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Part 1 · Discovery kit pricing

Betting on your product with discovery kit pricing

What 52 kits across 34 prestige fragrance brands actually price at, and what the number reveals

Loewe's discovery kit costs $4.67 per milliliter. Its 50ml hero bottle costs $2.52. The thing built to recruit you into the brand runs 1.85× the price per drop of the thing it's recruiting you toward.

Loewe isn't unusual. 4 of the 5 biggest names in prestige fragrance price their discovery kit above the per-ml of their own hero bottle.

01 · The opening bet

The trial is usually the more expensive way to buy the fragrance

Brand50ml $/mlKit $/mlKit ÷ hero
Byredo$3.94$4.541.15×
Creed$5.10$6.381.25×
Diptyque$3.16*$4.901.55×
Loewe$2.52$4.671.85×
Le Labo$4.80$4.20–4.670.88–0.97×

* Diptyque's smallest bottle is 75ml at $2.78/ml. The 50ml per-ml is interpolated from the brand's full-line curve.

The 50ml is the conversion target. It's the bottle the brand wants a trial customer to buy next, and in 4 of 5 cases the trial is the more expensive way to buy the same fragrance.

Le Labo prices the other way

All 3 of its discovery formats sit below the hero per-ml: a 5×1.5ml at $35, a 17×1.5ml at $107, a 6×5ml at $135. Every one. That's policy.

A kit priced above your hero makes money whether or not the customer comes back. A kit priced below it only makes money if they do. Le Labo has given up the margin on the way in and is counting on the fragrance to earn the second purchase.

That's a wager, and it's a cheaper one for an Estée Lauder-backed brand than for a founder with 9 months of runway.

Loewe · 6×1.5ml1.85×Diptyque · 3×7.5ml1.55×Creed · 3×10ml1.25×Byredo · 6×2ml1.15×Le Labo · 5×1.5ml0.97×Le Labo · 6×5ml0.94×Le Labo · 17×1.5ml0.88×0.50×0.80×1.00×1.10×1.50×2.00×
Fig 01 · Kit per-ml as a multiple of each brand's hero bottle per-ml. Le Labo's three formats all sit below the hero line.

02 · The wider cohort

52 kits across 34 brands fall into 3 groups

The full set spans indie, niche, clean and mass-prestige. Plot each kit as a multiple of its own brand's hero per-ml and 3 groups fall out.

Above hero

above 1.10×

The kit defends its unit margin. Most prestige kits are here, including all 4 incumbents above.

At hero

0.80× to 1.10×

The kit prices at or near the product it's recruiting toward. Le Labo's whole range sits in this band.

Below hero

below 0.80×

Rare, and it carries a different risk. Price too far under the curve in prestige and the trial reads as cheap, which doesn't help the hero bottle.

34 brands isn't a coincidence. Nearly every one of them describes the kit as the way in, the introduction, the start of the relationship. So the category prices its recruiting tier like a product and describes it like a funnel.

COHORT DISTRIBUTION · LE LABO HIGHLIGHTEDkit $/ml as a multiplier of the brand's 50ml heroABOVE HEROabove 1.10×AT HERO0.80× – 1.10×BELOW HERObelow 0.80×0.500.751.001.251.501.752.002.252.50DISCOVERY≤3ml vialsTRAVEL>3ml vialsle labole labobyredobyredoloewele labobyredodiptyquecreeddiptyque
Fig 02 · Kit price multiple against each brand's hero per-ml, split by format. Le Labo is highlighted across the full 52-kit cohort.

03 · What the price reveals

You can read a brand's private opinion of its own retention off the kit price

A kit priced for margin pays for itself on the transaction. If conditional conversion turns out to be 8% rather than the 25% in the deck, the kit line still looks healthy on the dashboard and nobody has a reason to check.

Any brand can put conviction on an About page. Very few can hand out $49 kits at 51% margin and survive it, because a brand whose product doesn't retain bleeds through the acquisition tier with nothing behind it. That's what makes the low price informative. It's expensive to be wrong about, so it can't be faked for long.

Which is why the trap is comfortable. For a brand with a mediocre product, high kit margin is load-bearing. It's the mechanism keeping the acquisition tier healthy on paper while the cohort quietly fails.

2 ways to end up at 1.85×

The first is a belief. The brand has looked at conditional conversion, doesn't like the number, and prices the kit to make its money on the way in. That's rational, and it's a decision to stop growing through product.

The second is that nobody asked. The kit sits under whoever owns kit margin, gets priced by the same rules as every other SKU, and no one has computed what a trial customer is worth. This is most of the category, and it's the good news: most brands in the margin trap have never tested whether they'd survive outside it.

The bet worth making

If your product is good, and you have the cohort data to know it rather than assume it, cheap discovery is the highest-return position on your board. You're buying customers at a price your competitors have decided they can't afford, and what stops them is their product.

A brand with 9 months of runway can't take the bet even if it would win, since compressing kit margin trades cash now for cash in 18 months.

So measure conditional conversion first. What share of kit buyers purchase a hero bottle within 6 months? If that number is strong, kit price is the cheapest way to press an advantage you already have. If it's weak, repricing fixes nothing and the product is the problem you were avoiding.

Part 2 works out the volume lift a price cut has to deliver before it's worth making.

Part 2 · The elasticity hurdle

Before you cut the kit price, work out what volume it has to buy

Cutting a discovery kit's price only works above a specific volume multiple, and it's easy to calculate:

(current kit gross profit + expected hero contribution per trial) ÷ (new kit gross profit + expected hero contribution per trial)

That's the volume lift the lower price needs to break even. Run it with your own numbers before you run anything else. Below the hurdle, a price cut is a margin giveaway with a strategy memo attached.

Everything below is one illustrative set of inputs to show the shape. The numbers are made up. The formula isn't.

Worked example

A $192 hero bottle, $42 of COGS and fulfillment, $150 of contribution per hero purchase. 25% of trial customers convert, and each converted customer buys 2 hero bottles. That's $300 of undiscounted LTV per converted customer, realized over 18 months.

Discount it, because month-18 money isn't month-1 money. At 10% annually, $300 becomes about $278. At 25% conversion, expected discounted hero contribution per trial customer is roughly $70.

Now the hurdle. A $94 kit with $24 COGS produces $70 of kit gross profit. Add the $70 of hero contribution: $140 per trial customer. A $49 kit produces $25 of kit gross profit. Add the same $70: $95.

$140 ÷ $95 = 1.48×.

If the cheaper kit doesn't move at least 1.48 times the volume, it loses. This example assumes 1.75×, which is the bet the whole case rests on, and most brands make that bet without stating it.

04 · Clearing the hurdle

What clearing the hurdle looks like

$94 kit$49 kit
Kit gross profit$70$25
Volume multiplier1.00×1.75×
Monthly trial volume100175
Monthly paid spend$5,000$5,000
Paid CAC per trial$50$29
Monthly kit gross profit$7,000$4,375
Cumulative discounted contribution, month 12~$48k~$38k
Month 24~$139k~$154k
Month 36~$229k~$272k

Month 1 goes to the expensive kit: $7,000 of gross profit against $5,000 of media is +$2,000, against −$625 for the cheaper one. The lines cross around month 19. By month 36 the cheaper kit has compounded roughly $43k more and sits on a larger base still recruiting at 1.75× the pace.

19 months is a long time to be behind. If your board reviews acquisition quarterly, that's 6 consecutive reviews where the decision looks wrong.

DISCOUNTED CUMULATIVE REALIZED CONTRIBUTION · EQUAL PAID SPENDAssumes 1.75× kit volume at the lower price · 25% trial-to-hero conversion · $300 LTV realized over 18 months · 10% annual discount ratediscounted cumulative realized contribution ($ thousands)Crossover · around month 19$94 kit · $70 gross profit · 100 kits/mo$49 kit · $25 gross profit · 175 kits/mo~$272k~$229k05101520253035month050100150200250300Discounted at 10%/yr · LTV realized over 18 months
Fig 03 · Discounted cumulative realized contribution under equal paid spend. The lower-priced kit crosses over around month 19 and leads by roughly $43k at month 36.

05 · The payback objection

Reinvestment buys more of the same curve. Repricing moves it.

The standard reply is that this destroys payback period. Take the $2,000 from month 1, put it back into media, push the channels that converted.

That works only if average CAC and marginal CAC are the same number. They aren't.

The first $5,000 reaches the warmest cohort: people already close enough to the brand or the scent profile to buy a kit. That's 100 trial customers at $50 average. The $2,000 of profit gets spent at the margin, deeper into the same audiences, colder intent, more auction pressure, more overlap. At $65 to $75 marginal CAC it buys 27 to 31 more customers rather than 40.

Repricing doesn't need another pocket of cheap media. The same $5,000 buys 175 trial customers instead of 100. Reinvesting profit buys more of the same demand curve. Repricing moves it.

LTV/CAC goes from 1.39× to 2.44×, and the spread comes from CAC efficiency rather than the discount rate.

06 · What to build

3 things to build first

  1. Conditional conversion. What share of kit buyers purchase a hero bottle within 6 months? Without it you can't compute the hurdle, which means you're repricing on instinct.
  2. A 24-month cohort model for the discovery cohort specifically. Contribution at 12, 18 and 24 months, discounted. The SKU P&L is already on a dashboard. The cohort is buried, and the buried number is the one the decision turns on.
  3. A wholesale scenario. Wholesale compresses kit margin further, which raises the hurdle. Model whether the economics survive the haircut before agreeing to retail distribution of discovery formats.

The hurdle is the whole discipline. It tells you when to cut the price and when to leave it alone.

See also

Case study
Prestige-natural skincare · pricing rebalance

Worked example of these methods applied to a client engagement — peer cost modeling, demand regression, and per-SKU rebalance.