Selecting Effective Product Claims in CPG/FMCG


Posted on 1 May 2019


What is a claim?

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.

Benefit     Reason to Believe     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.

Benefit     Reason to Believe     Targeting     

Alternatively, you can group claims by; feature/flavor, process, for a specific person or other.

Table

Noteworthy linguistic factors

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.

Indicative Willingness to Pay

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.

Substitution for a similar statement

3.) Neologisms

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.

Neologisms

Ways to test claims in surveys

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.

How do you show claims?

Common forms of claims testing are:

  • MaxDiff - where the respondents pick the most appealing and least appealing claims;
  • Choice Based - where respondents choose the claims they prefer most;
  • Recall - where respondents need to remember which claims they just saw;
  • Association - where users associate themes or brands with statements;
  • Likert scale - respondents rank how strongly they feel from 1 to 5; and
  • Open-ended - where respondents can type free-form text about what they like or dislike.

Types of responses


MaxDiff vs adaptive choice-based test: Common survey flow

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 vs adaptive choice-based test survey flow
MaxDiff vs adaptive choice-based test survey flow
MaxDiff vs adaptive choice-based test survey flow

MaxDiff vs adaptive choice-based test: How MaxDiff works

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:

  1. List all claims;
  2. Respondents identify best and worst options in each question of claims; and
  3. All claims are ranked with good certainty.
MaxDiff vs adaptive choice-based test: How MaxDiff works
1.) List of claims


MaxDiff vs adaptive choice-based test: How MaxDiff works
2.) Respondents identify best and worst options in each question of claims


MaxDiff vs adaptive choice-based test: How MaxDiff works
3.) All claims ranked with good certainty


MaxDiff vs adaptive choice-based test: How adaptive choice works

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.

MaxDiff vs adaptive choice-based test: How MaxDiff works
1.) List of claims


MaxDiff vs adaptive choice-based test: How MaxDiff works
2.) Respondents identify best option in each question (not worst) and survey adapts to focus on more promising claims


MaxDiff vs adaptive choice-based test: How MaxDiff works
3.) All claims are ranked, with greater certainty for top 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

What’s wrong with MaxDiff


X “Worst” is not very relevant because we are usually interested in “best”

X Usually, not mobile friendly

X Unnatural task for respondents, takes longer

X Standard MaxDiff does not adaptively eliminate worst options

Cost savings from Adaptive Choice


MaxDiff vs adaptive choice-based test: Typical cost savings

Testing combinations of multiple claims: Structure of inputs

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.

Testing combinations of multiple claims: Structure of inputs

Testing combinations of multiple claims: Outputs for individual claims

The outputs for Generic Conjoint shows preference by attribute and claim with Claim Combination Test showing preference for each claim.

Testing combinations of multiple claims: Outputs for individual claims
Testing combinations of multiple claims: Outputs for individual claims

Testing combinations of multiple claims: Outputs for combinations

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).

Testing combinations of multiple claims

Test up to 300 product claims with Conjoint.ly

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.


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