Cosmetic Claims Substantiation

This topic is part of the SG Systems Global regulatory & operations glossary.

Updated November 2025 • EU Regulation 655/2013 (Common Criteria), EU 1223/2009, UK Cosmetics Regulation, MoCRA, FTC/ASA guidance • Regulatory, Marketing, R&D, Clinical, Quality

Cosmetic claims substantiation is the process of generating, evaluating and maintaining evidence that supports the marketing statements made about cosmetic and personal‑care products. It sits at the intersection of science, regulation and storytelling: enough data to satisfy regulators and courts, clear logic for internal reviewers, and simple messages for consumers. It covers everything from hard performance claims (“reduces wrinkles in 4 weeks”) and “dermatologically tested” logos to “fragrance‑free”, “clean”, “vegan”, “hypoallergenic” and sustainability positioning. Weak substantiation is not just a technicality—it is a direct route to enforcement actions, class actions, delistings and reputational damage.

“If you cannot show, on paper, exactly why a claim is true, assume regulators will treat it as if it isn’t.”

1) Purpose & Intent of Cosmetic Claims Substantiation

The purpose of cosmetic claims substantiation is to ensure that what is promised to consumers reflects what the product can reliably deliver, under defined conditions, for the intended population. Regulators talk about “truthful, honest, fair, evidence‑based” claims; brand owners should translate that into “defensible, repeatable, not wishful thinking”. Claims substantiation is not just a sign‑off step before launch—it is a continuous lifecycle activity that tracks formula changes, new data, evolving regulations and complaint trends.

The intent is threefold: protect consumers from misleading promises; protect brands and retailers from legal and regulatory exposure; and give internal teams a clear framework to decide what can be said and how aggressively. If your substantiation system cannot explain, in plain language, why a claim is valid and where the supporting data live, you do not have a system—you have a pile of PDFs and a liability problem.

2) Regulatory Framework: EU 655/2013, MoCRA & Consumer Law

In the EU and UK, cosmetic claims are governed by the “common criteria” in Regulation 655/2013: legal compliance, truthfulness, evidential support, honesty, fairness and informed decision‑making. These criteria apply to any claim—words, images, symbols—no matter the channel. EU 1223/2009 and UK cosmetics law also link claims to PIF content; authorities can request access to the full evidence package behind any claim used.

In the US, MoCRA reinforces the need for “adequate substantiation” of cosmetic safety, while truth‑in‑advertising laws (FTC, state laws) and case law cover performance and “free from” claims. Other regions overlay their own guidance, but the themes are similar: claims must be supported by competent, reliable evidence, proportionate to the strength and precision of the promise. This means your claims substantiation system must be robust enough to stand in front of a regulator, judge or retailer and survive detailed questioning—not just internal marketing enthusiasm.

3) Types of Cosmetic Claims & Risk Profiles

Not all claims are equal. A basic descriptive claim (“pink cream with floral scent”) carries low risk; a functional or borderline claim (“treats acne”, “heals eczema”) can cross into drug or medical territory and trigger a very different regulatory regime. Typical categories include:

• Descriptive claims – colour, texture, fragrance, packaging features.
• Functional performance – moisturisation, shine, volume, long‑wear, SPF, anti‑wrinkle, anti‑frizz.
• Comparative claims – “2× smoother than bare skin”, “better than leading brand”.
• “Free from” or “clean” claims – “paraben‑free”, “fragrance‑free”, “clean beauty”, “non‑toxic”.
• Sensory & emotional – “skin feels comforted”, “instant freshness”.
• Ethical & sustainability – “vegan”, “cruelty‑free”, “recyclable”, “carbon‑neutral”.

Each category demands different evidence and carries different regulatory and reputational risk. Functional and borderline claims need the most rigorous substantiation; “free from” and ethical claims come second because of greenwashing and fear‑selling concerns; descriptive and purely subjective claims are lower risk but still must not be misleading. A mature system explicitly risk‑ranks claims and calibrates the depth of evidence accordingly.

4) Evidence Types & Hierarchy

Cosmetic claims are supported by a mix of study types and scientific rationales. A typical evidence hierarchy includes:

• In vivo instrumental/clinical tests – dermatologist‑controlled or CRO‑run studies with objective endpoints (corneometry, profilometry, TEWL, SPF/UVA tests).
• Consumer‑perception tests – home‑use studies with questionnaires capturing perceived benefits (e.g. “X% agreed skin looked smoother”).
• In vitro and ex vivo work – cell or tissue models, mechanistic tests supporting plausibility.
• Literature & prior use – published data on actives or formulations, history of safe and effective use.
• Bridging & extrapolation – applying existing data to similar formulas with justified reasoning.

Stronger, more specific claims require higher rungs on this hierarchy. “Helps to reduce the appearance of fine lines” might be supported by a single, well‑designed clinical plus perception data; “clinically proven to reduce wrinkles by 40 % in 2 weeks” demands a completely different level of statistical design and scrutiny. Claims substantiation should document not only the data, but the logic of how those data support the exact wording used on pack and online.

5) Linking Claims to CPSR, PIF, Formula & Label Copy

Cosmetic claims cannot be managed in a vacuum. They must align with formula, safety assessment and artwork. In the PIF, claims are usually tied to a dedicated “claims substantiation” section containing study reports, rationales and mapping tables from claim text to evidence. The CPSR should consider the intended claims, particularly where they imply specific benefits for sensitive populations, long‑term use or areas like around the eyes.

On the operations side, claims must match the formula actually being manufactured. If cost‑reduction reformulations remove or change actives, preservatives or fragrance components central to a claim, the substantiation must be reassessed and label copy updated. This connection is best managed through integrated PLM/formulation tools, artwork systems and a controlled change‑control process, not manual email chains between R&D, Regulatory and Marketing. If those lines are not connected, you will eventually have products on shelf making claims that no longer match the contents or safety documentation.

6) Quantitative Performance Claims & Study Design

Quantitative claims (“up to 48‑hour hydration”, “reduces dandruff by 60 %”) are powerful and heavily scrutinised. Substantiation must cover:

• Study design – sample size, control group, randomisation, blinding, inclusion/exclusion criteria.
• Endpoints – clearly defined, clinically or consumer‑relevant, measured with validated methods.
• Statistics – appropriate tests, p‑values, confidence intervals; no cherry‑picking favourable subgroups.
• Population – reflective of the claimed audience (age, skin type, hair type, geography).
• Use conditions – application frequency, co‑use with other products, wash‑off vs leave‑on, product amount.

Regulators and competitors will probe whether your catchy headline accurately reflects the study. “Up to” claims cannot rely on a single outlier result. Average benefit claims must be based on the full evaluable population, not just responders. If the design would look weak in front of a statistically literate regulator or court, then the claim is too aggressive for the data you have. Rewriting the claim to match the evidence is cheaper than defending over‑reach later.

7) Consumer-Perception Claims & Subjective Benefits

Consumer‑perception claims (“9 out of 10 women agreed…”) are common and legitimate, but they must not be faked or exaggerated. Robust use‑tests require:

• Clear, non‑leading questionnaire wording tied directly to claim language.
• A sample that reasonably represents the target consumer group.
• Controlled instructions for use and test duration.
• Transparent reporting of response rates and denominators (e.g. 90 % of 100 participants, not 90 % of those who completed a subset of questions).

Subjective benefits (“skin feels soft”, “hair feels lighter”) can be supported by perception data, but should still reflect a majority experience, not a handful of enthusiastic responders. Perception evidence should be archived as rigorously as clinical data—signed protocols, raw data, analysis, conclusions—under the same DMS and data‑integrity expectations, not lost in marketing agency archives or outdated PowerPoint files.

8) “Free From”, “Clean”, “Hypoallergenic” & Risky Claims

“Free from”, “clean”, “non‑toxic”, “chemical‑free”, “hypoallergenic” and similar claims are regulatory hot buttons. They can imply that compliant ingredients are unsafe or that a product is safer than competitors without solid evidence. Substantiation here is less about demonstrating a positive effect and more about ensuring the claim is not misleading, denigrating or fear‑driven.

For “free from” claims, you must confirm the absence of the named ingredient across raw materials, cross‑contamination risk and supply chain changes—and ensure that any alternative ingredients do not create the same perceived risk. For “hypoallergenic” or “suitable for sensitive skin”, substantiation often involves targeted clinical testing on sensitive panels plus a robust allergen‑minimisation strategy. If your formula contains known sensitising fragrance allergens or high‑risk preservatives, “hypoallergenic” is a very hard sell to regulators, no matter how creative the marketing narrative. Claims substantiation must call this out and force uncomfortable conversations early, not after launch.

9) Digital, Influencer & AI-Generated Claims

Claims do not live only on packs and TV ads anymore. Websites, e‑commerce pages, social media, influencers, chatbots and AI‑generated product blurbs all become part of the claims landscape. Regulators increasingly treat brand‑linked digital content as advertising, even when posted by third parties acting under your direction or incentives.

Claims substantiation frameworks must therefore extend to digital marketing teams, agencies and content tools. “Hero claims” should be centrally defined and locked; any new wording must go through the same review as pack copy. Influencer briefs should restrict them to pre‑approved language and avoid unsubstantiated medical‑like promises. If AI tools are used to generate descriptions, they must be constrained to a library of substantiated claims and banned from making novel promises. Pretending that only the pack is regulated territory is wishful thinking—and regulators know it.

10) Global Portfolios, Local Rules & Variant Management

Global brands face the challenge of one formula, many markets, many rules. A claim that is acceptable in one region may be borderline or forbidden in another. Claims substantiation must therefore be mapped to a claim matrix: which claims are allowed, altered or prohibited per region, language and distribution channel, with clear links back to evidence and local regulatory interpretations.

Variant management complicates this further. Shade, fragrance or format variants may share a common evidence package—or they may not. For example, a long‑wear claim generated on a matte foundation may not be valid for a dewy sister formula with different film formers. Your substantiation system should make clear which variants are covered by which data and which require additional bridging studies or disclaimers. “We assumed it applied” is not acceptable justification when local authorities or plaintiffs’ lawyers come knocking.

11) Data Integrity, DMS, Version Control & Change Management

Claims substantiation lives or dies on documentation. Study reports, protocols, raw data, analysis scripts, literature summaries and rationales must be controlled within a validated or at least tightly governed document‑management system (DMS). Key requirements include version control, access control, audit trails and robust indexing so evidence can be retrieved quickly in audits, inspections or legal discovery.

Change management is critical. Reformulations, new packaging, repositioning, target‑consumer shifts or regulatory updates can all erode the validity of existing evidence. A mature Management of Change (MoC) process automatically asks: “Which claims does this change affect, and what does it do to our substantiation?” If the answer is “we’ll check later”, you are essentially running with expired evidence—fine until someone challenges it, at which point you have no credible defence.

12) Complaints, Adverse Events & Post-Market Evidence Review

Claims substantiation does not end at launch; the market continues to generate evidence for or against your promises. Complaint trends, adverse‑event reports, call‑centre feedback, online reviews and social listening can all signal that a claim is overstated, misunderstood or targeting the wrong population. For example, repeated complaints that a “non‑comedogenic” product triggers breakouts in real‑world use may indicate that study design, recruitment criteria or claim wording need to be revisited.

Post‑market surveillance should feed back into claims governance through structured reviews. Significant safety signals already drive CPSR and PIF updates; claims signals should trigger reassessment of wording, target population or usage instructions, and in some cases new studies. Integrating complaints systems with claims and regulatory functions—not just customer service—is the difference between learning early and reading about your failures in enforcement notices or newspaper articles.

13) External Partners: CROs, Labs, Experts & Retailer Demands

Many cosmetic brands outsource testing and claims work to CROs, dermatology networks, academic partners or specialised labs. This does not transfer accountability. The brand (or Responsible Person in the EU/UK) still owns the decision to rely on a dataset and to translate it into consumer‑facing language. Partner selection, oversight and quality agreements should address protocol design, data integrity, statistics, sample storage, report structure and timelines for providing raw data if challenged.

Retailers increasingly have their own claim standards and may demand access to evidence or summaries for internal review. Failing to meet retailer expectations can lead to delisting or forced re‑labelling even when regulators have not yet intervened. A robust claims substantiation system anticipates these demands and packages evidence in a way that can be shared appropriately—protecting IP where needed but providing enough transparency to maintain trust with key customers and regulators.

14) Governance, Training, KPIs & Continuous Improvement

Claims substantiation should be governed like any other critical quality system, not treated as a marketing formality. That means defined roles (claim owners, reviewers, approvers), cross‑functional review boards, SOPs, training and periodic audits. KPIs might include percentage of SKUs with current substantiation summaries, number of claims changed due to weak evidence, time to provide evidence packs in audits, and number of regulator or retailer challenges citing claims.

Continuous improvement focuses on recurring pain: claims that are frequently rejected late in the artwork process; studies that consistently fail to deliver the promised headline; markets that generate disproportionate complaints or regulatory questions. Systematically addressing these patterns—better early‑phase study design, clearer claim guidelines for marketing, harmonised claim libraries across brands or regions—reduces both risk and friction. The end game is a portfolio where every major claim can be backed in minutes with a clear, coherent evidence story, not a multi‑week document hunt and retrospective justification exercise.

15) FAQ

Q1. How much evidence is “enough” to support a cosmetic claim?
It depends on the strength and specificity of the claim. Vague, low‑risk benefits may be supported by smaller perception tests and literature. Strong, quantified or borderline claims require well‑designed clinical or instrumental studies plus consistent supporting data. The standard is “competent and reliable scientific evidence”, not “we once saw it work on a few people”.

Q2. Do we need new studies every time the formula changes?
Not always, but every material change must be assessed. Minor adjustments may be bridged with rationale and limited testing if they do not affect the claim‑relevant mechanism. Removing or altering key actives, preservatives or delivery systems usually requires at least bridging studies and sometimes a full new substantiation package. Assuming that claims automatically carry over is risky and often wrong.

Q3. Are small in‑house consumer tests enough?
For low‑risk, qualitative claims, well‑run in‑house perception tests can contribute to the evidence base. For stronger performance claims or anything that might be scrutinised by regulators or competitors, relying solely on small, uncontrolled in‑house tests is weak. At minimum, you need clear protocols, representative panels and honest reporting; for critical claims, external CRO‑run studies are usually safer.

Q4. How should we handle legacy claims with weak or missing evidence?
Treat them as debt. Conduct a portfolio review, risk‑rank claims and either (a) regenerate evidence, (b) soften or remove claims, or (c) retire products where the gap is too large. Continuing to ship products with claims you know are weak is a conscious risk decision—one that regulators and plaintiffs’ lawyers may interpret harshly if issues arise.

Q5. What is the first practical step to improve claims substantiation?
Build a central claims register: for each SKU, list key claims, exact wording, markets where used and links to evidence. Identify gaps and high‑risk claims, then tackle them systematically—starting with hero products and high‑exposure campaigns. Only after this baseline is in place does it make sense to invest in more complex tooling or analytics.

Related Reading
• Safety & Regulatory: CPSR | PIF | ISO 22716 | Allergen Control
• Systems & Governance: QMS | DMS | Change Control | Data Integrity
• Operations & Lifecycle: Deviation / NCR | CAPA | Recall Readiness | Label & Claims Control