How to Choose the Right Study Design for Your Product Claims

In the consumer health and wellness space, study design is often treated as a technical detail – an operational step to be delegated to CROs or academic collaborators. But in reality, it’s one of the most strategic decisions a consumer health ingredient or finished product company can make. A well-chosen study design doesn’t just produce data – it produces evidence that moves markets, earns trust, and supports claims that stand up to scrutiny.

To get there, you have to start with a different question: What do you want to say about your product, and to whom do you want to say it?

Claim Concept First, Design Second

The foundational mistake we see brands make is picking a research provider and study design before defining the claim they want to make. For example:

• A brand wants to say, “Improves energy in 7 days,” but commissions a small RCT powered for mood, not energy.
  
  
• A legacy supplement wants to secure an FDA structure/function claim, but runs an open-label consumer survey with no control group.
  
  
• A new skincare entrant wants to validate impact on “visible signs of aging,” but doesn’t define which signs – or how they’ll be measured.
  
  

Each of these examples illustrates the same issue: no clear path from claim to design to data.

The FDA and FTC require that claims be “truthful, not misleading,” and “substantiated by competent and reliable scientific evidence” [1][2]. But what that means in practice varies depending on the type of claim – and that’s where design matters most.

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Different Claims Require Different Evidence Standards

Let’s look at three common types of claims and what kinds of studies support them:

• For structure/function claims, a confirmatory RCT is usually required. The study must be correctly statistically powered, use validated instruments (i.e., PROMIS, PSQI, DLQI) and other forms of generated health data or biomarker data, and follow a pre-registered protocol.
  
  
• For consumer marketing claims, the FTC accepts well-designed perception studies, as long as they reflect typical consumer experience and aren’t exaggerated [2].
  
  
• For early-stage discovery or investor decks, you may not need a claim at all – just directional data from exploratory or observational work to identify mechanisms, tolerability, or user profiles.
  
  

This distinction isn’t just academic. It influences budget, timeline, participant selection, and the types of endpoints you measure.

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Study Design Must Match Your Product’s Modality and Maturity

Just as important as claim type is product context. A randomized, placebo-controlled, double-blind trial may be the “gold standard” in pharma – but it’s not always the gold standard for wellness.

Examples by Product Type:

• Ingestibles (supplements, functional foods):
  
  Often need RCTs to isolate effect, especially for new dietary ingredients (NDIs) or GRAS-submission work.
  
  
• Topicals (cosmetics, skincare):
  
  Split-face designs and dermatological scales (i.e., GAGS, wrinkle scoring) are common. Subjective ratings matter – perception is part of efficacy.
  
  
  
• Wearables / lifestyle interventions:
  
  Hybrid designs using wearables (i.e., WHOOP, Ōura, Garmin) allow real-world measurement of endpoints like HRV, sleep, and activity [3].
  
  

Crossover studies, open-label designs, N-of-1 trials, and digital observational studies are all valid tools depending on the product and intended claim. The point is to match method to modality.

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Exploratory vs. Confirmatory: Where Are You in the Product Lifecycle?

Not every study needs to be a definitive proof point. Many brands benefit from starting with exploratory work – especially when:

• You’re unsure what outcome to measure
  
  
• You’re launching a new delivery format or multi-ingredient formulation
  
  
• You’re collecting early real-world evidence (RWE) for investor decks
  
  

This type of research can help refine hypotheses, understand dosage effects, identify ideal users, and shape the next stage of development. But you need to be clear: exploratory studies are for learning, not claiming.

By contrast, confirmatory studies require pre-specified endpoints, statistical power calculations, and strict adherence to protocols. These are needed when you’re preparing to:

• Make regulatory claims
  
  
• Submit to Amazon’s health claims team
  
  
• Partner with retailers who require scientific substantiation
  
  
• Differentiate in a competitive category
  
  

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Alethios QuickStart: Designing Studies that Start with the “Why”

This is why we built Alethios’ AI QuickStart feature – not to shortcut science, but to help founders and R&D leaders avoid misalignment from the start.

AI QuickStart takes you through:

1. Business goals (i.e., support a launch, de-risk an NDI, create investor collateral)
   
   
2. Claim types that are credible and achievable
   
   
3. Study designs that fit your modality, audience, and timeline
   
   

We’ve built this to help brands avoid wasting $200K+ on beautiful but unusable data.

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The Bottom Line: Evidence Isn’t Just Data – It’s Direction

Choosing a study design is not just a technical decision. It’s a business strategy. The best designs serve a purpose beyond publication – they create claims that are believable, achievable, and aligned with what matters to your audience.

At Alethios, we believe that good science should serve great ideas. That starts by treating study design as a question of intent – not just method.

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Sources

[1] U.S. Food and Drug Administration (FDA). “Structure/Function Claims.” Link

[2] Federal Trade Commission (FTC). “Dietary Supplements: An Advertising Guide for Industry.” Link

[3] DiMe Society. “Digital Measures That Matter.” Link