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How to start a conjoint analysis?
     David Tang    |    Market Research


This article provides a detailed response to: How to start a conjoint analysis? For a comprehensive understanding of Market Research, we also include relevant case studies for further reading and links to Market Research best practice resources.

TLDR Begin conjoint analysis by defining the problem and setting clear objectives to guide the entire research process.

Reading time: 5 minutes

Before we begin, let's review some important management concepts, as they related to this question.

What does Problem Definition and Objective Setting mean?
What does Framework Development mean?
What does Sampling Strategy mean?
What does Data Analysis and Interpretation mean?


Understanding the first step in setting up a conjoint analysis is crucial for any C-level executive aiming to steer their organization towards data-driven decision-making. Conjoint analysis, a sophisticated research method used to determine how people value different attributes that make up an individual product or service, is a cornerstone in the realm of market research and product development. The initial phase of this analytical process involves a deep dive into defining the problem and setting clear objectives. This step is not just about acknowledging the need for data but articulating what specific insights the organization seeks to gain. It's about narrowing down the broad spectrum of questions to the ones that are most critical for strategic planning and decision-making.

Framework development comes next, serving as the blueprint for the entire conjoint analysis. This framework should outline the attributes and levels that will be included in the study, ensuring they are both comprehensive and relevant to the target market. For instance, if a telecom company is evaluating handset features, attributes might include battery life, screen size, and camera quality, each with various levels (e.g., 12 hours, 24 hours, 36 hours for battery life). This step requires meticulous planning and a deep understanding of the market to ensure that the attributes chosen are not only significant to consumers but also feasible for the organization to deliver.

Choosing the right conjoint analysis method is another critical decision at this stage. There are several types, including traditional conjoint analysis, adaptive conjoint analysis, and choice-based conjoint analysis, each with its own set of strengths and applications. The selection depends on the specific research objectives, the complexity of the product or service being analyzed, and the detail of data required. Consulting with market research professionals or firms with a strong analytics background, such as McKinsey or BCG, can provide valuable insights into which method will best suit the organization's needs.

Setting Up the Study

Once the framework is established, the next step involves designing the study. This includes creating the survey or experiment that will be presented to respondents. The design phase is critical because it influences the quality of data collected. It's not just about asking the right questions but also about presenting them in a way that is understandable and engaging for participants. Crafting scenarios that accurately reflect real-life buying situations can significantly enhance the reliability of the data. For example, a well-designed study for a car manufacturer might involve scenarios that mimic the car buying process, including trade-offs between fuel efficiency, price, brand, and other relevant attributes.

Sampling strategy also plays a pivotal role at this stage. Deciding on whom to include in the study affects the applicability of the results to the broader target market. This involves not just demographic considerations but also behavioral ones, such as past purchasing history or brand loyalty. The goal is to ensure that the sample is representative of the organization's target customer base, thereby making the findings actionable and relevant.

Execution is where theory meets practice. Launching the study requires meticulous attention to detail and rigorous testing to ensure that the data collection tools are functioning as intended. This phase often involves pilot testing with a smaller subset of the target sample to identify any potential issues with the survey design or execution plan. Adjustments based on feedback from the pilot can significantly improve the quality of the final data collected.

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Analyzing and Applying the Results

After collecting the data, the next critical step is analysis. This involves using statistical software to decipher the preferences and trade-offs made by respondents. The analysis should not only quantify how much value consumers place on different attributes but also provide insights into how these preferences vary across different market segments. This stage is where the real strategic value of conjoint analysis comes to life, offering a nuanced understanding of customer preferences that can inform everything from product design to marketing strategies.

However, the utility of conjoint analysis doesn't stop with data interpretation. The real test of its effectiveness lies in how well the insights are integrated into strategic planning and decision-making processes. This means going beyond the numbers to understand the why behind consumer preferences and leveraging this understanding to make informed decisions about product development, pricing, and marketing strategies. For instance, if the analysis reveals a strong preference for eco-friendly products among a significant segment of the market, an organization might consider focusing on sustainable materials in their product development strategy.

Ultimately, the first step in setting up a conjoint analysis—defining the problem and objectives—sets the tone for the entire project. It requires a clear understanding of what the organization aims to achieve and a strategic approach to framework development. From there, meticulous planning, execution, and analysis pave the way for actionable insights that can drive meaningful business outcomes. Embracing this structured approach to conjoint analysis can empower organizations to make data-driven decisions that resonate with their target markets and support long-term growth strategies.

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