What is Constant Sum Scale

What is Constant Sum Scale?

Constant sum scales ask people to spread a set number of points or percentages across a group of items based on how important or preferred they are. This approach helps capture the relative weight or value people give to each option giving a deeper look into what matters most to them.

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 that 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.”

You will most likely 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.’

How to create effective Constant Sum Surveys: Best practices

Creating an effective constant-sum survey is both an art and a science. It involves understanding your audience, crafting questions that are clear and meaningful, and ensuring the survey design encourages accurate and insightful responses. Here are some key tips and best practices to guide you in designing your constant sum surveys:

Remember, simplicity is key

Craft questions that are straightforward and avoid technical jargon. The goal is for respondents of all backgrounds to understand what is being asked without confusion. You must also take care to include concise instructions on allocating points. For example, “Please distribute 100 points among the following features according to their importance to you. Ensure the total adds up to 100.”

Thoughtful Attribute Selection

Choose attributes that are relevant to the subject matter and balance them in terms of number and scope. Too many options can overwhelm respondents, while too few might not capture the necessary data. Ensure that the attributes cover a broad range of aspects related to the topic to get a comprehensive understanding of respondent preferences.

Survey Layout and Design

When you’re running online surveys, use a clean layout with an intuitive design. Features like sliders or input boxes should be easy to use and visually appealing. If your survey is long, include progress bars or indicators. This helps reduce survey abandonment by showing respondents how much they have completed and how much is left.

Conduct a test run

Before rolling out your survey to a broader audience, conduct a pilot test with a small group. This helps in identifying any confusing elements or technical glitches. Gather feedback on the survey experience from your test group and make necessary adjustments based on their insights.

Employ data integrity measures

Implement checks to ensure that the total points allocated by respondents always sum up to the constant total. This prevents incomplete or incorrect submissions. For surveys, consider using guided input options like sliders that automatically tally to the constant sum, reducing the chance of calculation errors.

Encourage thoughtful responses

Ensure that the questions and the way they are framed do not lead respondents towards specific answers. Remain neutral in your wording. Sometimes, respondents might not have a strong opinion about specific attributes. Including an ‘Unsure’ option can help in capturing this sentiment accurately.

Analyzing Responses

Understand that constant-sum surveys can yield a wide range of responses. Be prepared with a robust analysis plan that can handle this variability. In your analysis, look for patterns and trends in how points are allocated. This can provide deeper insights into customer preferences and behavior.

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.