JD Rico What wellness brands need to learn before the next decision becomes expensive to change
Wellness does not stand still while a product is being developed.
Consumer language shifts.
Ingredients acquire new associations.
Scientific evidence changes what looks credible.
Regulators alter the boundaries of what can be claimed.
Competitors reset price expectations.
Consumers find uses for products that their makers did not anticipate.
Product development has a different rhythm.
A formulation is selected.
Dosage is fixed.
Claims go through review.
Packaging is approved.
Manufacturing is booked.
Inventory is produced.
Distribution commitments are made.
With each commitment, changing direction becomes more expensive.
That creates a recurring commercialization problem: the market can keep teaching you after important parts of the product have become difficult to change.
Companies have been trying to bring consumer understanding into product development for decades. There is no single research method that solves the problem.
A review of consumer research in early new-product development examined ten common methods and found that their usefulness depends on what a team is trying to learn, the task involved and the kind of innovation being developed.
The practical issue is timing. Before a consequential commitment, which remaining unknowns could still change the decision?
Learning while the product is still movable
Dr. Richie Barclay, founder of MUTO, described a failure that will be familiar to people who have worked across R&D and commercialization:
“R&D locks a formulation before commercial has validated that consumers actually want it framed that way.”
He has seen teams spend eighteen months refining a delivery format or dosage before testing exposes a different problem: consumers do not respond to the story, or the price assumed during development does not match what the category will support.
Those discoveries are not equally expensive at every stage.
A weak proposition can be rewritten cheaply while it is still a concept. Once the proposition is tied to dosage, pack size, cost of goods, required testing or manufacturing commitments, the same discovery may reach much further into the business.
Brenda Buechler, whose commercial work spans pharmaceuticals, biotech, aesthetics, beauty and wellness, described the same tension from another direction. Product teams can optimize efficacy, stability or a novel mechanism before anyone has tested what a consumer needs to believe in order to buy or use the product.
This does not make technical development subordinate to marketing. It means a technical win can carry commercial assumptions that deserve examination before they become physical.
The earlier question is rarely “Do we have enough research?”
It is more useful to ask what the next commitment makes harder to change.
Some answers only appear after launch
Trying to resolve every uncertainty before launch creates a different mistake.
Barclay puts considerable weight on what happens once a product reaches real customers:
“Once you’re live, the wider consumer market will tell you far more than any pre-launch research could.”
Taken literally, that would be too broad. Plenty of expensive mistakes can be found before launch. His own case is valuable because it shows what post-launch evidence can reveal that pre-launch work may not.
Barclay reports that it took MUTO roughly twelve months to understand what consumers were really responding to. When the company leaned into that learning, he says its unit economics improved.
That is not evidence that companies should simply launch and figure things out later. It shows that real purchasing, use, language, and economics expose parts of a market that simulations cannot fully reproduce.
Dr. Harsha Moole reached a similar conclusion through retention. Asked what information he would want future teams to have, he pointed to:
“the actual drop-off data from people who tried the product.”
Pre-launch and post-launch evidence serve different purposes.
Before launch, a company can test comprehension, price assumptions, claims, category language, sensory response and other avoidable risks. After launch, it can observe who buys, who stays, who leaves, how people actually use the product, what support they need, and what the economics look like outside a test environment.
A team may have enough evidence to proceed while deliberately leaving some questions for the market. Another may face an assumption that has to be resolved before manufacturing capital is committed. A third may be able to isolate the uncertain part and test it without delaying everything else.
There are also decisions where waiting is more expensive than being wrong.
The useful distinction is not research versus action. It is the exposure created by the particular decision in front of the company.
Enough for what?
“Enough information” means very little without a commitment attached.
A company may have enough confidence to produce 500 units and nowhere near enough to print 100,000 packages.
It may know enough to test a landing page without knowing enough to sign a national retail agreement.
A formulation decision that triggers new stability work if changed later deserves a different evidentiary bar from a message that can be revised tomorrow.
This is where product reversibility becomes useful.
Some decisions preserve room to move. Others consume it.
When a decision remains inexpensive to reverse, imperfect information may be entirely acceptable. The stakes change when an assumption is about to be built into formulation, packaging, inventory, economics, claims architecture or a long contractual commitment.
The same uncertainty can therefore be trivial in one context and consequential in another.
Reversibility also prevents research from becoming an excuse for indefinite delay. If the risky assumption can be tested after a small commitment rather than before any commitment, the company may be better served by doing exactly that.
What matters is knowing what the test can and cannot teach.
A language test can expose confusion around a proposition but cannot establish repeat purchase.
A small production run can reveal usage problems without reproducing full-scale economics.
A DTC launch may teach a great deal about early adopters and very little about mass retail.
A concept test can perform beautifully while the finished product fails in a different context.
Smaller commitments buy learning only when the team remains clear about the unanswered questions.
Consumer meaning can disappear during development
A technically coherent product can reach market without a coherent place in the customer’s life.
What does it replace? Why would someone switch? What are people doing now instead? Which part of the problem matters enough for them to change behavior?
Buechler described working on a product for which consumers had no established category language:
“There was no existing consumer language for it because there was no existing category… what does this replace, and why would I switch?”
That question changes the work.
In an established category, a company can study familiar competitors, attributes, and buying criteria. A product that asks consumers to form a new category may need research to establish a reference point before it can differentiate itself.
Thérèse Kialukofi sees another source of drift inside the organization:
“Each function may be working on the same product, but they are applying different expertise and optimizing for different objectives, often asynchronously.”
That can happen without anybody doing poor work.
R&D may optimize performance. Regulatory may reduce claims risk. Finance may protect margin. Marketing may look for a proposition people understand. Sales may be reacting to channel requirements.
The product moves through all of them.
Kialukofi argues that a strong consumer insight can provide continuity, but she also offers an important limit to the usual prescription for more research:
“For established brands, more information is not necessarily the answer. Better interpretation and application of the information already available can be more valuable.”
This exposes two different information failures.
Sometimes the knowledge genuinely does not exist.
Sometimes it exists in a presentation, research repository or earlier stage of development and stops influencing subsequent decisions.
Barclay described that second pattern: insight work happens early, gets filed away and never resurfaces strongly enough to challenge choices made later.
The commercial risk is the same even though the remedy is different. Commissioning another study does little if the organization already possesses the relevant evidence and cannot carry it into the decision.
What can you actually say?
Wellness adds another constraint.
What a product does, what the evidence supports, what regulations allow a company to say, and what a consumer understands are related, but they are not interchangeable.
Sarah Otto, nutritionist and co-founder of Goodness Lover, has described formulation lock as a point where commercial and regulatory input can arrive too late. In her account, the strongest scientific story can encounter claims limitations that were never considered during product formulation. The eventual translation into consumer language can then flatten the very nuance that was supposed to differentiate the product.
That possibility belongs upstream.
In the United States, the FDA distinguishes among categories of claims used for foods and dietary supplements, while the FTC’s guidance for health-related advertising requires marketers to consider the messages consumers will take from a claim and whether appropriate scientific support exists.
The precise requirements depend on the product, the claim and the jurisdiction. The product-development implication is broader: a commercially valuable attribute can lose much of its value if the evidence cannot support a useful claim, or if the supportable claim cannot be communicated in a way consumers understand.
The reverse can happen too. An appealing commercial proposition can outrun the evidence.
That tension is part of the trust problem explored in Evidence vs. Hype in Wellness.
Barclay’s standard is concise:
“Trust has to be built on proof rather than positioning.”
For science-led wellness products, evidence is more than material handed to legal before a campaign goes live. It can determine which forms of differentiation are commercially usable in the first place.
That makes claimability an upstream product variable.
The product people experience is bigger than the formula
Moole’s experience at FindMyDirectDoctor shows what can happen when a technically sound offering is defined too narrowly.
“We built a clinically sound offering, but patients quit when the refills, coaching and follow-up were hard to navigate.”
The response was not another acquisition campaign.
“We had to rebuild the whole thing around retention, not just the product.”
The clinical proposition had not suddenly become worthless. The surrounding experience was preventing people from continuing long enough to realize its value.
As healthcare becomes more consumer-driven, access, follow-up, navigation, continuity, and routine can shape the outcome as much as the initial transaction.
Physical wellness products carry their own versions of this problem.
Buechler points out that stability and efficacy testing do not answer sensory questions:
“‘Cosmetically elegant’ and ‘how does this feel and smell on my face’ are consumer questions, not lab questions, and they don’t show up in a stability report.”
Carmine Del Sordi, founder of Pure & Easy Tea, extends the same logic into distribution. A product that is coherent in development still has to survive a change of context:
“Will the product still make sense when it moves from a development room to an Amazon thumbnail, retail shelf or hospitality setting?”
Formula, evidence, packaging, support, sensory experience, channel, and continued use are not identical parts of a product. They can, however, determine whether the customer receives the value the product was designed to create.
A commercialization process that treats those conditions as downstream presentation issues may discover them only after the expensive parts are fixed.
The economics can harden before the market answers
Price often appears late in launch planning even though its constraints start much earlier.
Ingredient choice affects cost. Dosage affects consumption rate. Packaging changes margin and logistics. Claims influence defensible differentiation. Channel brings another layer of economics.
Barclay argues that:
“Pricing and unit economics data needs to sit alongside formulation decisions from day one.”
That does not require knowing the final market price before development begins.
It requires recognizing when a product decision already contains a pricing assumption.
If the formulation only works economically at a price consumers will not pay, the pricing problem is partly a formulation problem.
If the dosage required for efficacy results in an unacceptable monthly cost, that economic exposure exists whether or not anyone has entered a retail price into the launch plan.
The market will eventually answer.
The question is how much the company has committed before it hears the answer.
Signals move at different speeds
Timing matters for another reason: information does not age uniformly.
The underlying physiological need for better sleep can remain stable while consumer language around sleep changes quickly.
An ingredient can acquire cultural momentum in weeks. Competitors can reset a category’s reference price. New evidence can alter the credibility of a mechanism. Regulatory action can suddenly change what had been a stable claims environment.
Terms such as biological age, cortisol, protein or metabolic health can circulate far beyond their technical definitions and pick up new consumer meanings along the way.
An insight can therefore be excellent when it is produced and stale when somebody finally uses it.
Signals move. Insights age.
That does not imply constant research into everything.
Consumer language may deserve frequent observation because it can move quickly.
A biological mechanism may remain useful for far longer.
Competitor pricing can matter throughout development and launch.
A regulatory position may stay unchanged for years and then move abruptly.
Different signals have different velocities. A company that treats all evidence as equally durable will over-research some questions and rely too long on old answers to others.
The practical task is deciding which signals attached to the next commitment are capable of moving before that commitment reaches market.
Reversibility buys room to learn
There is no perfect sequence that eliminates uncertainty from product development.
A company can instead become more deliberate about where it consumes flexibility.
If an assumption is cheap to reverse, the company has room to act with less information.
If the assumption can be isolated, a test can reduce exposure without freezing the rest of the product.
If the answer only becomes visible after launch, the product or operating model can sometimes be designed to accommodate what will be learned.
And when a decision is expensive to reverse, the company has a reason to examine the assumptions underlying it more carefully.
That may lead to proceeding, testing, waiting, investigating, reducing the initial commitment or accepting the uncertainty because delay would cost more.
The scenario determines the sensible response.
Four questions are especially useful before a major commitment:
What are we making harder to change?
Which assumptions become expensive if they are wrong?
What could move between now and market strongly enough to alter this decision?
Which signal would give us enough warning to respond?
They do not promise certainty. They make the remaining uncertainty easier to locate.
The cost of late learning
Companies already measure product-development costs, launch revenue, margin, time-to-market and retention.
The cost of learning late is less visible because it appears in different places.
It is in a reformulation invoice.
It is in packaging that has to be replaced.
It is in inventory carrying a proposition customers do not understand.
It is in margin lost because the price assumed during development never held.
It is in a delayed launch after the claims architecture has to be rebuilt.
It is in customers who disappear before the company identifies the experience problem.
It is in differentiation that becomes commercially unusable because the evidence cannot carry the intended claim.
Those costs are different manifestations of the same event: important information arrived after the decision it could have influenced, making it expensive to reverse.
That is the cost of late learning.
There is little reason to expect a useful industry average. Formulation economics, production volumes, regulatory exposure, channel commitments, and product reversibility vary too much.
Companies can measure their own version.
When an expensive correction occurs, ask when the decisive information became available, when it could realistically have been known, whether it would have changed the earlier decision, and what obtaining it sooner would have cost.
A second measure belongs beside it: how long does the organization take to turn an important unknown into evidence sufficient to influence a decision?
One captures the penalty for finding out late.
The other captures how quickly the business can learn while it still has room to respond.
Markets move. Products lock.
The companies that can see where flexibility is disappearing—and get the right information there before it does—have more room to learn without paying for the same lesson twice.
FAQ
Why do wellness product decisions become harder to change during development?
Commitments accumulate. Formulation, dosage, stability work, claims review, packaging, manufacturing, inventory and distribution can all create switching costs. An assumption that is cheap to revisit during concept development may be expensive once it has been built into the physical product or its economics.
Does this mean wellness brands should do more research before launch?
Not automatically. Different decisions require different evidence, and some questions only become answerable through real purchasing, use and retention. The relevant issue is whether an unresolved assumption could materially affect the commitment being made now.
What is product reversibility?
Product reversibility is the degree to which a decision can be changed after it is made without excessive cost, delay or disruption. Messaging may be relatively easy to revise. Formulation, manufacturing runs and large packaging orders are usually less reversible.
What does “Signals move. Insights age.” mean?
Different kinds of market knowledge have different shelf lives. Consumer language and competitive pricing can move quickly, while biological mechanisms or other evidence may remain useful for much longer. An insight can therefore have been accurate when produced and still be outdated for a later decision.
What is the cost of late learning?
The cost of late learning is the economic consequence of discovering important information after the decision it could have influenced has become expensive to change. It can appear as reformulation, packaging replacement, excess inventory, launch delay, margin loss, churn or lost differentiation.
Why should claims be considered during wellness product development?
Because scientific evidence, permissible claims and consumer understanding can diverge. A formulation may contain genuine differentiation that becomes difficult to communicate credibly, while an attractive commercial claim may exceed what the evidence supports. Earlier attention to claimability can influence product choices before they become difficult to reverse.
Is post-launch evidence more useful than pre-launch research?
They serve different purposes. Pre-launch research can expose assumptions before making expensive commitments. Post-launch evidence reveals actual purchasing, use, retention, customer language, and economics that may be difficult or impossible to predict in advance.
What should a company examine before committing to an expensive product?
Start with what the decision will make harder to change. Then identify the assumptions that would matter most if they were wrong, the signals that could move before launch, and what evidence could realistically be obtained before the commitment must be made.
Some unknowns are cheap. Others get built into the product.
If you’re trying to determine which assumptions need evidence before formulation, claims, packaging, pricing or production become expensive to change, email us.
