Ranking Survey Maker: Free Template, Examples

Overview: A ranking survey measures preferences by asking respondents to order items by importance, either all options or only their top choices. Results include overall ranking scores, first-place counts, and distributions that show how each item performed across the audience.

Getting Started: Create a ranking survey with one click using our free template. Calculate results instantly and analyze segments to uncover what matters most to your audience. Perfect for market research or general feedback.

Crafting the list of attributes is the most crucial step in creating a ranking survey. Each item should be distinct, clearly worded, and easy to understand. Avoid long phrases or technical wording, as this makes it harder for respondents to evaluate and compare options.

Keep the list manageable. More than ten attributes can overwhelm respondents and reduce data quality by increasing cognitive effort.

Define how the ranking data will support your research goals, and include a few supplemental questions to add context. For instance, in a market research study, pairing a ranking question with a household income question allows you to segment preferences by income group.

Place the ranking question near the start of your survey, ideally on page one, so you capture critical data even if some respondents drop off later. Supplemental questions can follow on page two. If you’re using a survey panel, you can reverse this order, since compensated respondents are less likely to drop out early.

When creating a ranking survey, you’ll have several configuration options you can adjust based on your study’s needs.

• Require an answer (can not proceed until answered).
• Define how many attributes to rank, for example, top three or top five.
• Clear the selected choices so respondents can start over.

There are two survey ranking question types you can choose from: click ranking or drag and drop. Below are the details of each along with interactive examples. Depending on your project one type might be more beneficial than others. Both types of ranking questions display the results the same.

Click-to-rank questions are perfect for quickly determining what matters, like in a customer feedback survey. This ranking question lets respondents order preferences with a tap, delivering fast, actionable insights without dragging options.

This type is ideal when you know your audience will mainly be on mobile devices. Scrolling a large list and dragging on a mobile device may not be an ideal option, leading to user frustration and possibly drop-off rates.

This type is also ideal when lists are smaller, like five to ten items, and you're asking to rank a top three.

A drag-and-drop ranking question is ideal when you're doing more advanced research, and respondents may need to take more time evaluating options. Drag-and-drop makes it easy to reorder and visualize preferences.

This type is ideal when you know your audience will mainly be on desktop devices, as it is much easier to drag and drop, especially large lists, with a larger screen and mouse.

This type is also ideal when lists are more extensive, roughly ten items or more.

SurveyKing gives you control over how respondents rank items. You can require them to rank every option or allow them to focus on just their top selections, for example, the top three out of ten. This flexibility creates a faster, more focused experience and reduces the cognitive load of comparing long lists.

Limiting ranking to top choices doesn’t just improve completion rates; it also sharpens the insights. When respondents evaluate only the items that truly matter to them, the resulting scores better reflect genuine preferences rather than forced comparisons. This makes the data more actionable for product teams, marketers, and researchers.

Other tools, including SurveyMonkey, require respondents to rank all options before submitting, even when many items are irrelevant. The flexibility to rank only the top three makes SurveyKing an excellent SurveyMonkey alternative, a faster, more intuitive solution for collecting cleaner, more meaningful ranking data.

While ranking questions can be highly beneficial, they come with a few important limitations:

• No measure of preference strength: A significant drawback is the inability to quantify the degree to which someone prefers one item over another. For example, if "Banana" and "Chocolate" are the top two flavors, there's no way to tell if people like Banana slightly more or 100 times more. That missing context can lead to poor prioritization, especially in product development or marketing decisions.
• Survey fatigue and cognitive overload: Evaluating a long list of items can overwhelm respondents. Even with simplified input types like click ranking, people must consider the entire list before making choices. This mental load can introduce errors, especially when more than 10 attributes are ranked.
• Primacy bias: Respondents tend to rank items that appear first more favorably, particularly when fatigued or on mobile devices. This order bias can skew results, making it seem like certain items are more important than they actually are.

A solution to these issues is MaxDiff survey. Instead of asking respondents to rank everything at once, MaxDiff presents small, randomized sets of attributes (e.g., 5 out of 10) and asks for the most and least important in each set. Over multiple sets, this approach generates more precise, reliable data.

Using the same food-flavor example, MaxDiff would force respondents to directly compare "Banana" and "Chocolate" in context, giving you a clearer picture of which option has more substantial preference weight. The result is a more defensible, data-driven insight into what truly matters most.

The ranking score is a weighted calculation. Items ranked first are given a higher value or "weight." Each option's score is calculated by summing the weighted values. For example, if there are five options, the weighted sum for an option a respondent placed in the first position (1) would be worth 5. The points are summarized, and the item with the highest points is ranked first.

The results include how often an item was ranked first and display the ranking distribution with a small bar chart. The color-coding of the ranking distribution makes it easy to see net top/bottom rank attributes.

The Excel export will display each attribute as a column with the respondent's ranking. The column would be blank if a respondent did not rank an attribute.

The sample data below are the results of the click ranking survey used by the food manufacturer. Each attribute has a row with the ranked distribution, first-place counts, and total score.

A feature unique to SurveyKing is the ability to create a segment report for a ranking question. This report type is helpful to drill down into the data and spot hidden relationships. For example, you might include a question in your survey that asks for the respondents' gender. You could then create a segment report (or a cross-tabulation report) by gender. The results would include the table shown above for both "Male" and "Female". You may notice "Males" prefer a particular attribute that females do not prefer or vice versa.