Claims Combination Test
The Claims Combination Test is used when your product has several claims. To learn more
about Claims and Claims Testing, please refer to our article on claims testing for consumer goods. We’ve created the Claims Combination Test
using a methodology perfected over numerous projects with FMCG brands, allowing you to find the best
combinations of claims from a list of up to 100 individual claims ranked on preference share.
Conjointly’s unique methodology:
- Leverages a unique twist on choice-based experimental design to simultaneously provide insights on product features and pricing.
- Simulates preference share to compare performance of different claims combinations against competitors.
- Offers various diagnostic options to measure how well claims perform on standard measures, e.g. attractiveness, naturalness – or your own metrics.
Using Claims Combination Test to assess claims in combinations of 3 along different levels of pricing.View case study
Respondents are asked to choose between one of four claims, arranged in various combinations.Take example survey
Claims Combination Test surveys can be automatically translated to more than 30 languages.View translations
Bring your own respondents or buy quality-assured panel respondents from us.Get respondents
Ranking of Singular Claims by Preference
Examining Claims Correlation
Simulating Preference Share
Preference share simulation showing the example product with different claims combinations identified the top claims combinations.
Analysing the Top Ten Claims Combinations
The share of preference in our example show shows that using claims combinations across both Benefits and RTBs takes the highest preference share.
Simulating Volume/Preference Shares
Analysis of Source of Business
Single Claims Test vs. Claims Combination Test
Claims Test produces lists of the top combinations of claims through TURF analysis that “reach” the largest number of customers. This can be problematic when testing combinations as TURF may recommend several claims that serve a similar purpose which can be detrimental to the effectiveness of the messaging.
Claims Combination Test ranks claims combinations on simulated preference share, giving a direct answer to the question of which claims combinations will get the most people interested in your product.
A list of competitor products provided by BrandCo to test their claims against, including product images, current claims, and prices.
BrandCo also provided 15 claims to be tested organised into two topics: Benefits and Reasons to Believe (RTBs).
Unlike standard conjoint testing, a Combination Test allows claims to be arranged flexibly in various combinations, and more rules can be used to sort claims.
Commonly, this test is done in two stages:
Stage 1: BrandCo claims were tested against competitors’ claims to find the claims most effective at taking market share.
Stage 2: BrandCo claims were tested against each other to “sort” claims and refine combinations.
Fully-functional online survey tool with various question types, logic, randomisation, and reporting for unlimited number of responses and surveys.
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.
Efficiently test up to 300 product claims on customer appeal, fit with brand, and diagnostic questions of your choice.
Pricing, feature and claim selection in markets where product characteristics vary across brands, SKUs, or price tiers.
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.
Test pricing of new and existing consumer goods in a competitive context using elasticity charts, revenue, and profitability projections.
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.
Perform focussed comparisons between two items to determine which performs better.
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.
Test the effectiveness of your digital advertisements in an online environment
Efficiently evaluate potential business names to identify the best one to represent your brand
Efficiently test potential images to identify the best one for your ads
Efficiently test ad copy to identify the best one for your campaign
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 print ads to identify the best one for your campaign
Efficiently test out-of-home ads to identify the best one for your campaign
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
Efficiently test potential logos to identify the best one for your ads
Efficiently test packages to identify the best one for your product
Efficiently test product concepts to identify the best one for your business
Efficiently test graphic designs to identify the best one for your brand
Conduct automated TURF analysis on results of any Conjointly experiment (or an outside dataset) using this user-friendly TURF analysis tool.
Allowing advanced choice modellers to upload their own experimental designs and perform data collection on Conjointly.
Ensure product-market fit and maximise your user acquisition and expansion, by differentiating software features according to your users' needs.