Brands have popularly used rating scales to collect customer feedback on product or service reviews. Rating scale questions are so easy to recognize and understand that sometimes respondents don’t even need to read the question. We see smiley ratings or star ratings and immediately know what to do.

In this blog, we’ll discuss in detail the different types of rating scales and how you can use them in your surveys to collect customer feedback.

What is a Rating Scale?

Rating scales are among the most common survey question types used for online and offline surveys. They are close-ended questions with a set of categories as options for respondents. Rating scales help gather information on qualitative and quantitative attributes.

The most common examples of rating scales are the Likert scale, star rating, and slider. For example, when you visit an online shopping site, you see a rating scale question when it asks you to rate your shopping experience.

It is a popular choice for conducting market research. It can gather more relative information about a product or certain aspects of the product. The scale is commonly used to gain quantifiable feedback. It can be used to gain insight into a product’s performance, employee satisfaction or skill, customer service performance, etc.

What Are the Two Categories of the Rating Scale?

Rating scales can be classified into two categories: ordinal scale and interval scale. Some data are measured at the ordinal level and some at the interval level.

1. Ordinal Scale

An ordinal scale gathers data by putting them in a rank without a degree of difference.

2. Interval Scale

An interval scale measures data with an equal distance between two adjacent attributes.

Robust online survey tools should allow you to create interactive surveys with rating questions to keep the respondents engaged.

Now that we have learned what it is and the two categories of the collected data, let’s look into the different types.

What are the types of rating scales?

You can use this type of scale in your survey in six different ways. These six scales gather data based on the categories mentioned above.

1. Numeric scale.
2. Verbal scale.
3. Slider scale.
4. Likert scale.
5. Graphic scale.
6. Descriptive scale.

We have explained these six rating scale types in detail to help you determine the right time to use the right question.

1. Numeric rating scale or NRS

A numeric rating scale uses numbers to identify the items in the scale. In this scale, not all numbers need an attribute attached to them.

For instance, you can ask your survey respondents to rate a product from 1 to 5 on a scale. You can assign ‘1’ as totally dissatisfied and ‘5’ as totally satisfied.

2. Verbal rating scale or VRS:

Verbal scales are used for pain assessment. Also known as verbal pain scores and verbal descriptor scale compiles a number of statements describing pain intensity and duration.

For instance, when you go to a dentist, you are asked to rate the intensity of your tooth pain. At that time, you receive a scale with items like “none,” “mild,” “moderate,” “severe,” and “very severe.”

3. Visual analog scale or Slider scale:

The idea behind VAS is to let the audience select any value from the scale between two endpoints. In the scale, only the endpoints have attributes allotted to numbers, and the rest of the scale is empty.

Often just called a slider scale, the audience can rate whatever they want without being restricted to particular characteristics or rank.

For example, a scale rating ranges from extremely easy to extremely difficult, with no other value allotted.

4. Likert scale:

A Likert scale is a useful tool for effective market research to receive feedback on a wide range of psychometric attributes. The agree-disagree scale is particularly useful when your intention is to gather information on frequency, experience, quality, likelihood, etc.

For example, a Likert scale is a good tool for evaluating employee satisfaction with company policies.

5. Graphic rating scale:

Instead of numbers, imagine using pictures, such as stars or smiley faces to ask your customers and audience to rate. The stars and smiley faces can generate the same value as a number.

6. Descriptive scale:

In certain surveys or research, a numeric scale may not help much. A descriptive scale explains each option for the respondent. It contains a thorough explanation for the purpose of gathering information with deep insights.

These are the six types of rating questions that you can use in your surveys to make it an engaging and fun experience for the survey takers.

How to create a rating scale survey?

While rating scale questions are simple to create and easy to understand, there are certain factors you need to be mindful of to ensure it doesn’t confuse the respondents. Let’s look at some tips to learn how you can create a rating survey.

1. Determine the scale –

The first step is identifying the right scale for your survey question and its scale points/response options. The scale should reflect the purpose of the research, and the scale points should resonate with the idea of the selected scale.

The aim is to ensure that the respondents can interpret the meaning and purpose of your rating questions easily and accurately.

2. Implement the right scale –

The six rating scale types should help you understand which rating scale you should use in your survey.

If you can’t determine which scale best fits the research, then consider running a test with the rating questions you wish to use. Evaluate the result to see which scale helps you collect the intended data.

3. Use a consistent rating scale –

Maintain consistency in your survey by using the same order/value in scale points. The best way to do this is by assigning the lowest end of the scale as 1 and the highest end as 5. This order is easy to follow as it shows that the more you move to the right, the bigger the numbers.

This not only helps your survey respondents but also allows for easier analysis.

4. Balance positive and negative options –

A balanced scale helps minimize response bias and non-response bias. This ensures that the respondent has the option to simply opt for the middle value and not show any priority. In contrast, for others, the security of the middle value influences them to provide honest opinions.

5. Let one question focus on one idea –

Prevent combining multiple concepts in a single question. This will confuse the respondents and muddle your result.

What are the advantages of using rating scales in surveys?

We have discussed the factors that contribute to the popularity of this question type, among others.

• It is a simple and easy-to-understand question type for both the researcher and the audience.
• It doesn’t take too much of the respondents’ time.
• There are various types of scales to help you create an engaging survey.
• In terms of marketing surveys, this scale is a valuable tool for data analysis. It can gain product review for evaluation and a further improvement in marketing strategy.

What are the disadvantages of rating scales?

Let’s also see the disadvantages of using this scale in surveys.

• It does not help collect the reason behind a customer review.
• It gets access to the overall experience but not the reason behind the audience’s perception.
• In the case of VRS, the scale may oftentimes overestimate the patient’s pain experience. In addition, patients with limited vocabulary may not understand the statements in a verbal descriptor scale.

When should you use the rating scale in your survey questionnaire?

The rating scale allows you to gather a large volume of quantifiable responses. The data you gather can help you identify patterns in feedback and determine what needs priority.

Here are a few instances where you can use rating scale questions in your survey:

#1 You can use it to gather information on a particular topic.

For example, you can use it in market research surveys to collect the following data:

• Customer reviews about an app they are using.
• Customer satisfaction with the delivery service of a courier company.
• Likelihood of recommending a café to a friend.
• Rate a list of brands from least to most favorite.

#2 You can use it to gather information about a service or product from the target audience for the purpose of comparison and analysis.

For instance, if you are planning to start a business, this type of scale will provide you with awareness of the current market demand. With the information gained, you can strategize your scheme.

#3 You can measure the frequency to assess how often a survey respondent engages in certain behaviors.

For instance, in healthcare research, you can use a rating scale to measure how frequently your patients partake in exercise or certain health behaviors.

#4 You can identify the importance and priority respondents assign to certain products.

For example, you can use it to understand your target market’s preference and level of importance for a product available in the market.

Examples of Rating Scale Survey Questions

Before we conclude our blog, let’s look at some rating question examples you can use in your survey questionnaires:

1. Customer Satisfaction Rating Scale Questions –

• How satisfied are you with the newly launched live customer support chat service on our app?
• How likely are you to refer our podcast app to others?

2. Product feedback Rating Scale Questions–

• Rate the quality of our latest product. (1- poor and 5 – excellent)
• How easy was it to use the new doc scanner app?

3. Event Experience Rating Scale Questions–

• How would you rate the organization of our music festival event? (1-poorly organized, 5- extremely well organized)
• How likely are you to attend our summer event in the future?

Wrapping up;

This sums up all you need to know about rating scales. However, here are some tips to ensure that your scale questions are easy to understand for the audience.

1. Assign clear and precise labels to the endpoints of your scale.
2. Avoid response bias by including both endpoints in your question ( satisfied/dissatisfied, easy/not easy, likely/not likely, etc.).
3. It’s better to make ‘1’ the negative and the other end ‘5’ or ‘10’ as the positive point.
4. Use odd scales to offer a neutral point for the audience.

Various rating scale question types are available in Voxco’s market research software, each serving a different purpose. Hence, before selecting a scale, it is important to figure out the purpose of the survey and the kind of information you wish to gain.

Research design is a blueprint for your entire research process. It helps you seamlessly navigate through the complexities of sampling, data collection, analysis, and interpretation. Whether you are venturing into the world of social sciences or conducting market research, understanding the elements and intricacies of the methodologies behind research will help you conduct the study with more clarity and confidence.

In this blog, we’ll explore the characteristics and types of research methodology to help you understand how to design your research process.

What is research design?

According to the definition of research design, it refers to the framework of market research methods and techniques that are chosen by a researcher. The design that is chosen by the researchers allow them to utilise the methods that are suitable for the study and to set up their studies successfully in the future as well.

Research design offers a variety of options. It can be qualitative, quantitative, or mixed. Under these designs, researchers can choose from various research methods such as experimental studies, surveys, correlational studies, or quasi-experimental review studies. There are also sub-types of research methods including experimental design, defining research problems, and descriptive studies.

Research designs are influenced by the research problem a company chooses to work on. This problem serves as the determining factor in the choice of research design, highlighting the logical sequence of steps in conducting a research study.

The market research study’s design phase is when the researchers determine the tools to be used and how they will be used. Good research usually ensures minimum levels of bias in the data collection method to improve both the internal and external validity of the research. The desired outcome of experimental research is to have a design that will result in the least amount of error in the study.

What are the elements of research design?

Some essential elements of research designs are highlighted below:

1. Research purpose:

A research design cannot be decided without an accurate purpose or problem statement.

2. Appropriate sampling:

This includes determining the appropriate sampling methods, correct sample size, and key characteristics of the population. Tools like a market research panel can simplify this step by giving you access to vetted and willing survey participants.

3. Data collection methods:

The process of gathering data from participants is a critical element of research design. This step involves selecting what data to collect, the right mode of data collection, and the tools used (be it card sorting tools, or other tools) for the purpose. Voxco offers three modes of data collection - online, CATI, and mobile-offline.

4. Data analysis:

Research designs include data analysis and interpretation. This element includes deciding which statistical method to use to analyze the data to mitigate any error or bias in research results.

5. Types of methodology:

This step includes determining the best among the several types of research methodology. Different research designs require different settings for the conduction of a study.

6. Setting up time frame:

Another element is to outline the general timeline it will take to conduct a study using different research methods.

7. Integrity:

Using an accurate research design will help your study be successful. Research studies that are successful and include the least amount of error provide important insights that are free of bias.

8. Ethical considerations:

It must also ensure adhering to ethical considerations such as informed consent, confidentiality, and anonymity.

What are the main characteristics of research design?

To better understand how you can design your own research process, let’s take a look at the main characteristics of the subject.

01. Neutrality before research initiation:

When you are planning to study a phenomenon, you may have an assumption about the kind of data you are expecting to collect. However, the results you find from the study should not be driven by bias and must be neutral. In order to understand the opinions on the obtained results, you can discuss it with multiple people and consider the points made by individuals who agree with the results obtained.

02. Reliability of research design:

When you replicate an already conducted market research, you expect similar results. Decide the type of research questions you are going to ask through your surveys and define that in your research design. This will help set a standard for the results. Only if your design is reliable it will help you obtain the expected results.

03. Validity of insights:

You need to ensure that the survey questionnaire you are using is valid. Validity refers to the fact that the research tool you use measures what it purports to measure. Only valid tools will help researchers in gathering accurate results for their study.

04. Generalizability of research findings:

The outcome of your research design should be generalizable to a wider population. Good research design findings are generalizable to everyone, and they indicate that if your survey were to be replicated on any subgroup of the population, it would yield similar results.

A good research design balances all the above characteristics. Researchers must also understand the different research design types to choose from. This understanding will help them implement the most accurate research design for their study.

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What are the different types of research design?

Broadly, there are two types of research design types:

1. Qualitative research design
2. Quantitative research design

Quantitative Research Design:

Quantitative research is the process of collecting and analyzing numerical data. It is generally used to find patterns, averages, predictions, and cause-effect relationships between the variables being studied. It is also used to generalize the results of a particular study to the population in consideration.

Quantitative research is widely used in science, both in the natural and social sciences. It provides actionable insights that are essential for company growth.

Qualitative Research Design:

Qualitative research is a method used for market research that aims to obtain data through open-ended questions and conversations with the intended consumers.

This method aims to establish not only “what” people think but also “how” they came to that opinion and “why” they think so.

What are the subtypes of research design?

We can further explore research design in five sub-types based on the objective, methodology, and focus.

01. Descriptive research design

Descriptive research refers to the methods that describe the characteristics of the variables under study. This methodology focuses on answering questions relating to “what” than the “why” of the research subject. The primary focus of descriptive research is to simply describe the nature of the demographics under the study instead of focusing on the “why”.

Descriptive research is called an observational research method, as none of the variables in the study are influenced during the research process. If the problem is unclear enough to conduct a descriptive analysis, researchers can use exploratory research methods first.

02. Experimental research design

Experimental research, also called experimentation, is conducted using a scientific approach with two or more variables. The first variable is a constant that can be manipulated to see the differences caused by the second variable. Most studies using quantitative research methods are experimental in nature.

Experimental research helps you in gathering the necessary data for you to make better decisions about your proposed hypothesis. The success of experimental research usually confirms that the change observed in the variable under study is solely based on the manipulation of the independent variable.

Experimental research design is the most practical and accurate kind of research method that helps establish causation. This research design is used in social sciences to understand and observe human behavior. The behavior is observed by placing humans in two groups so that researchers can make comparisons.

03. Correlational research design

A correlation refers to an association or a relationship between two entities.

Correlational research studies how one entity impacts the other and what are changes are observed when either one of them changes. This research method is carried out to understand naturally occurring relationships between variables.

Hence, at least two groups are required to conduct correlational quantitative research successfully. The variables in this study are not under the researcher's control; the researcher is simply trying to establish whether or not a relationship between two variables exists.

Since correlational studies only explain whether there is a relationship between two groups, they do not establish causation. Thus, it is not recommended to draw conclusions solely based on correlational studies; just because two variables are in sync does not mean they are interrelated or that one variable is causing the changes in the other variable!

A numeric correlation coefficient determines the strength of the relationship between two variables and ranges from -1 to +1. If the correlation coefficient obtained is -1, it indicates a perfect negative relationship between the two variables, i.e., as one variable increases (age), the other variable decreases (purchase of sports products).

If the correlation coefficient of a study is found to be +1, it indicates a perfect positive relationship between the two variables, whereas one variable increases (age) and the other variable also increases (purchasing beauty-enhancing products).

04. Diagnostic research design

In a diagnostic research design, the researcher is trying to evaluate the cause of a specific problem or phenomenon.

This research design is used to understand more in detail the factors that are creating problems in the company. Diagnostic research design includes three steps:

Step -1: The inception of the issue – When did the issue arise? In what situations is the issue more evident?

Step -2: Diagnosis of the issue – What is the underlying cause of the issue? What is influencing the issue to worsen?

Step -3: Solution for the issue – What is working in curing the issue? Under what situations does the problem seem to become less evident?

05. Explanatory research design

Explanatory research design uses the ideas and thoughts of a researcher on one subject to be the guiding point for future studies, it is also used in exploring theories further. The research focuses on explaining the unexplored patterns of phenomena and elaborates on the details pertaining to the research questions such as; what, why, and how.

Conclusion

A clear research design provides a direction guiding your process with a clear objective and questions to investigate the topic of interest. Research design ensures the validity and reliability of the research findings and confirms that one can replicate the result even for future research. An appropriately created and executed research design helps you draw meaningful conclusions.

What is Convenience Sampling?

A type of non-probability sampling, Convenience Sampling involves collecting samples from the population that is closer to the researcher. It is also known as accidental sampling, opportunity sampling, or grab sampling because the researcher can use the respondents who are conveniently available at the researcher’s reach. Convenience sampling can be used in the best market research tools available.

Gathering samples from the entire community is not always possible, at those times researchers use convenience sampling. The process is uncomplicated, prompt, and because it uses an audience of close contact, it is economical as well.

The sample includes people who are in the researcher’s close proximity such as workplace, school, club, apartment complex, etc. The factor that whether the sample represents the entire population is not taken under consideration. However, with this sampling technique, you can gather opinions, habits, reviews, etc. in an easy and simple way.

Examples of Convenience Sampling

In business and Market research, convenience sampling provides data from the perspective of the audience about the brand image and reputation. It is also used to obtain opinions about newly launched products or on a small-scale project.

• Let’s say a student is planning to open a food truck outside a college campus. They need to collect opinions based on the student’s choice of food to create their menu. The student will ask their friends and other students around campus to collect the data. margin of error calculator.
• You may have come across people outside a mall or convenience store with pamphlets and questionnaire surveys. This is also an example of a convenience sample, the people with pamphlets ask the people on the street to participate in the survey. The researcher may not know these people but they are available within their reach at the moment. You can use paper surveys or a mobile offline survey software.
• You need to create an online survey on the best mobile phones and the desired feature for your online blog. You create a survey with relevant questions and send them to your email and phone contact and share the link on your social media accounts. This way people from your daily contact can respond to the survey and you can gather the data in an easy manner.

When can you use Convenience Sampling?

Convenience sampling has certain issues, such as you cannot generalize the result to a larger population. However, in some cases, it is the only option that can give you the result. Sometimes, it is the only method when you cannot get a list of respondents or a large population. Convenience sampling is easy to conduct. Also when you need results in a short time and have a low budget, it is the method that can save you.

For instance, if your company has 3 offices and you are conducting a survey on how the employees feel about their wages. It is not possible for you to go through the entire body of employees of all the 3 offices. So, you grab the employee in your office and the ones you come across to conduct the survey. Hence, the alternate name, ‘grab sampling’.

In American universities, the convenience sampling survey method was used to understand the association between perceptions of unethical consumer behavior with demographic factors. Understand how to collect relevant information using demographic survey template.

What are the advantages of using Convenience Sampling?

Provides results quickly:

In cases when time is limited and you need to collect data fast, convenience sampling is used by many researchers. The simplicity factor of this non-probability sampling makes it a quick and easy procedure, unlike other non-probability samplings.

Cheap method of sampling:

Money is another factor it saves. A researcher includes the people who are in close proximity to the researcher, hence it is a cost-effective market research tool. The researcher can generate data with little to no investment. Students with low or no budget can use convenience sampling because they can make use of the people in their contact to obtain data for their survey.

Easy to use:

The respondents in convenience sampling are readily available to the researcher. The members of the sample can be friends, families, employees, regular customers, and random people on crowded streets. Therefore, the responders are accessible to the researcher, and collection of data, as a result, is an easy task.

Provides Qualitative Information:

On certain issues, it can provide in-depth information. For example, you can add a survey with the bill presented in your restaurant. The customers can fill the survey and give you their opinion, comments, and review about your restaurant. This way you can gather information relevant to the success of your restaurant with the help of convenience sampling.

Disadvantage of Convenience Sampling

Does not produce a representative result

Convenience sampling is a type of market research which uses a small part of the population to make assumptions about the entire population. However, generalization of the result to the larger population is not always possible. The convenience sampling result may vary widely depending on the scale of the population. For small-scale projects, a large sample size and data may provide representative results.

Biased

The result in convenience sampling can be biased because some people may take part in the survey and some may not. This can disturb the purpose of the survey and make the result futile.

The biased result can be prevented by using probability sampling along with convenience sampling. This can help derive more accurate results.

Efficiently analyzing Convenience Sampling

It is mostly recommended to use probability sampling. But, when convenience sampling is the only option follow the tips to have more efficient results.

• With a large sample size, the method of cross-validation can be used on one-half of the data. To see if the result is a match you can compare the result of the first half with the second half of the data.
• When conducting a sample it is advised to take multiple samples during the period of the research. This way you may be able to produce reliable results.
• Repeating the research several times can bring you closer to be results that can be generalized to a large population.

What is Field Research

Field Research is a method of collecting qualitative data with the aim to understand, observe, and interact with people in their natural setting. It requires specialized market research tools. The goal is to understand how a subject behaves in a specific setting to identify how different variables in this setting may be interacting with the subject. Field research is used most in the field of social science, such as anthropology and health care professions, as in these fields it is vital to create a bridge between theory and practice.

Methods of Field Research

There are 4 main methods of conducting field research, and they are as follows:

1. Ethnography

Ethnography is a kind of fieldwork that aims to record and analyse a particular culture, society, or community. This method defines social anthropology, and it usually involves the complete immersion of an anthropologist in the culture and everyday life of the community they are trying to study.

     2. Qualitative Interviews

The goal of qualitative interviews is to provide a researcher with a breadth of information that they can sift through in order to make inferences of their sample group. It does so through interviews by directly asking participants questions. There are three types of qualitative interviews; informal, conversational, and open ended.

    3. Direct observation

This method of field research involves researchers gathering information on their subject through close visual inspection in their natural setting. The researcher, and in this case the observer, remains unobtrusive and detached in order to not influence the behavior of their subject.

    4. Participant Observation

In this method of field research, the researchers join people by participating in certain group activities relating to their study in order to observe the participants in the context of said activity.

Steps to conduct Field Research

The following are some key steps taken in conducting field research:

1. Identifying and obtaining a team of researchers who are specialized in the field of research of the study.
2. Identifying the right method of field research for your research topic. The various methods of field research are discussed above. A lot of factors will play a role in deciding what method a researcher chooses, such as duration of the study, financial limitations, and type of study.
3. Visiting the site/setting of the study in order to study the main subjects of the study.
4. Analyzing the data collected through field research.
5. Constructively communicating the results of the field research, whether that be through a research paper or newspaper article etc.

Reasons to conduct Field Research

The following are a few reasons as to why field research is conducted, typically via market research tools:

1. To understand the context of studies: field research allows researchers to identify the setting of their subjects to draw correlations between how their surroundings may be affecting certain behaviors.
2. To acquire in-depth and high quality data:  Field research provides in-depth information as subjects are observed and analysed for a long period of time.
3. When there is a lack of data on a certain subject: field research can be used to fill gaps in data that may only be filled through in-depth primary research.

Examples of Field Research

• The following are real studies conducted using field research in order to answer questions about human behavior in certain settings:
  • William Foote Whyte used participant observation in his 1942 study to answer the question “How is the social structure of a local “slum” organized?”.  The study involved over 3 years of participation and observations among an Italian community in Boston’s North End.
  • Liebow’s study in 1967 involved twenty months of participation and observations among an African American community in Washington, DC, to answer the question “How do the urban poor live?”.
  • American sociologist, Cheri Jo Pascoe, conducted eighteen months of observations and interviews in a racially diverse working-class high school to answer the question “How is masculinity constructed by and among high school students, and what does this mean for our understanding of gender and sexuality?”.

Advantages of Field Research

1. Can yield detailed data as researchers get to observe their subjects in their own setting.
2. May uncover new social facts: Field research can be used to uncover social facts that may not be easily discernible, and that the research participants may also be unaware of.

No tampering of variables as methods of field research are conducted in natural settings in the real world. Voxco's mobile offline research software is a powerful tool for conducting field research.

Disadvantages of Field Research

• Expensive to collect: most methods of field research involve the researcher to immerse themselves into new settings for long periods of time in order to acquire in-depth data. This can be expensive.
• Time consuming: Field research is time consuming to conduct.
• Information gathered may lack breadth: Field research involves in-depth studies and will usually tend to have a small sample group as researchers may be unable to collect in-depth data from large groups of people.

Concept Testing is a market research method used by Companies to evaluate concepts or ideas before it is launched in the market. A target audience is surveyed on the concepts to gauge the interest, acceptance, and willingness of the customers to engage with the concept (product, service, advertisement).The responses collected from the audience help the company make an informative decision before the launch. When a brand is preparing to launch a new product or redesign an old product, they conduct Concept Testing to identify the likes and dislikes of the target market.

Importance:

• Concept testing allows the brand to see how well the product will perform if it is launched in the market. 
• It helps gain insight into the improvements and changes which are needed. 
• Concept testing helps identify how different segments of audiences prefer different features. 
• The data collected from customers prevents the company from investing in concepts that may not be accepted by the customers. 
• Concept testing prevents a company from investing in bad concepts based on assumptions. 

Concept Testing Methods

There are four most commonly used methods of Concept Testing.

Monadic Concept Testing:

In monadic concept testing, a single concept is evaluated by the respondents. If there is more than one concept, the respondents are divided into multiple groups. Each group is then shown one concept to analyze.This means that each respondent only comes across one concept. This allows conducting an in-depth survey. Make sure to keep the survey short and follow up if required.

Sequential Monadic Concept Testing:

In a sequential monadic test, the respondents are asked to evaluate each of the concepts. The respondents are divided into multiple groups and each group is shown the concepts in random sequence. The random sequence prevents the respondents from forming any biased opinions.Multiple concepts are evaluated with a small sample group which saves time and resources for the company. The risk is that the survey questionnaire may end up being long because multiple concepts are tested in one round.[elementor-template id="38118"]

Comparative Concept Testing:

For Comparative Concept Testing, respondents are asked to evaluate between multiple options to select the best Concept. The survey is simple, the brand asks which concept or idea is better and the winning concept is finalized for the launch.

Proto-monadic Concept Testing:

It is a combination of comparative and monadic concept testing. The respondents are asked to select the best concept. Then they are asked questions to evaluate the selected concept.The comparative concept testing alone cannot provide the reason for the respondents’ preferred choice. The second evaluation using the monadic test helps provide the necessary reason. It helps gather information on the various aspects, features, or attributes of the preferred concept.

Application of Concept Testing in Market Research

Concept testing helps businesses identify the best and the bad ideas. It saves a company from launching a bad concept in the market and faces loss. Concept testing is thus a crucial step before any ad campaign, logo, product, service, etc. are launched.These are some scenarios you can use in your Concept Testing.Identify Market: You need to have a good understanding of the market to target the right audience with the right concept. Concept Testing helps understand the reason why a different segment of audience likes different concepts. The knowledge of different demographic segments helps develop successful market strategies.Pricing: When you want to launch a new product or get an opinion on the prices of your products you can gather customer feedback. It can help you make decisions on how you should change the price or charge your products.Marketing message: With concept testing, you can identify what kind of marketing message resonates with your target audience. It helps you to understand how you can attract and influence your target customers to consider your brand for future business.Branding: You can also use concept testing for deciding logo, website design, color, etc. You can ask the respondent to select the effective idea and understand their reason for their choice.

Best Practices for Concept Testing

For any subtle adjustment whether it is on pricing or features, conduct Concept Testing. By identifying the different aspects of the concept you can focus on the key features. Concept testing can provide a clear view about which concepts need improvement and which need to be dropped. Conduct concept testing for each change made in the product as per customer feedback. Collecting customer’s perspectives on the newly changed concept is the way to ensure that your data stays up-to-date. The ongoing process of concept testing helps you track all the latest trends about customer’s needs and wants.Learn from the previously collected data by comparing it to the new data. Previous data is filled with information that can help you improve new concepts for testing. You can look into past research to identify which method of testing works effectively.The introduction is an important part of the survey because it gives the audience the idea of what the purpose of the survey is. You need to make sure that the concept is described in simple language. The introduction should include the concept, benefits, and key differentiators of the product.The survey design for Concept Testing should be simple. The choice of answers should be easy to understand. Using questions like Likert Scales gives a coherent structure and a smooth flow to the survey. It is also easy to analyze the data collected from a Likert Scale.[elementor-template id="38078"]

FAQs

What is Concept Testing in Market Research?

Concept Testing in Market Research involves using surveys to evaluate the target audience’s acceptance and willingness to buy the new product concept. The new concept is tested before it is introduced in the market to gauge customer’s reaction to the features, price, and other important aspects.

What is a Concept Statement?

A Concept Statement in concept testing is the description of the concept that helps visualize the end product/ service.

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There are four basic methods a brand can conduct Concept Testing:

• Monadic 
• Sequential Monadic
• Comparative
• Proto-monadic

Quantitative and Qualitative research :Which one to prefer?

Research is a great way of gathering data and information to enhance understanding about a variety of issues and ideas. It is imperative to know the kind of research to go for, in order to satisfy a purpose and obtain valuable data in the most convenient manner. While deciding the research type, one also needs to consider how this selection will impact analysis and contribute by providing input to make informed decisions. A research methodology may be easy to conduct but may not generate sufficient key insights or may not be feasible in terms of time, effort and resource investment but may be easy to evaluate and conclude. There should be a certain balance between the conduction and conclusion aspect of research, to pick the correct choice.The two broad categories of research are quantitative and qualitative research.Quantitative research deals with numbers and statistics to describe test and draw conclusions about variables. Such a data can be mathematically and statistically analyzed. It is also viable to present such type of research data in the form of charts and graphs for enhanced understanding. This type of research mainly focuses on testing relationships and hypothesis by gathering maximum information to make a meaningful conclusion. Examples of such type of research include observations, closed-ended type questions in surveys and experimental data.Qualitative research, on the other hand, focuses on descriptive and text-based data to make observations, understand ideas and concepts, gather insights and social perceptions. It is aimed at grasping how people view things around them using an unstructured and unrestricting method of research that allows people to elaborate their viewpoints. Unlike quantitative research, qualitative research is not focused on hard numbers and figures and is analyzed using text based analysis tools. Examples of qualitative research are open-ended questions, interviews, group discussions, video and audio recordings among others

QUANTITATIVEQUALITATIVENumber and figure basedText basedTests relationship and hypothesisIt is used for making observations and enhancing conceptual understandingAnalyzed using statistical and data analysis toolsEvaluated by using summarizing techniques and text based analysisResearched using closed-ended questionsResearched using open-ended questionsPresented using graphs, charts and diagramsTechniques such as Word cloud helps in capturing and presenting key insightsRequires large number of participantsLimited number of participants are neededObjective in natureSubjective in natureLanguage based reportingStatistical reportingExample: interviews and focus groupsExample: Structured questions and observations01

Methodologies

Qualitative researchQualitative research is conducted using focus groups, in-depth interviews, ethnography, documents, reviews and open-ended survey questions. All of these methods allow participants to elaborate and clarify their opinions and thoughts as well as study behavior in specific circumstances. Though it may seem a cumbersome process, collecting qualitative data helps in understand respondent mindset and making assumptions and observations based on authentic information.Focus groups: Discussions between participants with relevant knowledge base to gather holistic data on the research topic.Interviews: One to one dialogue to gather point of views and respondent’s thoughts about products, ideas and concepts.Open-ended survey questions: Unstructured questions meant to gather feedback and respondent’s unrestricted opinion.Documents: Second hand information on research topics to grasp topics using sourced data.Ethnography: An observation style based research involving participation in a community to note behavior and activitiesReviews: Studying and reviewing written piecesQuantitative researchQuantitative research is gathered using closed-ended questions, observations, experiments and different survey methods. These research methods mainly focus on bringing cause and effect relation as well as proving the validity of hypothesis by gathering input to support or deny the same.Closed-ended questions: Questions with limited answer options to assist categorizing and analyzing.Observations: Observing and noting numeric variables like temperature.Experiments: Establishing correlation between variables through controlled conditioning.Telephonic surveys: Gathering structures data through telephonic conversation.Polls: Polling questions and statements to assess agreement, rating and choice.

Analysis

Qualitative researchTexts and language used in qualitative research is highly variable and cannot be uniformly understood. Text based summarizing and interpretation techniques are used to highlight key areas.Thematic analysis: A latent approach that tries to uncover the underlying meaning behind written information by following a series of steps that involve understanding, highlighting, assigning themes and codes and finally writing up the takeaways from the gathered qualitative information as a whole by supporting each of these takeaways using phrases and texts from the first-hand data. It also tries to establish whether or not the purpose of the research has been satisfied based on the data collected.Word cloud: Word cloud is a summarizing tool used for overviewing the key words that texts contain. This usually promotes a follow up discussion on reasons that lead to the use of a word or phrase in relevance to the research topic.Discourse analysis: Understanding communication, linguistics and structure of qualitative data. This technique studies speech, sentence structures, conversational indicators and frame of references to understand how people interact in a social setting.Quantitative researchQuantitative research is based on facts and figures and so, it becomes relatively easier to make sense out of it using data and statistical analysis tools. These tools can be used to summarize and understand nature of relationship between variables. The analysis results describe the data using certain mathematical concepts that can easily be applied due to the structured nature of the data collection process. Descriptive analysis provides holistic and concise figures which combine results from individual responses to provide an overall picture of the collected responses.Such a statistical summary can then be presented in the form of graphs, pie charts, bar diagrams, line charts and other forms of data representation method which makes it easy to comprehend. Such statistical summaries can then be used to validate or invalidate hypothesis. This gives a more realistic and reliable approach for testing theories.

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Limitations

Qualitative research

• Highly varied and complex data makes it difficult to analyze as compared to quantitative data 
• It becomes difficult to assess reliability and validity given the lack of rigidity in answering
• Respondents may not be clear and elaborative in expressing themselves completely and so researchers may sometimes have to follow up to increase their understanding on particular answers.
• It requires a lot of time and money to hire professionals and conduct in-depth interviews.

Quantitative research

• Structured nature of the research limits answer choices

• Analysis of quantitative research requires expertise to decide the right kind of tool and conduct the process properly to generate meaningful results.

• Does not allow researcher to gather insights and study behavior.

• Requires large number responses to make the study substantive which requires a lot of resource investment.

Advantages

Qualitative research

• Aids understanding of participant mindset and reasoning
• Elaborative and unrestricted
• Establishes observations and enhances relationship understanding between variables
• Assists in gathering feedback for identifying gaps and positives.
• Narrative nature of the research makes the study and its results more authentic

Quantitative research

• Minimizes chances of ambiguities and confusion
• Relatively accurate 
• Easy to analyze using systematic tools
• Proves theories based on supportive information
• Easy to present and convey to third parties 
• Easy to summarize, categorize and interpret due to pre-defined structure.

The researcher has to carefully consider the purpose, resource availability and decisions to be made before going ahead with a particular research method. Researchers looking to make observations and establish theories should go for a qualitative approach, while testing and proving these theories is more feasible using a quantitative approach.Free Market Research ToolkitFill out this form to access 5 market research survey templates + 2 MR guide.

What is Pricing Research?

Pricing research is a method of research that measures and evaluates the impact of changes in price of a product on its demand. It is used by organizations to help determine an optimal price for new products, in order to maximise revenue and market share. This type of research is quantitative in nature.

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Techniques used within Pricing Research

Pricing techniques help organizations determine what price their target audience is willing to pay for their product. There are four key techniques used within pricing research, and they are:

• Van Westendorp Price Sensitivity Meter (PSM)
• Gabor-Granger Technique
• Conjoint Analysis
• Brand-Price Trade-Off (BPTO)

• Van Westendorp Price Sensitivity Meter (PSM)

This price sensitivity meter was developed by a Dutch economist named Peter Van Westendorp. The Van Westendorp Price Sensitivity Meter constructs a range of acceptable price points for a given product, determining the expected price range at which consumers will be willing to purchase it. This range is constructed by having customers evaluate a product and then respond to the following four questions:

• • Too Expensive: “At what price would you begin to think this product is too expensive to consider?”
  • Expensive: “At what price would you begin to think this product is expensive but worth considering?”
  • Cheap: “At what price would you begin to think this product is a bargain?”
  • Too Cheap:“At what price would you begin to think the product is so inexpensive that you would question its quality?”

Once responses are collected, the cumulative frequency of the different answers are charted in order to determine a series of acceptable price points. These price points will range from a lower threshold to an upper threshold, and will also include the optimal price point.

PSM is used to understand customers’ pricing expectations, rather than their willingness to pay or their likelihood to buy. It is used to identify how much respondents would expect a product to cost.

• Gabor-Granger Technique

The Gabor-Granger technique involves testing four to five different price points by asking respondents their likelihood to purchase the product at each one of these points.

Respondents indicate their likelihood to purchase at these predefined price points, and this data is used to determine an optimal price point for the product within the market. In contrast to the Van Westendorp Price Sensitivity Meter, where respondents invent prices in response to the questions, the Gabor-Granger technique asks respondents to evaluate predetermined price points that have already been vetted by the company. It identifies the optimal price range for a product, considering it in isolation.

• Conjoint Analysis

Conjoint Analysis, also known as discrete choice analysis, is a pricing research technique that is considered to be the most reliable way to determine the price of a product. It uses a form of conjoint analysis, known as discrete-choice modelling, using which researchers can determine the influence of price, as well as product features, on a customers’ willingness to purchase the product.

In this technique, respondents are given a choice of two to five product profiles, each with different configurations. Respondents are asked to choose one of these profiles. The data collected from respondents allows researchers to create pricing and packaging models that are most likely to appeal to customers.

Discrete choice analysis provides meaningful insights on the complexity of pricing and product preferences. The main drawback of this technique, however, is that it requires specialized expertise to execute, and tends to be more expensive to conduct than other pricing research techniques.

• Brand-Price Trade-Off (BPTO)

BTPO, or Brand-Price Trade-Off, is a statistical tool that is used to identify the effect of price on different areas such as profitability, revenue, market volume, and brand awareness. It is a choice-based pricing technique that depicts consumers’ differing preferences for brands based on their pricing.

Survey respondents are shown a range of branded products, each with a price associated with it. The range usually consists of 3 to 5 products. Consumers are then asked which “offer” would be most appealing to them in a hypothetical buying scenario.

BPTO is useful in situations where you want to understand the relationship between a brand and its prices.

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FAQs on Pricing Research

What are the different pricing techniques used within pricing research?

There are four key pricing research techniques, and they are:

• Van Westendorp Price Sensitivity Meter (PSM)
• Gabor-Granger Technique
• Conjoint Analysis
• Brand-Price Trade-Off (BPTO)

What are the benefits of conducting pricing research?

The key benefits of conducting pricing research are:

• It can predict consumers’ responses to price change

This content has been archived. It may no longer be relevantAn Ascribe Rule Set lets you programmatically alter the results of linguistic analysis.  To learn more about Rule Sets, see Introduction to Ascribe Rule Sets and Authoring Ascribe Rule Sets.

Your Rule Set may process thousands of findings when you use it in an Inspection. Therefore, it is very important to test your Rule Set carefully to avoid disappointing results.
Suppose we want to create a rule to uppercase our brand name when it appears in the topic of a finding. We write this simple Modify Finding rule:

// Uppercase our brandf.t.replace("ascribe", "Ascribe");

We intend for this rule to find all occurrences of the word “ascribe” in the topic and replace it with “Ascribe”. We need to test this rule, because it is not correct!

Rule Editor Dialog

On the Rule Sets page of Ascribe, we create a new Modify Finding rule and enter our code:

To test our rule, we need to make sure the Test part of the dialog is expanded as shown above. If not, click on the word Test to expand that part of the accordion. Now enter the properties of the finding you want to use for testing in the top part of the Test pane. I have entered “ascribe” there for the topic.

Click the Test button below the properties you entered. The properties of the resulting Finding after your rule runs are displayed below the Test button. They are shown in grey if they have not changed, which is what you see in the picture above. Our rule is not working! The resulting finding still has a lower-case topic:

The problem of course is that the replace method of a string returns the modified value. It does not change the value you pass in, so our topic is unchanged. To correct the code, we add an assignment to f.t and retest the rule:

Success! We can now save the rule by clicking the OK button.
You probably noticed that I entered properties for f.r, f.t, f.e, and f.x, even though only f.t is needed for the test. This is because if any of f.t, f.e, or f.x are empty after the rule runs the result of the rule will be ignored. You can try this in the dialog to see for yourself.

Testing Class rules requires a bit more work.  See Using Class Rules in an Ascribe Rule Set for more information.

Testing Edge Cases

Happy with the result of our Modify Finding rule we may decide to add a Modify Response on Load rule to do the same thing. That way our comments will display our brand name with proper case in the Verbatims pane of CX Inspector. We copy our code into a Modify Response on Load rule, change it to operate on f.r instead of f.t, and give it a test case with a lowercase brand mention. This type of rule receives only f.r when it runs. That’s why the other properties of the finding are not shown in the Test pane:

The rule still handles our test case properly, and we may be tempted to consider it completely tested. But we need to test it more. It fails on each of these test cases:

Wow, ascribe is great! I recommend ascribe. ⇒ Wow, Ascribe is great! I recommend ascribe.
Wow, AScribe is great! ⇒ Wow, AScribe is great!
I ascribed his success to luck. ⇒ I Ascribed his success to luck.

The first is because our rule replaces only the first occurrence. The second because our text matching is case sensitive, and the third because we are not replacing only whole words. The simplest fix is to use a regular expression. We can write our rule instead as:

// Uppercase our brandf.r = f.r.replace(/\bascribe\b/ig, "Ascribe");

The ig flags on the regular expression correct our first two problems, and the use of \b corrects the third problem. Our rule now handles all our test cases correctly.

Rule Debugging and Validation

Using Print()

As you are testing your rules it can be helpful to print out information for diagnostics. The finding object has a Println() methods for this purpose. Here is a rule that captures words in the response and prints each to the test pane when the rule runs:

var m = f.r.match(/\b\w+\b/ig);for (var i = 0; i < m.length; i++) {  f.Println(m[i]);}

If f.r == "Wow, Ascribe is great!", this will print:

"Wow""Ascribe""is""great"

to the Test pane.  The Print() and Println() methods are identical, except Println() appends a newline character to the output. Both methods accepts zero or more parameters. If the parameter list is empty a blank line is output. The Print() and Println() methods have effect only in the Test pane. When the Rule Set is actually used in an Inspection the methods do nothing.  These examples demonstrate the behavior of these methods:

f.Println("Hello world"); // "Hello world"f.Println(null); // ∅f.Println(f); // Rule.Findingf.Println([1,2,3]); // 1,2,3f.Println(new Date(2018, 0, 1)); // Mon Jan 1 00:00:00 PST 2018

In general Print() writes the result of calling the toString() method on the parameter passed.  However, if the parameter is null the character ∅ is written, and if the parameter is of type String the value is enclosed in quotes, as in the first example above.  If there are embedded quotes in the string they are escaped in the output:

f.Println("Is \"Jane\" your name?"); // "Is \"Jane\" your name?"

If a JavaScript object is passed (not an Array, but a pure Object) it is printed in a style similar to JSON, but only for the top level properties:

f.Println({a: "foo", b: 22, c: [1,2], d: {f: 5}});

produces

{  "a": "foo",  "b": 22,  "c": 1,2,  "d": [object Object]}

The behavior changes when more than one parameter is passed.  In that case the values are written sequentially to the output, separate by space characters.  This is useful for annotating the output:

var x = 5;f.Println("The value of x is", x); // The value of x is 5

Validation

When you click the Validate or OK button in the rule editor dialog, Ascribe runs a few test cases through your rule to guard against rules that will throw errors at runtime. Among the test cases are zero length strings for the various properties of the finding.  Returning to our example above:

var m = f.r.match(/\b\w+\b/ig);for (var i = 0; i < m.length; i++) {  f.Println(m[i]);}

If you try this you will find it works fine when testing, but causes a runtime error when you try to save the rule by clicking OK.  In the rule above, validation using zero length strings will cause the variable m to have a value of null. In the for statement this will case a runtime error of Exception: Object required. As a result, the rule cannot be saved as written. It must be corrected by testing m:

var m = f.r.match(/\b\w+\b/ig);if (m) {  for (var i = 0; i < m.length; i++) {    f.Print(m[i]);  }}

In general, when you receive the error Exception: Object required at validation time, you likely need to add a test for a valid object before you access a property or method of the object.

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