A conjoint analysis example can be complex. As global leaders in medical market research, IDR Medical show the benefits and challenges they can present.
COVID-19 has illuminated the healthcare industry's capacity for innovation. AI-aided accurate chest X-ray analysis, cost-effective genomic sequencing, and bespoke cancer treatments are noteworthy advancements. However, the persisting crisis necessitates further innovation in this hard-hit sector.
Healthcare companies wrestle with multi-faceted supply chains, fluctuating healthcare professional interactions, and disrupted clinical trials. Clinical settings face distinct challenges: shifting protocols, patient care transformation, limited resources, and financial constraints—all evoking calls for inventive solutions.
The pandemic's seismic impact led 90% of executives to expect major business transformations, with 85% anticipating enduring alterations in consumer preferences. For two-thirds of healthcare leaders, navigating this crisis is the pinnacle of their career challenges.
Here, conjoint analysis emerges as the guiding light for data-driven decision-making in healthcare. Implementing conjoint analysis bolsters cost efficiency, customer engagement, and profit dynamics.
Delving into conjoint analysis examples, we shall examine the benefits and challenges encountered when employing this technique in healthcare market research.
Conjoint analysis can be used in healthcare to find which aspects of a product or service are most important to consumers and providers, enabling healthcare organizations to develop strategies to reduce costs while improving outcomes.
Conjoint analysis is a quantitative research methodology, quantifying customer preferences and determining the trade-offs people make when making decisions about their care. Conjoint analysis can help:
Conjoint analysis serves medical market research and device manufacturers by assessing the competitiveness of product features and affordability. Consumers also relay future expectations and perceptions of current products, influencing overall reception.
Another conjoint analysis example is to use varying conjoint methodologies during medical device and pharmaceutical product development and launch. By gauging customer responses regarding different product aspects (such as design, value, brand perception, and price sensitivity), IDR Medical can help estimate preferences and predict market share. By utilizing customized conjoint methodologies, we can ensure more accurate and specific responses.
Conjoint analysis is an effective solution but is most relevant at certain stages of the product lifecycle. The main reasons to use conjoint analysis are:
When embarking on the creation of a new product or service, to drive new product development decisions, it's crucial to uncover features that enhance value, ignite customer excitement, and boost market share.
Using a conjoint analysis example for medical device market research will aid you in encapsulating these focal points. Whilst acknowledging and deciphering these aspects, you edge closer to delivering solutions that resonate with your audience, thereby driving business growth and solidifying your market position.
Before launching a new product, feature, or service, you should consider customer preferences for competitor products within the same category or price range. Understanding customer willingness to pay a premium price compared to competitors is essential. Conjoint analysis examples provide a deeper insight into the juncture of perceived value and consumer expectations.
This method navigates price sensitivity complexities and empowers informed decision-making. Offering guidance for optimal pricing strategies, their willingness to accept new offerings, while catering to the healthcare industry's dynamic demands.
As experts navigating the complexities of the healthcare industry, we understand that conjoint analysis may not always be the optimal approach for every project. At IDR Medical, we assess each undertaking from the outset to ensure time and budget efficiency, while presenting suitable alternatives when needed.
Below are a few critical considerations to weigh before embarking upon conjoint analysis:
A conjoint analysis example could be asking participants to select one of two blood pressure machines with varying attributes such as analog or digital, price, size, weight, etc. Each of the features has several levels that participants can choose from.
The choices are presented in specific combinations, and participants must rank them based on their preferences. The data collected is then analyzed to understand customer preferences for different product features and attribute levels.
A researcher can gain insights into why the respondents highly value specific attributes and how alterations in those attributes could impact their decision-making by studying their responses.
Conjoint analysis methods can include:
This approach uses specific attributes to construct diverse product descriptions or profiles, presented to study participants to be ranked or rated, evaluating their preferences, and likelihood to purchase. The data collected from this analysis can be used to determine the best configuration of features for each product.
This conjoint analysis example is a computer-aided survey that enhances each respondent's experience by customizing survey questions. Leveraging respondents' initial responses, each subsequent question narrows focus, guiding them toward their ideal product selection.
Mimicking real-life trade-off situations in decision-making, this conjoint analysis example identifies valued feature combinations. It's also known as discrete choice experiment (DCE) or discrete choice modeling (DCM).
Respondents gauge feature significance, evaluating their monetary value. Utilizing gathered data, an optimal product configuration tailored to customer preferences emerges, refining overall market offerings.
Adaptive Choice-Based Conjoint (ACBC) is the most modern conjoint analysis example and fuses the ACA and CBC methodologies. Through three interview phases, it delves deeper into participant preferences, adapting at the individual level as it learns from their prior responses. It’s longer than a traditional choice-based conjoint survey but provides a more in-depth analysis of each respondent's decision-making process.
To learn more about these five conjoint analysis examples and how each method works, follow this link to our eBook.
Acknowledging the intricacies of healthcare market research, allows us to support you in crafting a successful strategy tailored to your project's unique demands, with an unwavering commitment to your success.
Like any healthcare market research methodology, conjoint analysis has strengths and weaknesses to consider when deciding whether it is the right tool for your project. Conjoint analysis aims to understand how customers make decisions about products and services. The main challenge is ensuring the respondents accurately represent a market or target population.
Navigating these intricate methodologies can be challenging. Let IDR Medical support you in making informed decisions that ultimately contribute to your success in healthcare industry market research.
Conjoint analysis is increasingly used in healthcare and has proven successful in various areas. These include eliciting patients and communities' preferences for healthcare services, identifying consultants' priorities, establishing the best treatments, and determining patients' preferences in their interactions with doctors.
There are various stages that need to be completed before determining which conjoint method example should be used. Designing a conjoint survey involves several key steps to ensure that the survey accurately captures respondents' preferences and provides meaningful insights.
Here's a step-by-step guide to designing a conjoint analysis survey:
The first step is to define the objective of your conjoint analysis. Specify the insights or information you need to collect and explain how you intend to use the findings to make informed decisions. This will determine what type of conjoint analysis should be used and which attributes and levels need to be included in the survey design.
Pinpoint crucial attributes and distinguishing characteristics like brand, price, or battery life of your product or service to be under scrutiny. Ensure these attributes align with your research goals, bolstering the relevance and impact of your study.
Determine the different levels or variations within each attribute. Each attribute should have at least two levels, and the number of levels per attribute should be balanced to avoid bias.
Choice sets are combinations of attributes for respondents to select from. For effective conjoint analysis, incorporate a comprehensive, but manageable range of attribute combinations that encapsulates all possible variants. Strive for diversity, ensuring the total choice sets remain feasible to prevent respondent fatigue.
The choice task is a key aspect of surveys that requires respondents to evaluate products based on attributes, rank preferences, or determine purchase likelihood. Clarity is vital in defining this task, enabling effortless understanding and alignment with research objectives. Precision and comprehensibility are paramount in attaining valuable insights.
The experimental design is how the survey will be structured and presented to respondents. Factors such as the order of choice sets, the type of question layout, and response scales should all be considered when designing a conjoint survey. The design should ensure that each respondent sees a different combination of attribute levels to capture preferences accurately.
Before releasing the survey, it is essential to test and validate it. This involves piloting the survey with a small sample of respondents and making any necessary adjustments before launching the survey. Testing will help you identify any potential issues or errors that could impact the reliability of results. Additionally, validating the survey ensures that data collection is accurate and meaningful.
Launch the survey and gather responses from your respondents. Ensure that you monitor the data collection progress and that your sample has enough size to generate reliable outcomes. You invite more respondents if needed. When enough responses have been collected, you can begin analyzing the data.
Once all responses have been collected, analyze them using appropriate techniques to draw meaningful insights from the survey. Conjoint analysis examples, such as traditional or choice-based conjoint analysis, can help determine the importance of different attributes by assigning them utility scores.
The last step in designing a conjoint survey is to interpret the results. Analyze the data and draw meaningful conclusions from it. Use these findings to arrive at informed decisions about product development, marketing strategies, pricing, or other relevant topics based on the research objective that can be implemented within your organization.
Pioneering a new medical device or service launch, or seeking an edge over competitors? Mastering healthcare market research and analytical technique is necessary for success.
IDR Medical is an esteemed international healthcare market research and consulting firm, guiding medical device and pharmaceutical industry leaders. With decades of combined expertise, we amalgamate in-depth medical market research, business analytics, and strategic problem-solving for healthcare projects. Supports clients through idea conception, development, market evaluation, pricing, and commercialization, leveraging hands-on guidance and collaborative exploration of growth avenues.
Our talented team design effective conjoint surveys to unearth actionable insights into consumer preferences. IDR Medical span diverse areas within the medical technology and pharmaceutical realm, working as partners in discovering innovative solutions for complex challenges.
Start taking advantage of the benefits and witness the transformative power of conjoint analysis today.