ADD-ON FEATURE: You can use this solution with our Audience collector on any SurveyMonkey plan type. Get started now, or explore our other market research solutions. This solution is available for US Data Center accounts only.
The Web Link collector is available on any paid plan.
The MaxDiff solution helps you understand what items or features matter most to your audience. This is helpful when you’re prioritizing new products or features and want to know what your customers care about most.
The solution is based on MaxDiff methodology. We create your survey questions using the items you enter. You don’t have to create each MaxDiff question yourself – you enter the items you want to include in your survey, and we create the questions.
The MaxDiff solution builds your survey questions using the items you enter. You don’t have to create each MaxDiff question yourself – you enter the items you want to include in your survey, and we create the questions.
Expand the dropdown to learn more about the experimental design.
MaxDiff is not a predictive model. It uses algorithmic predictions to estimate outcomes based on multiple-choice scenarios. We recommend that you provide your own notices about these tools to your respondents.
Results from your study are retained for 3 years. After 3 years, the results are deleted.
Learn how to build your MaxDiff study.
To set up your study:
To add survey components:
You can add additional custom questions to your survey to gather other important information from your target audience. You can:
MaxDiff questions are locked to protect our proven methodology and can’t be edited. You can preview them but can’t change them.
Select Preview survey from the top right corner to test your survey in a new window and see what it will look like to respondents. You can even share the preview with others to gather feedback.
Select Next: Collect Responses when you’re ready to send your study.
When you’re ready to send your survey, select the Collect icon from the left-side menu.
There are two ways to collect responses:
You can create multiple collectors for your MaxDiff study.
PAID FEATURE: Web Link collector for the Feature Importance (MaxDiff) solution is available on any paid plan. Free plans can use SurveyMonkey Audience to collect responses.
Create a web link that you can send your way. To share a survey link:
SurveyMonkey Audience panelists have been sorted based on hundreds of targeting options so you can target your respondents based on country, demographics, employment status, hobbies, religion, and more.
To choose your target audience:
Once you submit payment, we'll start gathering responses for your survey right away.
Select the chart icon on the left side of the screen to start analyzing your results. In the Analyze section, there’s an Overview, Counts, Empirical Bayes, Survey results, and Individual Responses.
Counts analysis shows you how often items were chosen as Best or Worst. This data helps you quickly understand how survey takers rated each item. You can view a few different data sets in the chart: Simple counts, Best counts, Worst counts, or Best and Worst counts.
View all data for each item in the table below your chart. The table also includes Count proportion, which is the quantity of Best or Worst counts divided by the number of times people saw the item.
Empirical Bayes shows how survey takers feel about each item. It estimates each item's likelihood of being chosen as Best, relative to other items.
Empirical Bayes calculates a utility score for each item, which is a measure of how well an item performed. We calculate this score across all sets and survey takers. We use the following data to calculate utility score for each item:
First, we combine all responses to find the utility score for each item. Then, we calculate an item's utility value for each respondent. If someone didn't see all items, we use Bayesian Pooling (or "Shrinkage") to estimate how someone would have responded to the item. We assume that they would answer similarly to the aggregate score, since it combines all responses. We "shrink" the survey taker's utility value toward the aggregate score for the item they didn't see. These scores help us estimate how likely it is that an item will be chosen as Best.
The chart shows the utility score for each item. A higher score means that an item is more likely to be chosen as Best and may be more important to your target audience.
Select a scale in the top right corner to change how you view the data:
The table below the chart shows each item’s score and the 95% confidence interval. The confidence interval is a range of scores that contains the score we'd see a certain percentage of times if we did the survey over and over. For example, an item has a 95% confidence interval of [13–14]. In other words, the item would score between 13 and 14 in 95 out of 100 repetitions of the survey.
On any page, select the Filters button above the chart to filter your data. Any filters you apply to one chart will also apply to others. For example, if you add an Age filter to your Counts analysis, we’ll also apply it to your Empirical Bayes analysis.
You can export Counts data, aggregated Empirical Bayes data, full response data, or individual responses.