Market research is critical for driving growth. It can inform strategy development, product development and marketing, setting you up for success. But it’s even more important when it comes to growing your business in countries outside of your home market. 

The global market research process looks different from domestic market research and requires a different approach in order to get the best results. In this article, we’ll break down why global market research is so important, the challenges involved, and how to do it as effectively as possible.

What is global market research?

Global market research is an umbrella term for the collection and analysis of information that companies undertake in a country that isn’t their domestic market. This includes designing the study, conducting the fieldwork, analysing the data and reporting the results – and can pertain to anything from customer understanding to product development research. It differs from market research that takes place domestically, with an understanding of cultural differences being crucial to its successful execution. 

Why is global market research important?

Global market research serves a number of important purposes. It helps companies understand their current or potential customers in international markets. These markets — and the people in them — are often radically different from your domestic market in many significant ways.

Failing to understand the often subtle distinctions between different global markets and gain a solid understanding of them before you launch a product can be a critical mistake that costs companies dearly.

Market research is equally important in global markets where you already operate. Here, it helps companies feel out new potential product launches and marketing campaigns, understand how numerous factors in those areas may have changed since they last conducted research, and better understand the feelings of their customers internationally.

Here are some of the main reasons to prioritize global market research:

What works well at home might fall flat abroad. You may have heard of Starbucks. It’s one of the most successful businesses in its home market of the US and is a hit with customers in many other countries across the globe. In many cities around the world, you’ll find a Starbucks almost on every corner.

In Italy, however, its presence is more limited. This is because the Italian coffee culture is profoundly different from what Starbucks offers, and the Italian public simply doesn’t have much of an appetite for the brand. The fact Starbucks has been able to gain a foothold there is an impressive achievement in itself and was only possible by significantly altering its product range — a change driven by extensive market research and collaboration with local businesses. 

It allows you to improve operations and save costs. Market research helps you gain a more thorough and clear understanding of your new markets and the logistical and practical steps involved in operating there.

This allows you to get your operations right the first time, avoiding expensive mistakes and delays and streamlining the process so you can maximize your chances of overall success.

It helps you understand your competition and what you’re getting into. When it comes to new global markets and expanding into different cultures, competition is a huge factor. Market research helps you understand your competition so you can compete effectively and avoid being completely eclipsed by more popular brands.

When Best Buy attempted to move into the Chinese market, it failed miserably, closing all its stores in the country just five years later. Why did this attempt fail so badly? Ultimately, it was due to local competition.

Local, smaller Chinese electronics companies were able to offer similar products at a much lower price by paying staff less and offering fewer benefits. They also had stores in more accessible locations, catering to a more bike-based and less car-based customer population.

Had Best Buy spent more time researching the local market, they may have taken a different approach, or opted not to expand into China at all.
It allows you to identify new opportunities you may not have otherwise considered. By better understanding your market through research, you’ll be able to pinpoint new opportunities to grow, generate ideas for new products and strategies, and innovate in a way that increases your chances of success.

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The challenges of global market research

Doing market research on a global scale can be much more challenging than doing it domestically and there are many more factors and variables to consider. Much of your market research will involve speaking to customers in markets that differ from your home country. This can be difficult for many reasons:

Cultural

Some international markets will be home to a vastly different culture from your domestic market. This can make research difficult. It’s important to respect cultural norms and take these differences into account both when designing your research approach and analysing your results. 

For example, in some cultures, like in China, people might be more inclined to moderate their views in a group setting, making it harder to get to the heart of an issue in a focus group, for instance. Understanding this can help you determine which methodology to choose, along with how to probe, and what to look for when you’re analysing the data.

Linguistic

Carrying out customer surveys, focus groups, in fact, anything involving interviews and questions poses obvious linguistic barriers in foreign markets. This makes global research particularly challenging. You’ll need to be able to connect with respondents and understand their views in the local language. Understanding nuances and ensuring key details aren’t lost in translation is vital, so it pays to work with native speakers to help you navigate these issues. 

Logistical

Finding appropriate facilities to conduct research in a different market can be tough, particularly if you’re working on logistically challenging projects such as central location tests or taste tests, where you also need to factor in transporting products for consumers to test in person. For this, it’s important to plan ahead so you can anticipate problems and delays that might not exist in your home market.

Legal

In many parts of the world, there are laws and regulations in place that you’ll need to consider when designing your research approach. For example, Europe’s GDPR or Singapore’s PDPA.

(More information on the challenges of global market research and how to overcome them can be found in this article).

The right way to do global market research

Learn as much as possible about the regions you’re targeting

Before you start actually speaking to people and conducting market research, it’s essential to gain a thorough understanding of the region you’ll be working in. This helps avoid or mitigate many of the cultural and linguistic challenges mentioned above.

Find out as much as possible about the demographics, laws, culture, language etc of your chosen region. Publicly available resources can help with this. You may be able to access government statistics or reports that can give an illuminating view of the business landscape for companies in your industry in your chosen market and what other firms are doing. This can provide you with a solid base for your research before you even start talking to your target audience.

Design an effective research approach, rooted in your understanding of the market

You need to design a research approach that works in the context of the market. Every region of the world is different, sometimes in quite startling ways, from your domestic market. It’s important to make sure your research is designed in a way that reflects that.

This is important when you’re considering what methodology to use. For instance, you’ll need to ensure that if you’re conducting online research in China, the platform will need to be mobile-first due to the technological leapfrog the country has  experienced. 

(For more information about conducting online research in Asia, read our best practice guide)

It’s also important when thinking about sampling. For example, when conducting research in Vietnam, it’s essential to understand the striking cultural differences between North and South. People in the North tend to favour well-known brands, whereas those in the South are typically more open to new experiences,Make sure you think carefully about who you want to research at the outset, and if you are exploring an entire country, beware that these nuances do exist. 

One of the best ways to really immerse yourself is by working with an agency that has boots on the ground, and offices in the location you want to explore. This allows you to build a research strategy that is adapted to your new market, helping you to obtain valuable insights.

Collect the data and analyse the results, bringing cultural understanding to bear 

Once you’ve designed your approach, you’re ready to embark on the research itself. 

There are multiple methods you can use here, such as:

  • In-person interviews
  • Online surveys
  • Focus groups
  • Online or mobile research 

Each method has its own pros and cons, and the best research strategies will contain a blend of several approaches. Again, cultural understanding is really important here. 

This can impact the way you approach every element of your research. For example, when writing a questionnaire in Japan, it’s important to acknowledge the cultural aversion to giving negative feedback. Here, if you used a typical 5-point Likert scale, responses might tend to end up right in the middle, giving an unhelpful result. Instead, try a 4-point scale to give a clear indication of attitudes or intent. 

The next step is analysis, where again, a deep understanding of the market is critical to be able to properly interpret the results and to compare between countries. In Vietnam, for instance, it’s common for Vietnamese respondents to show high interest levels when asked about their likelihood to purchase a product. But these responses are not always realistic — many Vietnamese people will enthusiastically signal their desire to buy a product even when they don’t have the economic means to realistically do so. It’s important to cross-reference these results with other market data for a more reliable result. 

Remember to account for translation or working with native speakers at this point to ensure success too.

Looking to embark on a global market research project?

Global market research is an essential process for any company looking to expand into different international markets or grow their presence in existing ones. It allows you to optimize your chances of success when trying new things in markets that may be profoundly different from your domestic market in numerous ways. It also helps you understand those markets much more keenly so you can better serve your customers there.

There are lots of variables that can make the research process for global market research projects much more challenging. It’s important to take the time to understand your new market before you begin the research process.

However, if done right, global market research can be a critical factor in mounting a successful market entry attempt, marketing campaign, or product launch allowing you to expand your brand across the world and reach entirely new levels of growth.
At Kadence, we help businesses all over the world expand into new global markets by carrying out in-depth and localised research. Contact us to find out more about how we can help you do the same.

Quantitative research is an important part of market research that relies on hard facts and numerical data to gain as objective a picture of people’s opinions as possible.

It’s different from qualitative research in a number of important ways and is a highly useful tool for researchers.

Quantitative research is a systematic empirical approach used in the social sciences and various other fields to gather, analyze, and interpret numerical data. It focuses on obtaining measurable data and applying statistical methods to generalize findings to a larger population.

Researchers use structured instruments such as surveys, questionnaires, or experiments to collect data from a representative sample in quantitative research. The data collected is typically numerical values or categorical responses that can be analyzed using statistical techniques. These statistical analyses help researchers identify patterns, relationships, trends, or associations among variables.

Quantitative research aims to generate objective and reliable information about a particular phenomenon, population, or group. It aims to better understand the subject under investigation by employing statistical measures such as means, percentages, correlations, or regression analyses.

Quantitative research provides:

  • A quantitative understanding of social phenomena.
  • Allowing researchers to make generalizations.
  • Predictions.
  • Comparisons based on numerical data.

It is widely used in psychology, sociology, economics, marketing, and many other disciplines to explore and gain insights into various research questions.

In this article, we’ll take a deep dive into quantitative research, why it’s important, and how to use it effectively.

How is quantitative research different from qualitative research?

Although they’re both extremely useful, there are a number of key differences between quantitative and qualitative market research strategies. A solid market research strategy will make use of both qualitative and quantitative research.

  • Quantitative research relies on gathering numerical data points. Qualitative research on the other hand, as the name suggests, seeks to gather qualitative data by speaking to people in individual or group settings. 
  • Quantitative research normally uses closed questions, while qualitative research uses open questions more frequently.
  • Quantitative research is great for establishing trends and patterns of behavior, whereas qualitative methods are great for explaining the “why” behind them.

Why is quantitative research useful?

Quantitative research has a crucial role to play in any market research strategy for a range of reasons:

  • It enables you to conduct research at scale
  • When quantitative research is conducted in a representative way, it can reveal insights about broader groups of people or the population as a whole
  • It enables us to easily compare different groups (e.g. by age, gender or market) to understand similarities or differences 
  • It can help businesses understand the size of a new opportunity 
  •  It can be helpful for reducing a complex problem or topic to a limited number of variables
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Quantitative Research Design

Quantitative research design refers to the overall plan and structure that guides the collection, analysis, and interpretation of numerical data in a quantitative research study. It outlines the specific steps, procedures, and techniques used to address research questions or test hypotheses systematically and rigorously. A well-designed quantitative research study ensures that the data collected is reliable, valid, and capable of answering the research objectives.

There are several key components involved in designing a quantitative research study:

  1. Research Questions or Hypotheses: The research design begins with clearly defined research questions or hypotheses articulating the study’s objectives. These questions guide the selection of variables and the development of research instruments.
  2. Sampling: A critical aspect of quantitative research design is selecting a representative sample from the target population. The sample should be carefully chosen to ensure it adequately represents the population of interest, allowing for the generalizability of the findings.
  3. Variables and Operationalization: Quantitative research involves the measurement of variables. In the research design phase, researchers identify the variables they will study and determine how to operationalize them into measurable and observable forms. This includes defining the indicators or measures used to assess each variable.
  4. Data Collection Methods: Quantitative research typically involves collecting data through structured instruments, such as surveys, questionnaires, or tests. The research design specifies the data collection methods, including the procedures for administering the instruments, the timing of data collection, and the strategies for maximizing response rates.
  5. Data Analysis: Quantitative research design includes decisions about the statistical techniques and analyses applied to the collected data. This may involve descriptive statistics (e.g., means, percentages) and inferential statistics (e.g., t-tests, regression analyses) to examine variables’ relationships, differences, or associations.
  6. Validity and Reliability: Ensuring the validity and reliability of the data is a crucial consideration in quantitative research design. Validity refers to the extent to which a measurement instrument or procedure accurately measures what it intends to measure. Reliability refers to the consistency and stability of the measurement over time and across different conditions. Researchers employ pilot testing, validity checks, and statistical measures to enhance validity and reliability.
  7. Ethical Considerations: Quantitative research design also includes ethical considerations, such as obtaining informed consent from participants, protecting their privacy and confidentiality, and ensuring the study adheres to ethical guidelines and regulations.

By carefully designing a quantitative research study, researchers can ensure their investigations are methodologically sound, reliable, and valid. 

Well-designed research provides a solid foundation for collecting and analyzing numerical data, allowing researchers to draw meaningful conclusions and contribute to the body of knowledge in their respective fields.

Quantitative research data collection methods

When collecting and analyzing the data you need for quantitative research, you have a number of possibilities available to you. Each has its own pros and cons, and it might be best to use a mix. Here are some of the main research methods:

Survey research

This involves sending out surveys to your target audience to collect information before statistically analyzing the results to draw conclusions and insights. It’s a great way to better understand your target customers or explore a new market and can be turned around quickly. 

There are a number of different ways of conducting surveys, such as:

  • Email — this is a quick way of reaching a large number of people and can be more affordable than the other methods described below.
  • Phone — not everyone has access to the internet so if you’re looking to reach a particular demographic that may struggle to engage in this way (e.g. older consumers) telephone can be a better approach. That said, it can be expensive and time-consuming.
  • Post or Mail — as with the phone, you can reach a wide segment of the population, but it’s expensive and takes a long time. As organizations look to identify and react to changes in consumer behavior at speed, postal surveys have become somewhat outdated. 
  • In-person — in some instances it makes sense to conduct quantitative research in person. Examples of this include intercepts where you need to collect quantitative data about the customer experience in the moment or taste tests or central location tests, where you need consumers to physically interact with a product to provide useful feedback. Conducting research in this way can be expensive and logistically challenging to organize and carry out.

Survey questions for quantitative research usually include closed-ended questions rather than the open-ended questions used in qualitative research. For example, instead of asking

“How do you feel about our delivery policy?”

You might ask…

“How satisfied are you with our delivery policy? “Very satisfied / Satisfied / Don’t Know / Dissatisfied / Very Dissatisfied” 

This way, you’ll gain data that can be categorized and analyzed in a quantitative, numbers-based way.

Correlational Research

Correlational research is a specific type of quantitative research that examines the relationship between two or more variables. It focuses on determining whether there is a statistical association or correlation between variables without establishing causality. In other words, correlational research helps to understand how changes in one variable correspond to changes in another.


One of the critical features of correlational research is that it allows researchers to analyze data from existing sources or collect data through surveys or questionnaires. By measuring the variables of interest, researchers can calculate a correlation coefficient, such as Pearson’s, to quantify the strength and direction of the relationship. The correlation coefficient ranges from -1 to +1, where a positive value indicates a positive relationship, a negative value indicates a negative relationship and a value close to zero suggests no significant relationship.

Correlational research is valuable in various fields, such as psychology, sociology, and economics, as it helps researchers explore connections between variables that may not be feasible to manipulate in an experimental setting. For example, a psychologist might use correlational research to investigate the relationship between sleep duration and student academic performance. By collecting data on these variables, they can determine whether there is a correlation between the two factors and to what extent they are related.

It is important to note that correlational research does not imply causation. While a correlation suggests an association between variables, it does not provide evidence for a cause-and-effect relationship. Other factors, known as confounding variables, may be influencing the observed relationship. Therefore, researchers must exercise caution in interpreting correlational findings and consider additional research methods, such as experimental studies, to establish causality.

Correlational research is vital in quantitative research and analysis by investigating relationships between variables. It provides valuable insights into the strength and direction of associations and helps researchers generate hypotheses for further investigation. By understanding the limitations of correlational research, researchers can use this method effectively to explore connections between variables in various disciplines.

Experimental Research

Experimental research is a fundamental approach within quantitative research that aims to establish cause-and-effect relationships between variables. It involves the manipulation of an independent variable and measuring its effects on a dependent variable while controlling for potential confounding variables. Experimental research is highly regarded for its ability to provide rigorous evidence and draw conclusions about causal relationships.

The hallmark of experimental research is the presence of at least two groups: the experimental and control groups. The experimental group receives the manipulated variable, the independent variable, while the control group does not. By comparing the outcomes or responses of the two groups, researchers can attribute any differences observed to the effects of the independent variable.

Several key components are employed to ensure the reliability and validity of experimental research. Random assignment is a crucial step that involves assigning participants to either the experimental or control group in a random and unbiased manner. This minimizes the potential for pre-existing differences between groups and strengthens the study’s internal validity.

Another essential feature of experimental research is the ability to control extraneous variables. By carefully designing the study environment and procedures, researchers can minimize the influence of factors other than the independent variable on the dependent variable. This control enhances the ability to isolate the manipulated variable’s effects and increases the study’s internal validity.

Quantitative data is typically collected in experimental research through objective and standardized measurements. Researchers use instruments such as surveys, tests, observations, or physiological measurements to gather numerical data that can be analyzed statistically. This allows for applying various statistical techniques, such as t-tests or analysis of variance (ANOVA), to determine the significance of the observed effects and draw conclusions about the relationship between variables.

Experimental research is widely used across psychology, medicine, education, and the natural sciences. It enables researchers to test hypotheses, evaluate interventions or treatments, and provide evidence-based recommendations. Experimental research offers valuable insights into the effectiveness or impact of specific variables, interventions, or strategies by establishing cause-and-effect relationships.

Despite its strengths, experimental research also has limitations. The artificial nature of laboratory settings and the need for control may reduce the generalizability of findings to real-world contexts. Ethical considerations also play a crucial role in experimental research, as researchers must ensure participants’ well-being and informed consent.

Experimental research is a powerful tool in the quantitative research arsenal. It enables researchers to establish cause-and-effect relationships, control extraneous variables, and gather objective numerical data. Experimental research contributes to evidence-based decision-making and advances knowledge in various fields by employing rigorous methods.

Analyzing results

Once you have your results, the next step — and one of the most important overall — is to categorize and analyze them.

There are many ways to do this. One powerful method is cross-tabulation, where you separate your results into categories based on demographic subgroups. For example, of the people who answered ‘yes’ to a question, how many of them were business leaders and how many were entry-level employees?

You’ll also need to take time to clean the data (for example removing people who sped through the survey, selecting the same answer) to make sure you can confidently draw conclusions. This can all be taken care of by the right team of experts.

The importance of quantitative research

Quantitative research is a powerful tool for anyone looking to learn more about their market and customers. It allows you to gain reliable, objective insights from data and clearly understand trends and patterns.

Where quantitative research falls short is in explaining the ‘why’. This is where you need to turn to other methods, like qualitative research, where you’ll actually talk to your audience and delve into the more subjective factors driving their decision-making.


At Kadence, it’s our job to help you with every aspect of your research strategy. We’ve done this with countless businesses, and we’d love to do it with you. To find out more, get in touch with us.

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Survey design is an important part of doing business and market research. Put simply; it refers to the process of creating surveys that get responses.

This is important because it allows you to better understand the market and your customers, so you can make more data-driven decisions and fix areas that are falling short. Done right, a good survey can be the driving force for huge positive change.

How to design a survey

Planning

The first stage of survey design is all about planning. This is where you’ll decide what you want to focus on, why you’re running a survey at all, who you want to target, and more.

If you don’t get this stage right, you’ll end up with a survey that doesn’t have any clear goals or fails to achieve its objectives. To get meaningful feedback from a survey, you must be clear about what you’re trying to achieve.

This initial stage is extremely important and is not something to skim over or rush through. In fact, the planning stage should take up a large chunk of the overall process.

1. Figure out your goals

The goal of the survey is what gives it structure and influence every part of the process. Here are some examples of goals for surveys:

  • Find out what customers think about your brand versus the competition 
  • Assess the main challenges faced by customers in your industry
  • Learn what customers like the most and least about a specific product.

Goals should typically be narrow enough that there is no risk of confusing your stakeholders or your respondents. Narrow goals also avoid overwhelming your respondents with questions.

A clearly defined goal helps the team draw inspiration and stay united and focused. Once you have decided on a goal, you’ll have a much better idea of what type of questions to ask, the type of respondents you want to reach, and so on.

In other words, you need to set a goal in order for the rest of the process to click into place.

2. Decide who you want to target with your survey

The next stage of the planning process involves deciding who will actually take part in your survey. 

This is called the target population, and it should reflect the goal. For example, if you’re asking how your product impacts a person’s job, it’s probably not a good idea to target people under 16 or people over 70 as they are unlikely to be working.

3. Choose the right sample

The target population you choose will often be too large to effectively survey. This means you’ll have to select a sample — a smaller group that represents the larger demographic. You can then take these results and extrapolate them to the wider population.

Done right, this group will be representative enough to act as a miniature version of the whole. Sampling allows you to achieve your goals with a fraction of the cost, time, and resources required to survey the entire target population, which in most cases, would simply not be possible.

4. Pick the right survey method

This stage of the planning process will be driven by your goal and your target demographic. Some examples of different methods include:

Every method has its pros and cons. Online surveys enable you to reach a large number of people quickly, but they’re less appropriate if you’ve got a physical product you want people to interact with. Instead, a central location test might be more appropriate in this instance.

Every survey is different. If your target population is mostly people over the age of 65 or in geographical locations where internet access is not widespread, online surveys will probably not be the best method. Likewise, a central location test might not work well if your target demographic is very busy.

Once you have decided on a goal, established a target population and a sample, and chosen the method for your survey, it’s time to get down to actually creating it.

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Creating your survey

Creating your survey is all about making it as easy as possible for your respondents to read, understand, and answer. If you overwhelm them with information and confusing formats, they’ll quickly give up and you’ll end up with fewer answers and a smaller pool of data at the end.

Here are some ways to make your survey as effective as possible:

How to write effective survey questions

Writing good survey questions is essential to gather accurate and meaningful data. You need to ask enough to gather a good amount of information, but if you use too many, you risk driving your respondents away.

It’s always best to start with a clear introduction that introduces the survey, explains the format, and addresses any initial questions the reader might have. You might then start with some screener questions (about age or job title, for example) to filter out any respondents who don’t match the target demographic.

Here are some guidelines to help you write effective survey questions:

  1. Define your objectives: Identify the purpose of your survey and the specific information you want to gather. This will help you frame your questions appropriately.
  2. Keep it concise: Make your questions clear, concise, and concise. Avoid using complex or technical language that may confuse respondents. Use straightforward language.
  3. Avoid leading questions: Avoid questions that suggest a particular answer or influence respondents’ opinions. Use neutral language and focus on gathering unbiased responses.
  4. Use closed-ended and open-ended questions: Closed-ended questions offer respondents predefined answer choices (e.g., multiple-choice, Likert scale), making it easier to analyze the data quantitatively. Open-ended questions allow respondents to provide detailed and personal responses, offering qualitative insights.
  5. Use a mix of question types: A variety of question types can keep the survey engaging and provide different perspectives on the topic. Mix multiple-choice, rating scales, ranking, and open-ended questions to gather diverse data.
  6. Avoid double-barreled questions: Double-barreled questions simultaneously ask about two different things, confusing respondents and leading to inaccurate responses. Instead, ask separate questions to address each aspect.
  7. Order questions logically: Arrange your questions in a logical flow that makes sense to respondents. Start with easy, non-sensitive questions to build rapport and then move to more complex or personal questions.
  8. Pilot test your survey: Before launching your survey, conduct a pilot test with a small group of respondents to check for clarity, relevance, and potential issues. Make necessary revisions based on their feedback.
  9. Offer response options that cover all possibilities: Ensure that the response options for closed-ended questions cover all possible answers. Include an “Other” or “Not applicable” option if necessary.
  10. Avoid jargon and technical terms: Use language familiar to your target audience. Avoid industry-specific jargon or technical terms that may confuse respondents.
  11. Use scales consistently: If you use rating scales or Likert scales, ensure that the response options and scale labels are consistent throughout the survey. Clearly define the meaning of each point on the scale.
  12. Consider the order bias: The order of questions can influence responses. Be mindful of this bias and consider randomizing the order of answer options or questions to minimize its impact.
  13. Test for survey length: Long surveys can lead to respondent fatigue and higher dropout rates. Keep your survey as concise as possible while still capturing the necessary data.
  14. Offer anonymity and confidentiality: Assure respondents that their responses will remain anonymous and confidential. This encourages honest and accurate answers, especially for sensitive topics.
  15. Review and revise: Proofread your survey questions for clarity, grammar, and spelling errors. Take the time to review and revise the questions to ensure they accurately reflect your objectives.

Following these guidelines, you can create well-crafted survey questions that generate reliable and meaningful data for your research or analysis.

Executing the survey

Once the survey is planned and created, it’s time to implement it. If you have done the earlier stages correctly, this part should run smoothly. However, in practice, errors and unexpected setbacks are common. Here’s how to execute your survey in the best way possible:

Work with trained researchers

If your survey will be carried out in person or on the telephone, it’s important that your staff know how to write survey questions. Ensure you’re working with a team trained to ask open-ended questions correctly in a way that avoids confusion or tempts bias.

Pilot surveys

A common practice is to conduct a smaller pilot survey before the main one, which can help identify any problems with the survey and give you an opportunity to make some tweaks before sending it to the full sample group.

Avoiding bias

One of the main challenges when conducting surveys is bias. It’s easy to accidentally lead your respondents down a certain path and encourage them to answer in a certain way, which you must avoid in order to get accurate and valuable results. To minimize bias:

  • Avoid leading questions like comparisons with other companies or products
  • Keep questions as precise and simple as possible to eliminate the risk of misunderstanding
  • Try to predict inherent biases in your target group and work to mitigate them

Analyzing and sharing results

After the survey is complete, the final steps are to analyze and share the results. This is an extremely important step, as this is where you put into practice what you learned and draw value from the survey.

It’s important to categorize and analyze the results properly. This process might be as simple as collecting the results in an Excel spreadsheet, or it might be much more detailed, using a range of advanced analysis techniques..

Think about how the survey relates to your overall business and marketing and how you can act on the insights you gained and use them to achieve your goals.

Create a summary report

A summary survey report is a great way to share your results with your stakeholders in the business. It’s a document that breaks down what your survey set out to achieve and the key findings. We regularly create summary reports, as well as longer, more detailed reports for our clients. 

Make sure to clearly show what your aims were and what you learned, and present this in a way that anyone – regardless of market research literacy – can get to grips with. It’s worth working with a good designer to present the findings in the best way possible. At Kadence, we have our own design team who help us to create impactful reports that make data easy to understand and act upon.

Survey design can seem like a challenging process, and it does require input and collaboration from many parts of the company.

However, the rewards are worth it. A well-designed survey can provide a much more intimate understanding of your customer base and how your products and services are received. It can yield incredibly valuable feedback and prompt much-needed change.

To find out how Kadence can help your organization plan more effective surveys and harness data for maximum effect, reach out to request a proposal.

Conjoint analysis is often lauded as an extremely effective way to gain detailed insights and conduct market research, but how does it work?

Essentially, conjoint analysis is a method of measuring the value that customers place on different features of an existing or new product. It typically works via a survey, which looks something like this:

Participants are shown a combination of features (called attributes) for a product. If the product is a smartphone, for example, they might be shown the price, memory size, screen resolution, and camera quality. They’re then asked to compare different attributes. For example, what would they choose between a $150 phone and a $250 phone? Do they prefer 32GB of memory or 64GB? There are several ways to structure this, as we’ll find out. After the answers have been collected, we analyze the results to inform the right marketing decisions.

Conjoint analysis is a powerful market research method used to analyze and understand customer preferences. It is particularly valuable in assessing product attributes and their impact on consumer decision-making. In this blog post, we’ll delve deeper into the different types of conjoint analysis and the various benefits it can deliver.

Why Do Conjoint Analysis?

By examining various factors such as product features, price, brand, and packaging, conjoint analysis provides insights into how different attributes influence the target audience’s choices. This market research method proves especially beneficial in different stages of the product life cycle, from initial business analysis and product design to the product launch and beyond.

Conjoint analysis aids great product managers, designers, and project managers in making informed decisions by identifying the optimal combination of features and attributes that resonate with the target audience. It leverages research techniques like mail surveys, personal interviews, focus groups, and telephone surveys conducted by skilled survey researchers to gather data on consumer preferences and opinions. This valuable information helps development teams refine and optimize the final product, ensuring it meets customer needs and expectations.

Additionally, conjoint analysis provides insights into the competitiveness of existing products and aids in strategic planning for future product enhancements or new offerings.

Reasons to Conduct Conjoint Analysis

There are several reasons to conduct a conjoint analysis, including:

  • To measure and understand customer preferences for certain product features.
  • To assess or predict how well a new product will do if brought to market.
  • To gain an understanding of how changes in price affect demand.
  • To predict future trends, for example, around the adoption of certain features.

How to Conduct Conjoint Analysis

Choose the Right Survey Type

The first stage is to decide on the correct survey type. There are several ways to do a conjoint analysis — here are the main methods:

  1. Ratings-based conjoint analysis: This is where participants give each attribute a rating, for example, on a scale of 1-100.
  2. Ranking-based conjoint analysis: This is where participants rank the attributes in order from best to worst. There is also a best vs. worst analysis, where participants simply pick their favorite and least favorite attributes from the selection.
  3. Choice-based conjoint analysis (CBC): This is the most commonly used model and the one this guide will focus on. It presents combinations of attributes to participants and asks them to choose which they prefer.

One of the most powerful advantages of choice-based conjoint analysis is that it can allow you to use modeling to predict how customers will feel about combinations they didn’t even assess. In other words, it is an extremely efficient way of predicting responses to features without having to spend a huge amount of time testing each combination.

Identify the Relevant Attributes (Features)

Next, it’s time to decide which product attributes you want to have your respondents compare and assess. The key is not to use too many. We typically avoid using more than 5 or 6 attributes, e.g., for a car: color, engine size. We do this to reduce respondents’ cognitive load to ensure they engage with the choices presented to them.

For each attribute, you need to add levels. For example, if your participants are assessing a smartphone, one attribute might be ‘price,’ and the levels might be $200, $350, and $700.

The levels will usually reflect the different tiers of the product you’re considering selling. For the smartphone, you might be releasing a basic model, a higher-end model, and a deluxe model. The levels for attributes such as price, camera size, and memory will align with those tiers.

Levels should be chosen based on factors like:

  • How interesting and valuable they are for management — will they inform useful decisions?
  • How well they avoid bias?
  • How realistic they are.

In the CBC method, there are two commonly used models for making choices:

  • Single choice with none: This requires the participant to make one choice out of the selection. There is also the possibility to select none of the options.
  • Single choice: This is the same as above, but there is no ‘none’ option — the participant has to pick one.

Design the Questionnaire

Screener Questions

Most surveys start with some screener questions. These are general questions around demographics like the respondent’s age, job title, or purchase habits. The goal is to filter out those who won’t be a good fit for the survey based on the people you’re trying to target.

Introduce and Explain

It’s important to take some time at the beginning of the survey and in your questions to clearly explain what the respondents need to do to answer the questions. Surveys should be as clear and easy to follow as possible.

Create the Right Questions

The questions you choose and how you structure them will make or break your survey. Here are some guidelines to follow:

  • Questions should follow one another logically and be grouped together intuitively. It’s best not to confuse your participants by ordering your questions in a confusing way.
  • People often give more accurate and useful answers when you use situational questions. For example, instead of asking, “Which phone would you buy?” ask something like, “Thinking back to the last time you purchased a phone — if you had the following options instead, which would you have picked?”
  • Finish with some demographic questions so that you can further understand your customer base and analyze the results by demographic to understand any meaningful differences.

Analyze and Take Action

Once the survey has been written, scripted, sent out, and completed by your target group, it’s time to analyze the results and take action on them. This is perhaps the most important part of the process, as it’s where your research can really make a tangible impact.

There are several ways to analyze your results based on how you designed the survey. The most important thing is to collect and analyze your data in a way that makes it easy to draw useful conclusions and share them.

This will allow you to gain real value from the survey and present those findings to others in the company. This:

  • Helps justify your decisions and actions.
  • Informs future plans and inspires new features.
  • Identifies areas that need to change or improve.

At Kadence, it’s our job to ensure you create and conduct the most effective surveys and market research possible, giving your brand the edge. To find out more about how we can help with conjoint analysis and more, get in touch to request a proposal.

Conclusion

Conjoint analysis is a valuable tool in understanding consumer preferences and making informed product development decisions. By carefully designing and executing your surveys, you can gain insights that drive strategic planning and optimize your products to meet market demands. Whether you’re evaluating new product features, pricing strategies, or competitive positioning, conjoint analysis can provide the detailed insights needed to succeed in today’s competitive market landscape.

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