What is Constant Sum

Constant Sum helps you ascertain customer preferences and get numeric data on how much they prefer one feature over another

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What is Constant Sum?

The constant sum is a technique that is used in market research surveys where respondents are required to allocate a constant sum of points or units on specified criteria or features. All these points add up to a constant total, which remains unchanged.


Constant sum question type helps to get a better understanding of how respondents give value to specific attributes. When customers feel like certain features are more relevant to them than others, they tend to provide a higher score for that particular feature. Therefore, a constant sum is similar to rank order, but it carries value or points, which helps analysts to translate the data into reliable information.


How does the constant sum technique work

The constant sum is a technique adopted to understand what a consumer prefers amongst a collection of attributes, and, most importantly, by how much.


Constant comes in handy while computing percentages, handling finances, understanding customer preferences for specific criteria, or for any calculation which totals to a predetermined value, for that matter. For instance, when a respondent is asked to set 100 points for various features of a smartphone, he can assign a score of his choice for a feature he considers important. He can hit a null value for any attribute, which is not charming enough. The constant sum technique is where all the allocated scores add up to a total of 100. The score which a respondent gives reflects the value they give for the said feature.


An example of Constant Sum

Consider a question that’s part of your survey, which involves asking respondents their preference while opting for a restaurant to dine out. The question and the responses go as, “What factors do you consider while dining out on a Friday night?” with the options “Cost, location, ambiance, customer service.”


Most likely, you will receive a mix of different responses, with each option getting a share of the total percentage. Say the results are:


  • Location (20%)
  • Price (40%)
  • Ambiance (25%)
  • Customer service(15%)


You sure do get the idea that people consider price as a strong deciding factor. However, do you know by how much, compared to other factors? For some, price is the deciding factor, while for others, it is merely a contributor. So how exactly can you analyze the situation? The constant sum is the answer to your dilemma.


With constant sum, the question would be, “On 100 points, score points on the factors that mean the most to you; be sure to divide your score so that the total adds to 100!” and the responses you receive from a respondent would be:


  • Price- 60
  • Location- 10
  • Ambiance- 5
  • Customer service-25


When you analyze the answers, the data gives you a clear picture of not just the deciding factors, but also how much a factor supersedes another one. Therefore, by placing respondents in this budgeting loop, instead of tagging every feature as important or randomly picking a feature, they give a more systematic response. Consequently, you get profound insights into their expectations & behaviors. Therefore, we can say that constant sum scaling can be used to analyze the comparative significance customers place on various factors of a subject.


Understand customer preferences with SurveySparrow

Implementing constant sum and getting responses can be quickly accomplished in two steps. The first is setting up the question, while the second involves analyzing the results.


Choose constant sum slider question type

Select the constant sum question type, first and foremost. In the slider option, respondents can slide the answers to their desired value. You can set the minimum value and the range for the same. If you wish to keep the values within a particular number, you can limit the total and configure it. To make it easy for your respondents, segment each scale into small units and, for better precision, decimal points as well.



Or, constant sum text question type

In addition to the slider type, you can opt for the constant sum text question type to accept text input from your respondents. Just like the constant sum slider question type, you can set a range and a total. Furthermore, you can introduce symbols in the constant sum text question type. You can input anything in this field- symbols like %, $, or text like ‘hours.’ Enter the corresponding numeric value from respondents.


Collect data & analyze

Once you collect the survey data from your respondents, the next step is to analyze the survey results. Based on the points allocated by respondents for each feature, the various attributes are scaled and divided by the total number of respondents. This gives rich insights into how much value respondents give to one attribute over the other. The constant sum makes the audience think through carefully before picking one feature over the other. Hence, you can avoid getting responses that mark all features as ‘important.’


What are the benefits of Constant Sum?

Constant sum derives data from respondents by making them distribute points to various options provided, which adds up to a predetermined total score. Constant sum offers the following advantages.


Proper Demarcation

Constant sum enables an analyst to establish clear demarcation regarding the various attributes associated with the subject under study- if it’s a product, the features offered by it, for instance. While the rank order question type only gives an idea of the respondent’s preference, constant sum gives a ‘preference-by-how-much’ idea


Easy to Employ

The constant sum question type is easy to implement and gives profound insights into customer preferences. You can not only understand which option is customer-favorite but also understand by what factor. To get this data, all you need to do is add the constant sum question type in your online surveys.


Data Integrity

Constant sum prompts respondents to allocate scores to various attributes based on their preferences. And, the sum of all the points must add up to a predetermined value. This gentle constraint makes respondents weigh their options carefully before making a choice. Instead of randomly answering all features as essential or important, they would take a moment to reflect on the factors that matter to them. Consequently, you get better results for your online surveys.


What are the challenges of Constant Sum?

Even though constant sum enables you to get metric data for customer preferences, there are some challenges associated with it.


The respondent might miscalculate and set higher or lower points for the features. If the number of attributes listed is many, the respondents are left with the burden of making cumbersome calculations, which leads to confusion and, ultimately, survey abandonment.



To design effective constant sum questions, limit the number of options presented, ensuring they are informed by qualitative research and randomized to prevent bias. Set a clear pre-specified total that values must add up to, allowing respondents to allocate numerical values across variables. These practices promote mindful choices, generate metric data, and facilitate understanding of respondents' priorities.
To prevent order bias in a constant sum question, it is recommended to randomize the order of the options presented to respondents. By presenting the options in a random order for each participant, you can reduce the influence of any systematic bias that may arise from the order in which the options are listed.
When determining the options in a constant sum question, it is important to base them on prior qualitative research. Keep the number of options manageable, ideally between 5-7, to make it easier for respondents to allocate their points effectively. Randomize the order of the options to prevent order bias and ensure fair representation.
Constant sum questions involve allocating a fixed sum of points or resources among options, unlike rating questions that assign independent values and ranking questions that prioritize options based on importance or preference.
It is recommended to present a limited number of options, ideally between 5 to 7, in a constant sum question to avoid overwhelming respondents and facilitate easier allocation of points.

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