How to prioritize product features using MaxDiff and TURF analysis

At a glance

Product feature optimization provides actionable market insights by evaluating target audience preferences across competing product features, so teams can rank, combine, and invest in the features that drive the most customer value. It relies on trade-off methods like MaxDiff and TURF analysis rather than simple ratings, which tend to make every option look equally important.

Product feature optimization is the process of using structured customer research, rather than internal opinions, to decide which product features to build, keep, or cut. Instead of guessing which features matter most, teams run a feature prioritization survey that forces respondents to make real trade-offs between options.

The two building blocks behind most product feature optimization studies are MaxDiff analysis (which features matter most and least) and TURF analysis (which combination of features reaches the broadest share of your audience). Together, they turn a long feature backlog into a ranked, evidence-backed roadmap.

The fastest way to run this kind of study without a dedicated research team is to start from a proven framework rather than building a survey from scratch. SurveyMonkey's Product Feature Survey template gives you pre-written, expert-designed questions you can customize for your own feature list, so you can move from open questions to a prioritized list of features in days, not months.

MaxDiff (maximum difference) analysis, also known as best-worst Scaling, is a trade-off research technique used to quantify preferences.

It helps you to sort features, messaging, brand names, and more, according to customer preferences. MaxDiff also allows you to test combinations of similar features. By identifying what consumers want most, you can maximize your time and capital on efforts that truly affect your customers’ purchasing decisions.

Keep in mind that although MaxDiff provides quantitative data, your results can also be considered qualitative because the analysis shows how important your attributes are relative to each other, not how important they are in general.

MaxDiff analysis uses survey research methods to ask participants to choose among several options at once by selecting only the best and worst options. By eliminating potentially vague mid-range responses, there’s no guesswork involved in understanding what participant answers mean. 

MaxDiff analysis may bring conjoint analysis to mind. The methodology in conjoint analysis is similar, but instead of going through several iterations of tradeoffs, MaxDiff limits the number of decisions the participant has to make but still provides actionable insights.

Best-worst scaling questions use attributes (a property, item, or feature to be measured) and sets (a group of attributes provided to participants). MaxDiff questions can be asked as part of a longer market research questionnaire or in a standalone survey. 

Traditional ranking and rating questions, such as Likert scales, allow survey respondents to choose along a scale or rank items on a continuum. MaxDiff forces respondents to choose only the most and least important options. This type of analysis is immune to user scale bias, scale meaning bias, lack of discrimination, and other types of survey bias that can plague rating and ranking questions.

Example of a traditional ranking question

"Please read through the following list of smart television features and rank them in terms of your priority."

Example MaxDiff question

"Please indicate the smart TV feature that would be the most important in your purchase decision and which feature would be the least important."

MaxDiff is critical for finding out what your target customers value most. There are several advantages to using MaxDiff.

Now that you know what MaxDiff is and why it works, here's how to apply it to feature prioritization. You can build this manually, or use an automated feature prioritization survey solution, like SurveyMonkey's Feature Prioritization solution, to handle the analysis and reduce the risk of human error.

Before you can begin to develop your survey questions, you need to determine which features you want to evaluate. Sit down with project stakeholders and choose 12-25 features. This range offers the best number of comparisons to determine each feature’s relative importance.

You can design your own study or create it with the assistance of the market research consultants at Momentive. Your survey should offer attributes divided into subsets, with one subset of three to five features provided for each question. Using a tool helps you to generate subsets randomly. This allows you to obtain the most accurate, actionable data. 

If you’re creating your MaxDiff analysis manually, keep in mind that the experimental design must contain:

Use the following formula to determine how many sets are required:

# of times to show attribute = total attributes / # of attributes per set

Following these guidelines means that respondents will see each feature once during the survey, but not necessarily every combination of features in a set.

If you use a tool, it will provide you with a statistical analysis of your data. For manual analysis, you’ll need to calculate the MaxDiff. 

The data in this table indicates that 100 respondents said that Feature 1 is the most important feature and only 20 of 200 selected it as least important.

(most important - least important) / total responses

Your table should now look like this:

Magnitude is measured on a scale from -1 to 1. The closer the magnitude is to 1, the stronger users prefer that feature. Data from this calculation can be put into a graph for easy visualization.

Once your analysis reveals which features your customer would value most, take your data and analysis back to stakeholders. You’ll be able to make informed decisions about prioritizing your feature selections.

Let’s look at examples of MaxDiff determining feature prioritization. 

You are in the hospitality industry and are in charge of remodeling one of your resorts in the northern US. It’s a costly venture, so you want to know what is most important to vacationers in your target market.

You create a list of features you might want to upgrade in the resort:

Question 1

Of the following features, please indicate which is the most important and which is the least important when choosing a vacation resort:

Question 2

Of the following resort features, please indicate which is the most important and which is the least important when choosing:

The remaining questions will continue with various subsets comprised of the features you want to evaluate. The questions will include frequency balance, orthogonality, and position balance.

You submit your MaxDiff survey to 300 members of your target market. The data reveals that, of the 300 responses, most participants consider an indoor pool and a free breakfast to be the most important options. 

This data is presented to management, and feature prioritization is decided based on the data.

The airline you work for wants to know what features will make customers choose them over the competition.

You create a list of features that could be initiated or changed at your airline:

Question 1

Which of the following features would be most likely to factor in your choice of a particular airline, and which would be least likely to make you choose it?

Question 2

Which of the following features would be most likely to factor in your choice of a particular airline, and which would be least likely to make you choose it?

Your remaining questions continue with various subsets comprised of the features you want to evaluate. The questions will include frequency balance, orthogonality, and position balance.

You submit your MaxDiff survey to 500 travelers in your target market. The data reveals that, of the 500 responses, most travelers would prefer more legroom significantly more than any other feature.

This data is presented to management and target flights are chosen to increase legroom.

Both MaxDiff and conjoint analysis measure trade-offs, but they solve slightly different problems, and the right platform should support the method that fits your question. The table below compares the two approaches so you can decide which one, and which platform capability, fits your next study.

If your question is "which of these features matters most, and which combination covers the most customers," MaxDiff plus TURF is the more direct path — and it's the method built into SurveyMonkey's Feature Prioritization solution.

Beyond feature prioritization, MaxDiff analysis is useful any time you want to quantify what your target market values most. Common applications include:

It's the practice of using customer research, typically MaxDiff and TURF analysis, to decide which product features to prioritize, based on evidence rather than internal opinion.

MaxDiff is the underlying method; a feature prioritization survey is the vehicle that puts MaxDiff questions in front of your target audience so you can collect and analyze the results.

It depends on your question. If you need to rank many individual features and find the best combination for broad appeal, a platform with built-in MaxDiff and TURF automation, like SurveyMonkey's Feature Prioritization solution, removes the need for specialist statistical expertise. If you need to model complex attribute-and-price interactions, evaluate a platform against your specific conjoint requirements.

Most feature prioritization studies work best with 12 to 25 features. That range gives you enough comparisons to produce reliable rankings without overwhelming respondents.

No. SurveyMonkey's Feature Prioritization solution automatically generates statistically balanced question sets and handles the analysis, so you don't need a quant background to get rigorous results.

Don't spend time and budget on features your market doesn't actually want. SurveyMonkey's Feature Prioritization solution uses MaxDiff and TURF analysis to show you which features customers value most and which combination reaches the broadest audience without requiring in-house research expertise.

Prefer to build your own survey first? Start from the Product Feature Survey template and customize the questions for your feature list.

Start with the Feature Prioritization solution to automate your MaxDiff and TURF study end to end.