Conjointly Claims Test is a powerful and comprehensive methodology for testing up to 300 product claims that helps you identify the most convincing claims for your brand or product category. It combines several techniques that Conjointly researchers have developed and refined on full-service projects for FMCG brands:
- Choice of most motivating claim among a set of several claims (similar to conjoint analysis).
- Adaptive experimental design algorithm that reduces sample size and brings clarity around top claims by zooming in on most promising claims.
- Diagnostic questions using Conjointly's unique dual negative-positive scale to help you get a de-biased view of how your customers see each claim and compare results across cultures and countries.
- Brand associations to help you check which brand each product claim is most closely associated with.
- Open-ended feedback showing both positive and negative reactions to each claim.
Using Claims Test Tool to find the top performing claim with a strong brand association.
Respondents choose the most motivating claims and then review claims separately.
Claims Test surveys can be automatically translated to more than 30 languages.
Bring your own respondents or buy quality-assured panel respondents from us.
Summary of preferences and diagnostics for each claim
Compare performance of different claims on several metrics:
- Preference Score (and Rank) from choice-based questions where respondents pick the claims that motivate them most to buy your product.
- Diagnostics help you assess how respondents rate claims on either standard questions ("healthy", "relevant", "premium", etc.) or your own measures.
Summary of preferences and diagnostics by topic
If you group claims into different topics, this table will summarise average scores (both preference and diagnostics) for these topics.
Correlations of relative preferences for claims among respondents
Do you want to know whether people who like the claim "Naturally sourced ingredients" also like the claim "Great tasting yogurt"? With this table, you can explore what preferences are correlated and which ones are not.
This output provides a clearer understanding of the relationship between claims: A positive correlation between Claims A and B indicates that respondents who like Claim A tend to also like Claim B.
This output is only available for test of up to 50 claims.
Brand associations for each claim
If you are testing a generic product, you can add a list of brands. We will check which brands respondents associate a particular claim with. If you are testing your own branded product, add sub-brands and brand extensions. This table will summarise what percentage of respondents associate each claim with different brands.
Passport of a claim
Each claim gets its own passport that shows how well it performs on each metric and shows positive and negative reactions to claims.
Claims that are among top claims and also perform well on diagnostics receive a seal of approval as Winning Claims.
TURF stands for Total Unduplicated Reach and Frequency. It is a technique that came into prominence during the 1950s in the space of media planning. In this report, we are only using the "reach" component of this technique.
Reach is the percentage of respondents for whom at least one of the claims in a particular combination is their most preferred claim. That is, it is a measure of how many respondents can be "activated" by a combination of claims.
Importantly, claims are tested one-by-one (not in combinations). Therefore one must be careful not to misinterpret this as ranking of preferences for combinations of claims.
This output is only available for testing up to 50 claims.
Complete solution for 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.