Their prices hadn't moved in five years.
The market had.
We closed the gap — while keeping them below market.
A prestige-natural skincare brand engaged Leinemann to evaluate list prices across its hero portfolio. We modeled them against 100+ category peers — the brands stocked at Violet Grey, Goop, and Moda Operandi — looking at where peers price, what goes into the bottle, and how size and category shape the curve. The brand sat 20–45% below peers on most heroes. The rebalance closes about two-thirds of that gap without crossing into the luxury tier.
- Diagnosis: Five years of held prices in a category that moved upmarket. Brand was 20–45% below peers on heroes; small sizes priced lower per-ml than full sizes — an inversion of the category.
- Method: Three independent models — a supply-side peer-pricing regression (1,216 formulations, 9,000+ ingredients, six wholesale catalogs), a demand-side elasticity regression on 875 SKU-weeks of transactions, and a constrained optimizer (margin maximizer × peer ceiling × revenue floor).
- Recommendation: Per-SKU list-price moves from +5% to +40%. Largest moves on the most-mispriced and least-elastic SKUs; smallest moves on price-sensitive acquisition SKUs.
- Outcome: ~+11% portfolio contribution margin lift, brand remains 10–25% below comparable peers, wholesale margin % unchanged, small-size per-ml inversion corrected.
Where they were vs. where the market was
Over five years, the prestige-natural category moved meaningfully upmarket. Tata Harper, Vintner's Daughter, Augustinus Bader, May Lindstrom — every peer the brand competes with raised prices, often more than once. Our client held flat.
We benchmarked the entire category: every peer SKU priced and compared, every formulation costed ingredient by ingredient, every sub-category modeled separately for how cost translates into retail price. The model said the brand's median formulation was priced 25% below where comparable peers sit. The mandate was to narrow that gap from −34% on the most-mispriced SKUs to roughly −10%, while holding the strategic discount on smaller and acquisition-tier sizes.
The brand sits in the lower 20% of prestige-natural brands by price-vs-model. Brands like Sisley-Paris (+153%) and Noble Panacea (+98%) price well above the model's prediction; brands like Embryolisse (−74%) and Alpyn (−69%) sit well below. The rebalance keeps the brand in the accessible half — just less aggressively below.
What's actually in the bottle
"What's in the bottle costs more than what's on the price tag."
Most pricing analysis stops at retail price comparisons. We went further. For every peer SKU, we costed the formulation ingredient by ingredient — over 1,000 formulations, more than 9,000 ingredients, six wholesale supplier catalogs across the US, EU, and Asia. Then we compared formulation cost to retail price, by sub-category.
The result: a model that says, with measurable rigor, what a formulation should cost retail given what's in it. The brand prices by what the formulation costs to make and what the market pays for similar formulations.
Worked example. A reference prestige-natural botanical serum (white) sells for ~$7/ml on a formulation costing roughly $1,100/kg. The brand's comparable Botanical Serum (red) sells for ~$2.30/ml on a formulation costing roughly twice as much per kg. Same shelf, ~2× the formulation cost, ~⅓ the price per milliliter. The rebalance partially narrows that gap; it does not close it.
DTC vs Wholesale
"Small sizes were actually cheaper per milliliter than full sizes. Professional buyers noticed."
The brand sells through two channels with different economics. DTC carries first-time-buyer and subscription discounts. Wholesale to specialty retail and spas operates at 50% off list — the industry standard for prestige skincare. The two channels respond to price differently. DTC customers buy on absolute price points. Professional buyers buy on per-milliliter economics.
On the small sizes, the per-ml math had been telling them something interesting: in some cases the smaller bottle was cheaper per milliliter than the larger one. That wasn't a discount program — it was unintended. Most peers run flat-to-+20% small-size premium (Herbivore +9%, True Botanicals +20%, Vintner's flat across three sizes). The rebalance corrects the inversion: small sizes get a modest per-ml premium over full size, in line with the category norm.
Face-oil peer set on log-log axes. Category trend (dashed) slopes down — bigger bottles get cheaper per ml. The brand's Antioxidant Treatment 30ml priced below its 50ml on a per-ml basis, inverting the category. The rebalance lifts the 30ml above the 50ml line, restoring the small-size premium.
Why these specific recommendations
"Own-price elasticity estimated from 875 SKU-weeks of transaction data, cross-checked against industry priors, backstopped by three independent constraints."
Most pricing decisions get made on intuition and round numbers. Ours came from 2.75 years of weekly sales data, controlled for paid spend (Triple Whale-tracked), seasonality, confirmed GWP weeks, and SKU/month fixed effects. The model produces a per-SKU effective elasticity that scales with price level — a higher-priced SKU is more elastic in absolute-dollar terms than a lower-priced one.
| β₁ log(net price) | −0.34 | noisy; consistent with literature prior of −0.3 to −0.6 |
| β₂ dollar discount / unit | +0.017 | well-identified, t = 4.8 |
| log(total ad spend) | +0.43 | ad-spend control, t = 11.1 |
| is_GWP_week | +1.12 | gift-with-purchase bump, t = 8.5 |
β₁ is noisy on its own — the confidence interval crosses zero. β₂ is rock solid. Because effective elasticity combines both — ε_eff(P) = β₁ − τ·β₂·P — the β₂ contribution dominates at the price points that matter. Recommendations are also backstopped by three binding constraints: a contribution-margin maximizer, a peer-market ceiling, and a revenue floor. The four most aggressive moves are revenue-floor-bound, meaning they would be unchanged for any β₁ in the [−0.30, −0.50] range.
- A structural substitution model between SKUs — own-price response only.
- Cross-elasticity estimates between products.
- Out-of-sample validation on new product launches.
- Identification beyond within-SKU week-to-week price variation.
Per-SKU lift, anonymized
Lift sized to gap-vs-peer-model and per-SKU elasticity. Largest moves on the most-mispriced and least-elastic SKUs; smallest moves on price-sensitive acquisition SKUs.
| SKU (ANONYMIZED) | GAP VS PEER MODEL | LIST-PRICE LIFT |
|---|---|---|
| Hero Facial Oil — 50ml | -34% | +18% |
| Hero Facial Oil — 20ml | -28% | +12% |
| Antioxidant Treatment — 50ml | -30% | +16% |
| Antioxidant Treatment — 30ml | -22% | +11% |
| Botanical Serum — 60ml | -27% | +14% |
| Hyaluronic Gel — 50ml | -34% | +36% |
| Hyaluronic Gel — 30ml | -25% | +40% |
| Hydrating Toner — 50ml | -10% | +8% |
| Brightening Serum — 50ml | -6% | +5% |
Wholesale prices move with list at the existing 50%-off-list rate — retailer margin percentage is unchanged.
The most aggressive move, pressure-tested
The Hyaluronic Gel 50ml was sold at $1.68/ml. The model recommended a price that puts it at $2.28/ml (+36%). The largest list-price move in the set — and the fair question is whether that's too much.
We pressure-tested it against the closest functional peers: water-based hyaluronic-gel serums in the prestige-natural tier with no peptide loading. At $2.28/ml the SKU lands between Pai Instant Kalmer ($2.19/ml) and Joanna Czech Hyalogy P-effect Reliance Gel ($2.36/ml) — same brand tier, adjacent price points. The category median in the peer set is $3.87/ml. The model is not asking for the median; it is asking for the floor of the premium-natural tier.
If you're navigating a similar pricing question — where a category has moved and the catalog hasn't — I'd be glad to talk it through.