Claims Substantiation
Performance testing designed to support meaningful product claims
d-labs designs and conducts performance testing to help detergent and cleaning product companies generate technical evidence for product claims, comparative statements and market positioning.
Test programs are built around the specific claim being considered, with relevant benchmarks, controlled conditions, appropriate replication and statistical analysis used to determine what the performance data can reasonably support.
Claims Testing Capabilities
Performance evidence designed around the claim you want to make
d-labs designs claims testing around the specific performance statement being considered, selecting appropriate benchmarks, test conditions and analysis methods so the resulting evidence is relevant to the proposed claim.
Superior performance claims
Evaluate whether a product performs better than a specified competitor or benchmark under defined test conditions.
Comparative claims
Support statements comparing one product directly with another, such as improved cleaning performance or better performance against a defined benchmark.
Equivalence claims
Assess whether products perform similarly enough under the selected test conditions to support an intended equivalence position.
Performance improvement claims
Determine whether a new or reformulated product delivers a measurable improvement over the previous formulation.
Specific performance claims
Generate evidence around defined attributes such as stain removal, grease removal, cleaning effectiveness, foam performance or other relevant product characteristics.
Market positioning
Provide comparative performance evidence to help support broader product positioning against selected competitors or category benchmarks.
The strongest claims start with a clearly defined statement and a test designed specifically to evaluate it.
Test Design For Claims Support
The wording of the claim should determine the design of the test
A claims substantiation study should start with the exact statement the client wants to support. The wording of that statement influences the benchmark product, test method, performance measures, test conditions and level of replication required.
d-labs works with clients to translate the proposed claim into a technical question that can be evaluated objectively.
This helps ensure the resulting evidence is relevant to the intended statement rather than generating data first and trying to fit a claim around it afterwards.
Define the proposed claim
Clarify exactly what performance statement or comparison the test is intended to evaluate.
Select the right benchmark
Choose the competitor, previous formulation, reference product or control that is relevant to the proposed statement.
Match the test conditions
Configure soils, substrates, dosage, temperature, water conditions, product use and other variables so the test reflects the claim being assessed.
Set the evidence requirement
Determine the appropriate replication, performance measures and analysis needed to support a reliable conclusion.
Test the claim you intend to make — not simply the performance that is easiest to measure.
d-labs provides technical performance evidence and interpretation. Responsibility for final advertising, regulatory and legal compliance remains with the product owner.
Evidence & Statistical Analysis
Claims need evidence strong enough to support the conclusion
Performance differences can occur because of genuine product effects, but they can also arise from normal variation in the test system. Claims testing therefore needs enough replication and appropriate analysis to distinguish meaningful differences from random variation.
d-labs designs test programs with the level of replication appropriate to the product, method and proposed claim, then applies statistical analysis where relevant to determine how confidently the observed differences can be interpreted.
The objective is to generate evidence that is not only technically sound, but also clear enough to show what the results do — and do not — support.
Appropriate replication
Use sufficient repeated measurements to understand normal test variability and improve confidence in the result.
Statistical significance
Determine whether observed differences are likely to represent genuine product-performance differences rather than normal variation.
Evidence strength
Consider the consistency, magnitude and statistical reliability of the result when determining the technical conclusion that can reasonably be drawn.
A numerical difference is not automatically evidence of a meaningful performance difference.
From Results to Conclusion
Understand what the evidence supports — and where its limits are
A claims study should lead to a clear technical conclusion, not simply a table of results.
d-labs interprets the performance data in the context of the proposed claim, benchmark, test conditions and statistical outcome to determine what the evidence reasonably supports.
Where the results do not support the original statement, the findings can also help identify whether a narrower claim, different comparison or further product development may be more appropriate.
Clear technical conclusion
Summarise the outcome in practical terms, including whether the tested performance statement is supported by the data.
Evidence boundaries
Clearly identify the products, conditions and performance measures to which the conclusion applies, avoiding broader interpretation than the testing can justify.
Next-step guidance
Where the proposed claim is not supported, use the results to help determine whether the claim, product or test strategy should be reconsidered.
The objective is not to find a claim that fits the data — it is to understand what the evidence genuinely allows you to say.
Start a Claims Testing Project
Need evidence to support a product performance claim?
d-labs can design and conduct claims substantiation testing for detergent and cleaning products, using relevant benchmarks, controlled test conditions, appropriate replication and statistical analysis to determine what the performance evidence can reasonably support.