Feature and claim selection and measuring willingness to pay for features for a single product.
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MaxDiff analysis is a technique for robust ranking of items. It can be used for ranking:
MaxDiff is a statistical relative of conjoint analysis. It derives its name from “maximum difference” scaling, also called best-worst scaling.
Traditionally, MaxDiff treats each product as an individual item, whilst conjoint treats products as a combination of attribute levels. As such, conjoint analysis produces rankings for particular products by summing the preference scores for each attribute level of that product whilst MaxDiff produces rankings by polling the respondents directly. However, Conjoint.ly’s novel robust approach to MaxDiff allows for:
Using MaxDiff Analysis to find out which colours are the most popular for the customers.View case study
MaxDiff polls the respondents directly about each product as an individual item.Take example survey
MaxDiff Analysis surveys can be automatically translated to more than 30 languages.View translations
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How do customers rank the potential phone colour options?
Each level of each attribute is also scored for its performance in customers’ decision-making. In our example, navy is the most favourable colour (relative to the other colour options), and displays as positive. Yellow is relatively the least preferred colour and therefore displays as negative. It's important to remember that performance score of each attribute is only relative to the other options shown to respondents. For instance, it is only certain that the colour red will display as negative when it is compared with this specific set of colours (levels) — testing red against a different range of colours, could yield a positive result.
List all possible level combinations and rank them by customers' preference.
Conjoint.ly forms the complete list of product constructs using all possible combinations of levels. They are then ranked based on the relative performance of the levels that they combine. This module allows you to find the best product construct that your customers will prefer over others.
Find out how preferences differ between segments.
With Conjoint.ly, you can split your reports into various segments using the information collected automatically by our system: respondents' answers to additional questions (for example, multiple-choice), simulation findings, or GET variables. For each segment, we provide the same detailed analytics as described above.