Definition: MaxDiff analysis, also known as the best-worst scaling is an analytic approach used to gauge survey respondents preference score for different items. MaxDiff analysis is similar to the conjoint analysis in many ways. However, the only visible difference being MaxDiff is easier to use and is more comprehensive when you want to analyze critical research situations.
Message testing, customer satisfaction, brand preference, and product features are the typical surveys where researchers use MaxDiff analysis to predict outcomes. Maximum Difference Scaling or MaxDiff question involves the ‘Best’ and ‘Worst’ scales in a given set. Researchers ask the respondents to pick the most and least important factors in given answer options.
To understand the absolute importance of attributes in MaxDiff, you can use anchored MaxDiff scaling in your survey. With the addition of a simple question, you can derive the fundamental importance of features in your survey.
Researchers use MaxDiff for:
MaxDiff example: A smartphone making company is interested in launching a new smartphone. However, before launching the new phone, they are interested to understand what features prospective customers are looking for. MaxDiff analysis helps researchers prioritize features that impact the customers buying decision.
The company conducts a MaxDiff survey to understand the must-have features and to know the features that will make a difference. Suppose a smartphone making company has detailed knowledge of how customers perceive their preferences or attributes, they can create smartphones with a wide range of valuable features to the customer.
Before explaining how to use a MaxDiff question, you must get acquainted with the standard terms of the MaxDiff analysis question.
In MaxDiff surveys, researchers display a set of attributes and ask respondents to choose the ‘most’ and ‘least’ items in the features.
Here is a MaxDiff example created using our online survey platform. In the adjoining steps, you will understand how to use a MaxDiff question in your online survey.
Here you can select the maximum attributes you want to be displayed. You can decide several attributes per task and also choose the attributes you wish to repeat. Additionally, you can also select whether you want to randomize the attribute display or not.
The number of task count shown to each respondent is based on the total number of attributes tested and the number of points you wish to display.
After conducting the MaxDiff survey, it is time to analyze the collected data.
MaxDiff analysis as a whole helps you understand why most of the respondents prefer a few attributes most and a few attributes least.
Researchers have found out that rating questions are susceptible to user scale bias, scale meaning bias, and lack of discrimination. Additionally, ranking questions have limitations of their own like being over bias, difficult for respondents to evaluate, limitation in testing number of items, ordinal data obtained limiting the analysis, and not allowing ties.
Constant sum questions also have the same limitations and loopholes. Furthermore, researchers have seen that when presented with constant sum questions, respondents try to make the task of evaluating all the items easier by engaging in the response strategies.
Having understood the problems and limitations of different survey question types, especially with rating scale questions, researchers prefer to use the Maximum Difference Scaling or MaxDiff survey as we call it. We can perceive MaxDiff analysis as a trade-off analysis technique allowing researchers to conduct multiple pairwise comparisons.
By effectively using the MaxDiff question, researchers could ask the respondents to select the most and least preferred or important points from the given list of answer options they are interested in testing for the most remarkable difference amongst items.
Look at the above image, and you will understand the primary difference between a rating scale question and a MaxDiff question.