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Tips for Successful Stakeholder Collaboration & Sharing Choice-Based Conjoint Analysis Results

At Numerious, we stress the importance of stakeholder collaboration during the design phase of a conjoint experiment. If designed right, choice-based conjoint analysis can provide invaluable insights into customer preferences and tradeoffs. But the true value of those insights lies in effectively communicating the findings to guide strategy and decisions. The end goal of every conjoint project is to empower teams to make data-driven choices, advancing customer-centric growth. Properly communicating and interpreting conjoint results to stakeholders can help drive informed decision-making, guide strategy, and maximize the impact of research efforts.

In this article, I will explore the importance of sharing choice-based conjoint analysis results with decision-makers and present effective communication and stakeholder collaboration strategies.

We’ll discuss,

Stakeholder Collaboration and The Importance of Sharing Results

Choice-based conjoint analysis unveils customer preferences and tradeoffs, providing valuable business insights. However, to achieve the most value one must effectively collaborate with key stakeholders as they are the ones who can take action on the results of your research.

Imagine a researcher proposing a price point that would result in zero profit for the business. I can guarantee that would not land well with the product team. Imagine recommending a feature change that would require a multi-million dollar investment in developer and manufacturing costs that would side-line a launch when an equally appealing modification could be tackled with a sprint and fit easily within the current product roadmap.

As a strategist, it is your responsibility to engage your stakeholder throughout the entire analysis process so that the outcomes of the research will be actionable. By encouraging stakeholder collaboration in the analysis process, businesses can harness their expertise and diverse perspectives to make informed decisions that enhance customer-centric growth.

Best Practices for Sharing Results

To effectively share choice-based conjoint analysis results with stakeholders, several best practices can be followed. Here are some best practices for extracting maximum value from conjoint analysis:

Lead with Simulations

The simulator tool is the most powerful output of a conjoint study. Therefore, you should focus on simulations when presenting findings and only use utility charts and importance scores as supporting tools.

Simulator Example

Simulator Example

A simulator tool provides a tangible and comprehensive approach to sharing choice-based conjoint results as it allows the stakeholder to see the direct impact of a change to their product or service on consumer preferences. And, it can do it within a competitive context. To put it simply, these powerful tools estimate market choices based on new product profiles and competitive scenarios, enabling stakeholders to visualize the real-world impact of different decisions.

What can you do as a researcher? Encourage hands-on experimentation with the simulator and facilitate the exploration of options. Once stakeholders see how easy it is to manipulate different product variables and see the impact, they will feel empowered to make data-driven choices based on the results. Have stakeholders with conflicting opinions of what's best for the product roadmap? Use the tool for war-gaming different scenarios, allowing them to evaluate every angle of a product launch.

Simulators translate abstract utility patterns into tangible and measurable data points like:

· Share of preference for current and new offerings

· Revenue and/or profit at various pricing levels

· Impact of adding or removing specific features

· Cannibalization rates across a product portfolio

By running simulations, businesses can bridge the gap between abstract utility patterns and concrete insights that resonate with stakeholders.

Limitations of Utility and Importance Scores for Stakeholder Delivery

While utilities provide directional preferences within an attribute, the scores don't represent real-world impact. For example, the utility scores may indicate a "square" version of the widget is most preferred. But, if every widget on the market is a square, perhaps it would be better for your brand to make a "circle". One can only uncover this within a simulator. It is within a competitive context that concrete insights can emerge on market response to new offerings. Isolating utility patterns misses the forest for the trees.

For stakeholders like executives, product leaders, and marketers, utilities fail to directly answer pressing questions on pricing, features, positioning, and growth opportunities. We must frame conjoint insights around what will resonate.

That being said, we know some stakeholders are used to seeing these output. So if your hand is forced, it's best to plot the distribution of the utilities so the team can see the entire picture because we all know, "lies are in the averages".

Utility Score Example

Utility Score Example

Craft Current and Future State Scenarios

Looking for a place to start? Use a simulator to model the existing market landscape to help stakeholders grasp the starting point based on the survey data. Then, model out future state scenarios to demonstrate how new offerings, pricing strategies, or feature tweaks can shift the market landscape.

What can the future scenarios demonstrate?

· Preference share gains from new product variants

· Optimal pricing strategies for maximizing revenue

· Cannibalization effects across a product line

· How specific feature tweaks increase or decrease appeal

Stakeholder collaboration in developing and reviewing these scenarios enriches comprehension of the results. Furthermore, this approach enables stakeholders to envision the potential impacts of different decisions, facilitating a clearer understanding of the strategic applications of the conjoint analysis.

Current and Future State Example

Enhancing Stakeholder Collaboration for Impact-Driven Decisions

The most effective way to extract maximum value from choice-based conjoint analysis results is to engage stakeholders in discussions and decisions based on the analysis. Tying recommendations to business objectives around revenue, profit, share gains, consumer interest, and other key metrics is vital. Simply exporting results is not enough.

When considering how to leverage the results, remember that:

  • In pricing discussions, conjoint can uncover the revenue-maximizing price point and willingness to pay for features.

  • For positioning, conjoint aids in understanding which specific benefits drive choice and can help focus messaging.

  • When innovating, conjoint highlights which feature customers value most to guide investment and engineering.

Acknowledging Limitations

While conjoint can give us a wealth of information (and significantly more than many other marketing research techniques), we must acknowledge the limitations of the methodology. Conjoint should be ONE input into a forecasting model - not the only input. It would be difficult to predict absolute market share without incorporating factors like awareness, availability, and macro conditions.

Conjoint also doesn't explain why specific options are preferred. Supplementing with questions outside the conjoint experiment or even including additional research phases, like qual, can help fill these gaps and provide a more comprehensive view. However, even with these limitations, for guidance on customer-centric decisions, conjoint delivers a uniquely powerful lens if paired with true stakeholder collaboration.


Sharing choice-based conjoint analysis results with stakeholders is essential to drive informed decision-making and maximize the impact of research efforts. Additionally, conjoint empowers strategies resonating with customer needs and preferences. Through effective communication and stakeholder collaboration, businesses can leverage the power of choice-based conjoint analysis to align strategy with customer preferences, enhance product offerings, and drive customer-centric growth. Moreover, collaborating across functions enriches comprehension and drives evidence-based decision-making for optimal market success.

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