MaxDiff (also known as Maximum Difference Scaling or Best–Worst Scaling) is a statistical technique that creates a robust ranking of different items, such as product features. MaxDiff is an alternative to conjoint analysis from which the respondent has to indicate which feature is most important or most desirable, and which is least important or desirable. Conjointly’s novel robust approach to MaxDiff allows for:
- Testing of multiple attributes in the same survey
- Brand-Specific combinations of attributes for when each brand is substantially different (to enable that, first create a Brand-Specific Conjoint and then convert it into the MaxDiff variety)
- Simulation of preference shares, at a highly indicative level
Traditionally, MaxDiff treats each product as an individual item, whilst conjoint treats products as a combination of attributes and levels. As such, the conjoint analysis produces rankings for particular products by summing the preference scores for each attribute level of a product, whilst MaxDiff produces rankings by polling the respondents directly.
Using MaxDiff surveys to determine which colours are the most popular for the customers.
MaxDiff surveys ask the respondents directly about each product as an individual item.
MaxDiff questions can be automatically translated to more than 30 languages.
Bring your own respondents or buy quality-assured panel respondents from us.
Main outputs of MaxDiff Analysis
Relative value by levels
How do customers rank potential phone colour options?
Each level of each attribute is scored for its performance in customers’ decision-making. In our example, navy is the most favourable colour and is displayed as positive. Yellow is the least preferred colour and therefore displayed as negative. It's important to remember that the performance score of each attribute is relative to the other levels shown to respondents. For instance, the colour red will only be shown as negative when compared against a specific set of colours (levels) — testing red against a different range of colours could yield a positive result.
Ranked list of product constructs
List all possible level combinations and rank them by customers' preferences.
Conjointly 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 combined. This module allows you to find the best product construct that your customers will prefer over others.
Segmentation of the market
Find out how preferences differ between segments.
With Conjointly, you can split your reports into various segments using the information our system collects: 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.
Analyse with TURF Simulator
Conduct TURF analysis on MaxDiff data using the TURF Analysis Simulator.
TURF analysis aims to find the combination of items that appeals to the largest proportion of consumers. Conjointly makes conducting TURF analysis easy by letting you export your MaxDiff data directly into Conjointly's TURF Analysis Simulator with a single click.
Preference share simulations
View simulations of preference shares for your product with the Preference Share Simulator.
With Conjointly, you can simulate shares of preference and volume projections for different product offerings, including those that are available in the market. Learn more about using the simulator for MaxDiff.
What is the benefit of performing TURF Analysis on the results of a MaxDiff experiment?
TURF Analysis is a natural extension of MaxDiff, as it allows you to identify which combination of attributes will "reach" the most amount of consumers, where reach is defined as the percentage of respondents for whom at least one of the attributes in a particular combination is their most preferred.
When considering launching multiple products/features, the powerful TURF Analysis Simulator lets you use the results of your MaxDiff experiment to identify the combination of items that appeals to the largest proportion of consumers with a single click!
Can I use MaxDiff in combination with Van Westendorp analysis?
How do I make brand-specific combinations of attributes?
Complete solution for features and claims research
Fully-functional online survey tool with various question types, logic, randomisation, and reporting for unlimited number of responses and surveys.
Efficiently test up to 300 product claims on customer appeal, fit with brand, and diagnostic questions of your choice.
Identify winning product variants from up to 300 different ideas (e.g., designs, materials, bundle options) on customer appeal, fit with brand, and diagnostic questions of your choice.
Efficiently test product descriptions to identify the best one for your product
Feature and claim selection and measuring willingness to pay for features for a single product.
MaxDiff (aka Maximum Difference Scaling or Best–Worst Scaling) is a statistical technique that creates a robust ranking of different items, such as product features.
Pricing, feature and claim selection in markets where product characteristics vary across brands, SKUs, or price tiers.
Ask respondents to evaluate product concepts and digital assets one-by-one to get a read of their preferences and perceptions with various question types.
Efficiently evaluate potential business names to identify the best one to represent your brand
Efficiently test potential brand names to identify the best one to represent your business
Efficiently test potential domain names to identify the perfect new home for your brand
Efficiently test potential product names to identify the best one to reflect your brand
Efficiently test potential business card designs to identify the best one for your business
Determine price elasticity for a single product and identify revenue-maximising price level.
The Price Sensitivity Meter helps determine psychologically acceptable range of prices for a single product and approximately estimate price elasticity.
Conduct automated TURF analysis on results of any Conjointly experiment (or an outside dataset) using this user-friendly TURF analysis tool.
Test pricing of new and existing consumer goods in a competitive context using elasticity charts, revenue, and profitability projections.
Ensure product-market fit and maximise your user acquisition and expansion, by differentiating software features according to your users' needs.