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Do you need support in running a pricing or product study? We can help you with agile consumer research and conjoint analysis.

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BSC

Brand-Specific Conjoint

Brand-specific conjoint is a discrete choice method for markets where potential product characteristics vary across brands or SKUs (it is commonly the case in FMCG, telco, home appliances, and tech). Technically known as choice-based alternative-specific/labelled conjoint design, it is used for:

  • Feature selection for new or revamped products.
  • Pricing your product, taking into account competitors' offerings and pricing.
  • Testing branding, packaging and advertising claims.

Using Brand-Specific Conjoint to test preference share and revenue before resetting prices.

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The survey flow consists of approximately 12 questions with different SKUs to choose from.

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Brand-Specific Conjoint surveys can be automatically translated to more than 30 languages.

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Bring your own respondents or buy quality-assured panel respondents from us.

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Main outputs of Brand-Specific Conjoint

Share of preference simulation

Share of preference simulation

Estimate share of preference based on customers' revealed preferences.

You can run "what-if" scenarios to see how consumers will behave if you change features of your product. Learn more about preference share scenario modelling.

Understand amount of interest in new product launches

Understand amount of interest in new product launches

Through preference share simulations.

Run "what-if" scenarios to measure the amount of interest in new product ideas, compare with current SKUs and assess sources of business (i.e. if you are sourcing from competitors or cannibalising your product line).

Price elasticity of demand

Price elasticity of demand

Estimate consumers' sensitivity to price changes and its effect on sales.

Run "what-if" scenarios to assess consumers' reactions to price increases or decreases in the context of your other SKUs and competitor offerings. Project revenue levels at different pricing options to select optimal pricing for your new or existing SKUs.

Relative performance of brands

Relative performance of brands

Performance of different brands, considering their best variants.

Conjoint.ly estimates how strongly customers prefer different brands of products, taking into account the different variants (combinations of features and prices) presented to them. In this example. Telco A is the strongest performer, while Telco E lags behind.

Partworth utilities

Partworth utilities

Importance of product characteristics and performance of different features.

Conjoint.ly estimates how important each attribute is relative to the other attributes in customers' decision-making process. This is called relative importance of attributes. For example, in this test for Telco A, coverage is approximately three times as important as price (given the range of price levels tested) - 54 points vs. 16 points.

Each level of each attribute is also scored for its performance in customers’ decision-making. This is called relative performance of levels. For example, for Telco A there is clear preference for nationwide coverage over metro areas, and for metro areas over downtown-only coverage.

Ranked list of product constructs

Ranked list of product constructs

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 ranked them 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.

Segmentation of the market

Segmentation of the market

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), or GET variables. For each segment, we provide the same detailed analytics as described above.


Learn more about conjoint analysis

What is Conjoint Analysis?

Conjoint analysis is one of the most widely-used and powerful quantitative methods in market research. Discover how it works and where to use it.


Complete solution for pricing research

GC
Range optimisation
Features and claims

Generic Conjoint

Feature and claim selection and measuring willingness to pay for features for a single product.

BSC
Pricing research
Range optimisation

Brand-Specific Conjoint

Feature and claim selection and pricing in markets where product characteristics vary across brands, SKUs, or price tiers.

CT
Features and claims

Claims Test

Test pricing of new and existing consumer goods in a competitive context using elasticity charts, revenue, and profitability projections.

MT
Concept testing

Monadic Test

Compare performance of concepts or products though focussed testing

AB
Concept testing

A/B Test

Perform focussed comparisons between two items to determine which performs better.

TURF
Range optimisation
Features and claims

TURF Analysis Simulator

Conduct automated TURF analysis on any dataset using Conjoint.ly’s user-friendly TURF analysis tool.

FST

Free Survey Tool

General survey with standard question types, randomisation blocks, and image standardisation.

DIY

DIY Experimental Design

Allowing advanced choice modellers to upload their own experimental designs and perform data collection on Conjoint.ly.

BPTO
Pricing research

Brand-Price Trade-Off

Test pricing of new and existing consumer goods in a competitive context using elasticity charts, revenue, and profitability projections.

MD
Range optimisation
Features and claims

MaxDiff Analysis

MaxDiff analysis for robust ranking of flavours of your product by consumer preference; or usage occasions by frequency.

PVS
Range optimisation

Product Variant Selector

Feature and claim selection and pricing in markets where product characteristics vary across brands, SKUs, or price tiers.

GG
Pricing research

Gabor-Granger Pricing Method

Determine price elasticity for a single product and identify revenue-maximising price level.

VW
Pricing research

Van Westendorp Price Sensitivity Meter

The Price Sensitivity Meter helps determine psychologically acceptable range of prices for a single product and approximately estimate price elasticity.