help ensure interpretation accounts for industry dynamics, competitive context, and strategic relevance – so you’re not just looking at data, but acting on it with confidence.

Once your conjoint analysis is complete in AYTM, one of the most powerful tools at your disposal is the simulator. The AYTM conjoint simulator allows you to mix and match different product feature combinations and see which ones best align with your target audience’s preferences. This tool helps translate raw data into realistic predictions that can guide your go-to-market or product development strategies.

What is a Conjoint Simulator on AYTM?

A conjoint simulator is an interactive feature within the AYTM platform that lets you model hypothetical products using the preferences uncovered in your research. As you build different variations of your product – selecting specific features, configurations, or price points – the simulator calculates the share of preference each option is likely to receive from consumers. Essentially, it answers the question: “What happens if I build it this way?”

Why Simulators Matter for Feature Prioritization

While utilities and importance scores indicate what matters to consumers, simulators reveal how different combinations of features perform in a market context. This is where feature prioritization becomes more strategic. For example, you can use simulations to:

• Compare a “basic” vs. “premium” version of a product
• Test trade-offs between price and added features
• Evaluate how removing a specific feature impacts consumer preference
• Understand cannibalization risk across your own product lines

Imagine you’re developing a new fitness tracker. Utilities from your AYTM conjoint analysis show that heart rate monitoring and battery life are high priorities. The simulator helps you see what happens when you build one model with both of those features, versus a model with just one – perhaps at a lower price point. Seeing predicted preference shares helps you choose the most compelling feature set relative to your business goals.

Tips to Get the Most Out of AYTM Simulators

To use simulators effectively, be sure to:

• Start with realistic configurations that reflect your technical or budget constraints
• Test several scenarios to stress-test your assumptions
• Benchmark against current products (yours or competitors’)
• Use share of preference insights alongside business metrics like profit margin

Simulators are especially valuable in fast-moving industries where feature decisions must be made quickly, but with confidence. Partnering AYTM’s tools with thoughtful decision-making produces results that are not only data-driven, but also highly actionable.

While platforms like AYTM make DIY market research feel more accessible than ever, interpreting conjoint results isn’t always straightforward. Behind those clean dashboards and colorful charts lie important nuances – ones that can easily be missed without the right experience or training.

The Real Challenge of DIY Conjoint Analysis

Conjoint analysis outputs contain several key data types: utilities, attribute importance scores, preference shares from simulations, and often interaction effects between features. However, understanding what these numbers truly mean in context – and how to translate them into confident product decisions – requires expertise. Common DIY errors include:

• Mistaking high utility for high importance (not always the same)
• Overlooking variability across audience segments
• Running too few test configurations to support robust simulations
• Focusing on statistical outputs without connecting to business implications

For instance, a team might see that consumers rated a feature like “voice control” highly and assume it must be added. But an expert may notice that its benefit only matters in specific price tiers or for niche segments – insights that could be critical to success.

Connecting Data to Strategy

Numbers alone don’t make decisions – people do. Expert analysts serve as translators between raw data and strategy. They ask questions like:

• Does this result align with our broader brand promise?
• What are the operational or cost implications of this feature set?
• How might consumer preferences evolve, and how future-proof is this decision?

It’s this layer of questioning that ensures your AYTM conjoint analysis for product development leads to better business outcomes rather than just more data.

Ultimately, it’s not only about knowing what the numbers say, but also knowing what they don’t say. Missteps in interpretation can lead to misguided investments, missed opportunities, or even failed launches – costs that far exceed the investment in working with experienced consumer insights professionals.

As DIY market research tools like AYTM continue to evolve and become staples of insights workflows, many organizations find themselves missing the strategic layer to make the most of them. That’s where SIVO’s On Demand Talent comes in – experienced insights professionals who know how to blend human expertise with the power of modern platforms.

Doing More with Your Tools (and Less Lift)

DIY tools promise speed, cost saving, and autonomy. But without skilled interpretation, they can fall short of their potential. SIVO’s On Demand Talent gives you access to professionals who:

• Understand how to set up AYTM conjoint studies that align with your business objectives
• Spot hidden insights in utility scores and trade-offs
• Use simulators to recommend the most viable product configurations
• Coach internal teams for future success and skill-building

Unlike freelancers or consultants, our On Demand Talent act as true extensions of your team. That means they integrate seamlessly into your workflows, quickly getting up to speed on your organizational context, goals, and required outcomes.

Flexible Talent, Reliable Results

Whether you’re a startup experimenting with product-market fit or a Fortune 500 in need of scalable research support, On Demand Talent offers the flexibility to meet your needs. You can bring in the right level of expertise exactly when you need it – for a single study, to fill resource gaps, or to accelerate your overall consumer insights roadmap.

Clients often find that working with On Demand Talent helps their teams not only get answers more confidently but also build long-term capabilities with their investments in research tools like AYTM. You’re not just outsourcing – you’re leveling up.

In today’s environment – where teams must do more, faster, and often with less – finding the right balance between DIY and expert support is the key to staying competitive. With SIVO’s On Demand Talent, you don’t have to sacrifice quality to gain that speed or flexibility.