Posted on 1 May 2019
A claim is an assertion about a product across any channel, such as; advertising, digital promotions, public statements, or product packaging. However, consumer insight, pricing and logos are not considered as claims and should not be tested in the same manner.
We can group claims by their content into three key categories, which are; benefit, reason to believe (RTB) and targeting.
The benefit can be broken down further into four sub-categories that are most commonly seen as driving benefit for the consumer, which are; feature/flavor, functional, emotional, and societal/moral.
The reason to believe (RTB), can be commonly seen as; sourcing or appellation, process, ingredients or composition, certification, and experience or branding. Targeting is commonly seen as; for a specific occasion, and for a specific person, with all other categories grouped as such.
Alternatively, you can group claims by; feature/flavor, process, for a specific person or other.
1.) Length of text
When testing claims, the below trend commonly emerges showing indicative willingness to pay strengthening in line with the length of characters in the claim. While limitations such as space on the packaging or number of claims on the packaging may limit your ability for longer claims, it is still worth considering that longer claims consistently outperform shorter claims. One possibility for this trend could be that longer claims present more information which are in turn more persuasive.
2.) Substitution for a similar statement
Substitution for a similar statement can be just as appealing to consumers and may potentially reduce manufacturing costs. Consumers react very similarly to the below example, although the manufacturing process can be cheaper when referring to the second claim.
A newly created name which lacks any prior meaning is known as a neologism which can be helpful to; describe the chemical makeup of a product and simplify complicated names or define a scientific process. Neologisms can be very powerful when used within claims and can be seen to perform strongly with old and new products alike.
Claims can be shown as either a single claim or a combination of claims. A single claim, such as, “with the special taste of raw milk” could be shown on packaging on its own or in combination with one or more other claims.
Common forms of claims testing are:
MaxDiff and choice-based claims testing have a similar overall survey flow, which starts with listing the claims you wish to test. The MaxDiff or choice-based component of the experiment is followed by; brand association, attitudes along with key metrics, and free form feedback.
MaxDiff assumes that respondents will evaluate all possible pairs of items that are presented to them and they will choose the pair with the maximum difference in preference or importance.
The below is the flow of a MaxDiff experiment:
Adaptive choice-based experiments are used when the number of attributes or claims exceeds a reasonable number that can be tested in a standard choice-based experiment. This experiment type allows for testing up to 300 claims, with respondents identifying the best option in each claim (not the worst) and the survey adapts to focus on the more promising claims.
Several components of MaxDiff add unnecessary frustration and time to respondent completion. Fifty percent of respondent time is spent on finding the “worst” scenario, which is irrelevant to seeking the most commonly sought output of the “best” scenario. Additionally, the layout of MaxDiff does not optimize well for small screened mobile devices which commonly extends time spent and frustrates respondents. Respondents are also commonly frustrated by picking the best and worst scenarios, which is not reflective of natural decision-making processes, as naturally respondents are inclined to only select the “best” scenario.
Adaptive choice can reduce sample cost by up to 40% compared to MaxDiff. This figure is made up of a 10% saving from shorter survey length and a 30% saving from needing a smaller sample due to adaptiveness
Not all combinations of claims are mutually exclusive an therefore cannot be tested in the same manner. For example, “56 years of chocolate-making magic” and “Over 50 years of chocolate-making magic” are too similar and cannot be combined. If unlike the previous example all your claims fall into mutually exclusive categories, they can be tested using Generic Conjoint, otherwise Claim Combination Test should be used.
The outputs for Generic Conjoint shows preference by attribute and claim with Claim Combination Test showing preference for each claim.
Testing combinations of claims is used when not all combinations of claims are mutually exclusive and provides outputs for preference share (vs. competitors) and preference index (no competitors).
Do you want to efficiently test up to 300 product claims on customer appeal, fit with brand, and diagnostic questions of your choice? Conjoint.ly Claims Test is a powerful comprehensive methodology for testing up to 300 product claims that helps you identify the most convincing claims for your brand or product category.