Customers today, more than ever, expect brands to be responsive to their preferences and design products that meet their needs. Fortunately for consumers, the amount and variety of product options has never been more extensive. Large online marketplaces, product recommendation services, and hours upon hours of video reviews make consumers smarter and more equipped than ever. Unfortunately for brands, oversaturated markets are a grim reminder that designing products based on consumers’ needs remains crucial.
Conjoint analysis has emerged as a valuable tool in understanding customer preferences and their decision-making processes. Unlike traditional marketing surveys that often assess customer preferences by asking direct questions about single product features in isolation, conjoint analysis provides a holistic approach that considers the interactions and trade-offs between multiple product characteristics simultaneously.
So rather than asking about a single aspect of a product (e.g., Would you buy a pen with red ink?), conjoints ask customers to consider several different hypothetical products in their entirety (e.g., Would you buy a BIC ballpoint pen with red ink and a cap? What about a blue, Pilot gel pen with a click-y top?).
By presenting respondents with realistic product scenarios and requiring them to make choices, conjoint analysis captures the complexity of decision-making in a way that traditional surveys often fail to achieve, allowing product managers to gain insights into the relative importance customers assign to different product characteristics (e.g. How important is ink color in pen buyers’ decision-making?) and their impact on overall preferences.
In this article, we will explore how conjoint analysis can be used to optimize product design based on consumer preferences. In particular, this post will explain how to design a conjoint analysis and offer practical recommendations along the way.
To effectively utilize conjoint analysis for product design, it is crucial to clearly define your research objectives. Despite how powerful conjoint analysis is, it may not be the smartest or most appropriate methodology to answer your research question(s). This section will cover how to identify the stage of the product design lifecycle in which you find yourself.
The application of conjoint analysis may vary depending on the stage of the product design lifecycle you find yourself in. Understanding your current stage can help you tailor the conjoint analysis process to derive maximum value. Here are some common stages and how conjoint analysis can be utilized:
Considering the stage of the product design lifecycle allows you to tailor your conjoint analysis approach to the specific needs and goals of that stage, ensuring the insights gained are most relevant and actionable.
By defining your research objectives and considering both the suitability of conjoint analysis for your needs and the product design lifecycle stage you are in, you can lay a strong foundation for conducting effective conjoint analysis and making informed design decisions.
After you’ve determined that conjoint analysis is right for you, the next crucial step is to design your attribute map. This section will cover important considerations, including how to select what product features (otherwise known as product attributes) and nested characteristics (otherwise known as attribute levels) to test.
Start by determining the key product features, or attributes, that you want to test. Most consumer products have many attributes that could be customized in appearance or functionality. Cars, for example, come in many shapes, sizes, and types. When it comes to cars, consumers can choose between different transmissions, seat fabric, color, and many other attributes.
The key here is to select product attributes that (a) directly impact customer preferences and influence their decision-making and (b) are configurable features of your product. Consider factors such as functionality, design elements, pricing, packaging, and any other attributes that are relevant to your product category and target market.
For each product attribute, there are a few (or many) different varieties. For example, car shoppers have the option of choosing between electric, hybrid, and gas vehicles. They can decide between leather, fabric, and vinyl seats. They can even shop based on the exterior color they want.
Levels represent different variations or options within each product feature (or attribute). It is important to carefully select levels that are meaningful and representative of the product space you are exploring. Aim for a range of levels that capture the potential diversity of customer preferences.
Make sure you also keep an eye out for unrealistic combinations of product features. You may need to explicitly prohibit certain impossible or contradictory combinations of product features.
Another critical consideration is how to present the product features and levels to survey respondents. You have the option to use visual assets, textual descriptions, or a combination of both.
Depending on the complexity of your product and the nature of the attributes being tested, you may choose to use a combination of visual assets and descriptions. This approach can provide a comprehensive understanding of the product features while minimizing ambiguity, but remember to maintain consistency in the presentation format throughout the conjoint analysis to ensure reliable and valid responses from participants.
Once you have determined the product attributes and levels to include in your conjoint analysis, the next step is to create a balanced design. A balanced design ensures that your attribute level pairings are optimally displayed, maximizing the power of your study. To achieve a balanced design, you need to ensure that each attribute level pairing appears an equal number of times across different choice tasks. This balance prevents biases resulting from the order or frequency of specific levels and allows for accurate estimation of attribute effects.
Various algorithms and software tools are available to assist in generating a balanced design. These tools help optimize the allocation of attribute level combinations and ensure an efficient and statistically robust conjoint. By creating a balanced design, you enhance the quality and reliability of your conjoint analysis results, enabling you to make more informed decisions regarding product design and feature preferences.
In this section, we will explore the key considerations for creating a balanced design, including the number of choice tasks, the number of alternatives, and the inclusion of a dual response none option.
Conjoint analysis is a powerful tool for optimizing product design based on customer preferences. By considering the interactions and trade-offs between multiple product characteristics, conjoint analysis provides valuable insights into the relative importance customers assign to different attributes and their impact on overall preferences.
By leveraging conjoint analysis, you can gain a deeper understanding of customer preferences, identify key drivers of preference, and make informed decisions about product design, and market positioning. Ultimately, using conjoint analysis empowers you to create products that resonate with customers and meet their evolving needs in today's competitive marketplace.
Does your organization need help identifying your consumers’ product preferences? We’d be happy to help you with your conjoint analysis.