Constant Sum Question: A New Matrix Question Type to Customize Your Survey
Constant Sum Question: A New Matrix Question Type to Customize Your Survey
We’re thrilled to offer researchers yet another new question type to power their surveys: the constant sum question.
This can exist as a Matrix question type on the Pollfish market research platform. As such, this is an addition to another Matrix question we offer: the Bipolar Matrix question type.
As you know, surveys are a great tool to conduct both qualitative market research and quantitative market research. But now, with this new question type, you can create questions with quantitative elements.
That’s because constant sum questions enable respondents to enter numeric data, wherein each numeric entry is summed up and displayed to the respondent.
You can use this question type for a consumer analysis, along with researching everyone in your target market: donors, students, employees, partners and more.
This article explains what a constant sum question is, its use cases, importance, how to create one on Pollfish and more.
What is a Constant Sum Question?
A constant sum question is used in a market research survey; it allows respondents to assign a specific number of points to all the answer options in the question.
Thus, this is a multiple-choice question, one that requires respondents to enter a numeric value for all choices per question.
The type & total of these points can be defined by the researcher while designing the survey. When these points are defined, respondents won’t be able to answer with values that exceed the maximum points allowed.
The points can take whichever unit you wish to study, such as currency, hours, frequency, etc.
This question type allows you to calculate the numerical aspects of customers' decisions and everyday lives, allowing you to better understand their customer buying journey and virtually all else.
Let’s delve further into the usage of this question type.
Constant Sum Question Use Cases
The constant sum question type gives an understanding of how your respondents value each answer option per question.
These options revolve around a specific topic and inquiry, such as how many times within a certain time period customers buy certain products, or how they rate particular products.
Therefore, you can apply this question to a wide variety of research. The following lists key use cases of this kind of question. This is not exhaustive, as you can ask respondents to assign value to essentially all topics and issues.
- The dollar (or other currency) amount spent
- On specific items
- On certain days
- On budgets
- Amount of time
- Taking part in particular habits
- Working on a project
- Leisure time
- Taking care of responsibilities
- Percentages
- Allocating portions to various activities
- Viewpoints
- Inclinations
- Habits
- Rating systems
- Scales (1-10, etc) on products and services
- Ratings on customer service
- Easiness of a product, school or work assignments
- Ratings on overall customer satisfaction
The Importance of the Constant Sum Question
This kind of question is important for various reasons.
First off, it is useful for product research. If customers feel that certain features of a product or service are more important than others, they will allot more points to those features.
Thus, researchers will get a clear indication of the products (and product features) that customers are satisfied with and not.
Using a constant sum scale is also a great way to create differentiation within a data set. It helps you determine which factors are important and which are not for your target market sample.
They are especially helpful in cases where many factors are critical and overlap in some sense. Thus, studying many factors is no longer a hindrance: you can just create an answer option for each factor.
The respondents will assign it a point or rating so you can see the nuances of each factor, especially when it comes to how your customers feel about them.
As such, this question allows you to study multiple aspects easily, as the data this question yields is straightforward and to the point.
This question is also important in a case where you seek to get purely quantitative data. Again, this is useful when dealing with larger sets of answer options. In this case, open-ended questions and other qualitative questions won’t be useful.
Additionally, this question type is especially convenient when you don’t want to form individual questions on a specific aspect.
This would require answer choices unique to the aspect in question, whereas, in a constant sum question, you can fill in various aspects per question.
You can see the sentiments on each aspect displayed in a simple numerical format. This is useful for maintaining a shorter survey, which is a common survey best practice.
In all, this type of question provides convenience for your study and a good UX for your respondents.
Examples of the Constant Sum Question
We dove into the various use cases of this question and now we’ll walk you through specific examples.
Example 1:
Ask respondents to allocate 100 points on the expenditures of their surplus goods, AKA, non-essential items. You can create your own point system or use a currency.
Provide a list of options and ask them to assign the points in order of importance.
Let’s say they spend $20 on movies, $70 on gadgets, $10 on miscellaneous expenses. With the constant sum question, you’ll find out which groceries are the most important for the respondents, as well as which they spend the most and least on.
Example 2:
Ask respondents their views on a particular digital experience with your business. Your answer options can include emails, customer service sessions, finding what they need on your site and more.
You can customize your scale to your liking. As such, you can use points via a scale of 100, or 10. You can also use percentages, especially when talking about the time spent on each.
It would be like this: rate the time you spent on the digital experiences with our company: viewing the homepage - 30%, reading a blog post - 20%, searching for products - 40%, speaking with a support rep via chat - 10%.
They can also rate how they viewed each experience; this would require a scale of 1-10, or 100, depending on researcher preferences.
Example 3:
You can discover how well your customers know and feel about certain brands, especially useful if they are your competitors.
As such, you can ask them to rate how they feel about each brand along with how much time they’ve spent engaging with it.
This can appear as such: rate how much you’ve engaged with each brand, which can include buying from them, viewing their items, reading their content, etc.: Macy’s- 30%, Old Navy -15%, Marshalls - 45%, Burlington Coat Factory - 10%.
How to Use the Constant Sum Question on Pollfish
Creating a constant sum question on the Pollfsih platform is easy and straightforward.
For respondents, it’s as simple as allocating a certain point to each answer option. See the section above with examples of how respondents can answer the question.
For researchers, it involves implementing the question in the questionnaire section, along with adding and customizing acceptance criteria.
Here is how to add it to your questionnaire:
- Go to the questionnaire section of the survey after creating a new one.
- Select a Matrix question and then the Answer type: Constant Sum.
- You can lift the Must total validation and change it to Continuous Sum.
- There are 2 appearances as well.
- You can add a sign (if you seek) and select if you accept decimals or not at responses.
Create the survey you want
The Pollfish team is constantly working to improve your survey experience, so you can expect us to continue updating and upgrading our platform with more features.
With our vast array of question types, you can form any survey and any research campaign.
Our research platform is optimized for both the respondent and the researcher. Thus, it is a win for all parties involved.
Researchers can reap a wide breadth of information on their respondents and leverage a wide pool of insights in their survey results dashboard.
Pollfish also provides artificial intelligence and machine learning to remove low-quality data and a broad range of survey and question types to customize your surveys.
In addition, there’s the advanced skip logic feature, which routes respondents to relevant follow-up questions based on their previous answers.
With a research platform containing all of these capabilities, you’ll be able to set up any survey you want, study any group based on demographics and psychographics alike and reap high-quality data.
Excelling in Survey Research with the Quantitative Survey
Excelling in Survey Research with the Quantitative Survey
A quantitative survey provides researchers with data that is quantifiable in nature, making this type of survey an important component of any research project. In a quantitative survey, numeric values are assigned to the answers so researchers can objectively measure and compare survey data.
A quantitative survey produces the type of data that many of us associate with surveys. This type of data is easily converted into objective, numerical results that can be viewed in tables and charts to provide a clearer picture.
In “The Complete Guide to Quantitative Market Research,” we covered the types of quantitative research methods that are used to drive market research. In this article, we will focus specifically on how you can use a quantitative survey to gather numerical data to drive your research project.
Defining the Quantitative Survey
In a quantitative survey, data is obtained by asking respondents objective, close-ended questions. Each question has a predefined list of answers. The responses are then used to compile numerical data that you can analyze via tables, charts, and graphs.
Quantitative survey questions are used to gain insights about ratings, pricing, frequency, and likelihood. They are often used to understand the relationship between attitudes and consumer behavior. The responses for quantitative survey questions include binary, multiple-choice, and scaled responses.
One of the main ways that a quantitative survey differs from a qualitative survey in that it asks “who” and “what,” while qualitative questions ask “why,” in order to understand the motivation behind actions, thoughts, or feelings. Qualitative questions are commonly used to gain context or gather information about attitudes, lifestyle choices, and issues. The responses for qualitative questions involve both open-ended and multiple-choice questions.
The Pros and Cons of Quantitative Surveys
In order to understand when to use quantitative surveys, you must first understand the pros and cons of this type of survey.
The Pros:
- The data from quantitative surveys is usually easy to collect and analyze.
- The simple format of quantitative surveys allows researchers to distribute them more broadly and reach a larger audience.
- Without open-ended questions, quantitative surveys are usually faster to complete, which can improve the response rate.
- Quantitative surveys are useful when researching sensitive subjects because they can allow the respondent to remain completely anonymous, without the need to contribute any personal or identifiable information.
- Quantitative surveys are more mobile-friendly than qualitative survey questions because the respondent does not need to type out lengthy answers.
The Cons:
- Quantitative surveys do not allow researchers to probe for deeper or unique answers to survey questions.
- The results of quantitative surveys can be misleading. Despite the seemingly objective nature of quantitative surveys, researchers can interpret the data based on their own views and then state conclusions in a way that sounds factual since they are based on numbers.
- Since quantitative survey questions have predefined responses, there is no opportunity for a respondent to volunteer unexpected information.
- It can take longer to plan a good quantitative survey that will collect the data needed to understand relationships or behavior.
- Survey responses must be carefully considered so that respondents are able to select an answer they can relate to.
Creating a Survey with Quantitative Questions
Quantitative survey questions will yield data that you can use to better understand your target market. The results can be compiled into a research report to provide statistical information and detailed insights. This information is typically used to understand prevalence and quantify phenomena, along with then being used to broaden research efforts and better understand the market as a whole.
In order to formulate the right type of questions, you first need to understand the goals of your research project. In quantitative research, researchers often start by stating the objective as a question and then designing survey questions to find the answer.
For example, a researcher might ask: “How do the study habits of college freshmen compare to the study habits of college seniors?” In order to answer this, the researcher would need to gather information about both college freshmen and college seniors in order to draw conclusions.
Remember: you need to create quantitative survey questions in a way that allows them to be translated into numerical data. This means that you will need specific, numerical answers to each question.
Quantitative questions frequently ask “how” or “what.” For example:
- What is/are…?
- How many…?
- How often...?
- What percentage…?
Below we provide some example questions that a researcher might ask in order to understand how study habits change throughout the course of a college education. For the purpose of this exercise, assume that the researcher has used pre-screening questions to sort the respondents into two groups - college freshman and college seniors who are attending a 4-year university for the first time.
Establish Demographics
In order to understand how demographic factors influence responses, you will need to gather some basic demographic information:
- What is your age? [Dropdown]
- What is your gender? [Multiple choice]
- How many years have you attended this college? [Dropdown]
- How many people in your immediate family (parents and siblings) have attended college? [Multiple choice]
- What is the highest level of education attained by either of your parents? [Multiple choice]
Understand Study Habits
The next part of your survey will focus on gathering data that you can use to describe the study habits of these two groups.
- How many hours per day do you study? [Multiple choice answer]
- How often do you attend a study group? [Multiple choice answer]
- How likely are you to join a study group for a class that you struggle with? [Multiple choice]
- How many study groups are you currently a member of? [Multiple choice]
- Which of the following study tools do you use and how often? [Matrix]
- How do you rate the following study tools? [Matrix]
Deeper Questions
Despite their objective nature, quantitative survey questions can help you understand how your respondents feel about their experiences, that is, it helps you quantify their feelings Here are some ways you can use quantitative questions to gain deeper insights:
- Please select how much you agree or disagree with the following statement: My current study habits are effective. [Likert scale]
- Please select how much you agree or disagree with the following statement: I know which study tools and methods are appropriate for each of the courses I’m taking [Likert scale]
- Please select how much you agree or disagree with the following statement: I think that I study more than other students in my year. [Likert scale]
Once you have your survey responses, you can begin to analyze the data. After this, you should have a general idea of the landscape of freshman and senior habits. This data can help you create a research report or lead to further surveys to further explore or better understand your findings.
Power Your Quantitative Survey with the Right Questions
Quantitative survey questions can power your research project by helping you gather and analyze large amounts of data with relative ease. This data can help you establish a good understanding of your subject matter and establish objectives for future research efforts. For this reason, most researchers include a large percentage of quantitative survey questions in their surveys.
Many surveys contain a mix of quantitative and qualitative questions, with quantitative questions forming the bulk of the survey. This is helpful because quantitative questions allow researchers to easily analyze and define findings, while qualitative questions can reveal deeper insights, contextual information, and unexpected findings.
Gain further insights by pairing some of your quantitative survey questions with a few, carefully chosen qualitative questions. By pairing questions in this way, you get the best of both worlds — numerical data that is ready for analysis and the potential for new discoveries by way of personalized responses.
Frequently asked questions
What is a quantitative survey?
A quantitative survey is one that asks close-ended questions that can be assigned a numerical value in order to allow for analysis via tables and graphs.
How does a quantitative survey differ from a qualitative survey?
Quantitative surveys seek to answer questions about “who” and “what,” why qualitative surveys are concerned with understanding “why.” Quantitative surveys do not have open-ended responses, while qualitative surveys can have a mix of multiple-choice and open-ended.
What are some of the benefits of quantitative surveys?
Quantitative surveys are easier to distribute to a large audience, allow for easier data collection and analysis, and tend to have a higher response rate since they are faster to complete.
What are some of the drawbacks of quantitative surveys?
Some of the limitations of quantitative surveys include the potential to misinterpret results and that they provide little opportunity to receive unexpected answers. It can also be challenging to design a good quantitative survey since the answers are defined rather than open-ended.
What is the benefit of including a mix of quantitative and qualitative questions?
Many surveys contain a mix of quantitative and qualitative questions because it provides researchers with plenty of numerical data to analyze, while also providing the potential to dig deeper and get some unexpected responses.
The Complete Guide to Quantitative Market Research
The Complete Guide to Quantitative Market Research
Quantitative research is a chief category in the research sphere, along with qualitative research. An encompassing aspect of market research, it can include both primary and secondary methods of extracting data.
Although used interchangeably with qualitative research, quantitative research is a distinct process that should not be confused with its counterpart. In fact, it is the opposite of qualitative research.
Let’s navigate through the waters of quantitative research in this complete guide.
What Defines & Makes Up Quantitative Research?
As its name suggests, quantitative research is the process of aggregating quantitative, or numerical data for research purposes. This data is used for a number of applications. These include:
- Quantifying opinions, behaviors, attitudes and problems
- Making generalizations
- Forming predictions
- Discovering patterns
- Determining averages
- Testing relationships
Quantitative research generally relies on a larger sample size in order to quantify any issue or variable. In order to achieve this, this research method involves using mathematical and statistical means.
This type of research answers the “what” and the “how much” of a subject within a research endeavor. As it forms generalizations, this type of method involves surveying a larger population, using measurable data and processing all the data first and then analyzing it from a statistical standpoint.
The Four Main Types of Quantitative Research
There are four main ways to perform quantitative research. Aside from their methodology, these sub-categories also seek different types of answers and conclusions.
1. Descriptive Research
This is used to determine the state of variables. It describes the situation and environment surrounding a variable or topic. As such, it is used for arranging comparisons, outlining sample characteristics, overlooking emerging trends and confirming existing phenomena.
The data is collected by way of observation. Descriptive Research is used to form a hypothesis, but only after having aggregated all the necessary data.
2. Correlational Research
This research method is used to examine the relationships between different subjects and variables. Analyzing relationships is necessary to either test a hypothesis or a prediction. Because this research focuses on relationships between fixed variables, other outlying variables are not part of the investigation.
Correlational research is in direct opposition to experimental research, as none of the studied variables are manipulated. Correlations can be either positive or negative, with different degrees of the relationship’s strength.
3. Experimental Research
This method is used for finding whether there is a cause and effect relationship among variables. This kind of research relies on the scientific method. Unlike correlational research, experimental research involves manipulating variables.
Researchers would manipulate a variable to uncover its effect on another one. This method is frequently referred to as true experimentation, as no experimental undertaking leaves all variables unchanged; at least one must be influenced in some way.
This includes manipulating, randomizing or reverting back a variable. The variables are then measured, calculated and compared.
4. Survey Research
The final research method is crucial to understanding behavior. In market research, it is often used to acclimate a brand with its target market’s desires, needs, points of contention and behaviors.
Surveys allow researchers to ask pointed questions to either discover their target audience or get a granular sense of their opinions. As such, they can be conducted within one group or many, for the sake of comparison.
Instead of turning to survey panels, which are likely to have skewed or biased results, researchers should use a random sample of people. A non-panel-based survey will garner more respondents that aren’t motivated by professional compensation.
Surveys can be administered by mail, in-person, on the phone, or digitally. The latter has even more options: online surveys, third-party surveys, emails and in-app.
Examples of Questions for Quantitative Research
Survey research has a far larger scope of questions than do the other three types, as researchers can ask practically anything to conduct their studies. However, there are some best practices in survey questionnaires, such as focusing on your industry, your product and the desires of customers.
Learn more about asking insightful market research questions. Here are a few examples of quantitative research questions in the three other categories.
- Is working from home the best option to improve productivity for employees with long commutes?Variable: Working from home and in-office
Demographic: Employees with long commutes
Quantitative Research Type: Experimental - How has the coronavirus changed employment for white-collar workers?
Variable: Employment types and statuses
Demographic: White-collar workers
Quantitative Research Type: Experimental - How often do working people travel for a holiday?
Variable: Amount of times respondents travel during a holiday
Demographic: working people
Quantitative Research Type: Descriptive - How much would you pay for a subscription to an entertainment magazine?
Variable: payments for a magazine subscription
Demographic: women aged 14-44, those interested in celebrities
Quantitative Research Type: Descriptive - What is the difference in smartphone usage between Millennials and senior citizens?
Variable: Time spent on using a smartphone
Demographic: Millennials and seniors
Quantitative Research Type: Correlational - Does the leadership style of car shop owners predict the job satisfaction of car salespeople?
Variable: Leadership style and job satisfaction
Demographic: Car shop employers and salespeople
Quantitative Research Type: Correlational
When to Use Quantitative Research and How to Analyze It
The quantitative research method has specific use cases. You ought to consider which is best for your particular business, which includes your strategy, your marketing and other facets.
The core of quantitative research is to quantify a phenomenon (a problem, an inadequacy, and a slew of other occurrences) and understand its prevalence. Researchers do this by observing large portions of a population.
You should use this form of research whenever you need to be presented with the state of things at a higher level, or from a bird’s eye view. This Is because this type of research can identify links between various factors, look for correlations and discover cause and effect relationships.
Researchers can then use the results of their findings to form predictions. This is useful in market research when launching a new product, brainstorming product ideas or innovations or growing a customer base.
To analyze this research, it should first be made quantifiable and objective. Researchers should pin down the scales and units of measurements in their various studies. Then, they should organize them into easily interpretable formats.
For example, once you gather the numerical data, you can enter it into a spreadsheet. Thereafter, you can organize it by desegregating it into graphs, charts and tables. Finally, you should draw data-based conclusions from your study. You can also do further sleuthing via advanced analytics.
The Benefits and Drawbacks of Quantitative Research
Quantitative research has a bevy of benefits; it also has some hindrances. You should peruse both the positive and negative qualities of this research type before setting out on any major research project. The following may help you choose one form of research over the other, or use aspects of both.
Benefits
- Larger sample pools: the larger the group of respondents, the more accurate are the results.
- Highly structured: Surveys, questionnaires, and other tools for recording numerical data
- Focused: The design of the study is determined before it begins
- Theory-based: Research tests a theory to provide support/proof
- Designed to Be Analyzed: Numbers/statistics exist as tables, charts, figures and other non-textual forms for easy analysis.
- Objective: Steering clear of bias as the research is separated from the data & only objective responses are sought.
- Direct comparisons of results: The study can be set in different cultural environments, times or different groups of participants with a statistical comparison of results.
Drawbacks
- Focuses solely on numbers: This can be limiting as researchers may overlook other data and larger themes.
- Superficial Representations: It cannot adequately describe complex concepts (ex: feelings, opinions) it only shows the numbers behind them.
- Several factors can invalidate results: A hypothesis and a model for collecting/ analyzing data.is required; any mistake can lead to bias and inaccurate illustrations.
- Erred Structure: If any data is missing or if measurements are not clear, biases easily take precedence.
The Final Word on Quantitative Research
Market research is far too encompassing to fully complete, especially in a limited amount of time. To tackle market research, begin with a research method. Quantitative research is often a good starting point, as it shows you the existence of a problem by way of quantifying it.
Aside from confirming the existence, it can help confirm a hypothesis, find correlations and prove cause and effect relationships. A hard set of data can also help you make educated predictions.
While the three types of quantitative research methods are useful, they do have several disadvantages. The fourth one, ie, survey research helps fill in the gaps and inadequacies of numerical limitations. Interestingly enough, they too can be a source of hard data and numbers.
Either way, market research is sure to benefit from incorporating surveys as part of the processes.
Frequently asked questions
What is quantitative market research?
Quantitative market research utilizes the techniques of quantitative research in order to better understand the target market. In quantitative research, the information gathered from surveys and questionnaires is converted into numerical values so it can be easily analyzed.
What types of questions do quantitative research answer?
Quantitative research seeks to define “what” and “how much.” It is used for identifying patterns, making predictions, establishing averages, and quantifying opinions, attitudes or behaviors.
What are the four main types of quantitative research?
The four main types of quantitative research are survey research, correlational research, descriptive research, and experimental research.
What type of surveys are used for quantitative research?
Quantitative surveys are best suited for quantitative research. In this type of survey, there are no open-ended questions, and all responses can be assigned a numerical value. In most cases, a quantitative survey is distributed to a large and random sample of individuals.
Why are large sample sizes important when conducting quantitative research?
A small sample size can lead to inaccurate results. The larger the sample size (i.e. the group of individuals who receive the survey), the more likely it is that the results will be statistically significant and accurate.