Why tiered offers beat flat discounts
A flat discount gives your margin away on every unit, including the first one, which the customer was probably going to buy anyway. A tiered offer is smarter about where the discount lands: the customer only unlocks the saving by adding units, so most of the margin you give up is traded for revenue you would not otherwise have had.
The economics compound in your favour. A bigger basket spreads your fixed per-order costs (shipping, pick-and-pack, payment fees) across more units. Sell one $60 unit and an $8 carrier fee eats 13% of the order. Sell four units in one box and the same $8 is 4% of it. That is why a "buy 4, save 20%" order can carry a lower product margin than full price and still make far more profit per order.
Every tier is still a bet on customer behaviour. If a tier's discount is deeper than the extra conversion and basket size it buys, it loses money like any other discount. The calculator makes that comparison explicit.
How the calculator works
The tool builds a full order P&L for your full-price baseline (one unit, no discount) and for each tier, then ranks everything on profit per 1,000 sessions: gross profit per order multiplied by the conversion rate that tier achieves, normalised per thousand visitors.
1,000 × CVR(tier) × (order revenue − COGS − carrier cost)
- Order revenue: units × discounted price, plus the shipping fee on orders below your free-shipping threshold.
- Conversion: your baseline rate adjusted by each tier's uplift. Uplifts can be negative: forcing a four-unit commitment can suppress conversion for considered purchases.
- Costs: COGS per unit and your real carrier cost, charged on every order. Free shipping never makes the carrier cost disappear; it removes the fee revenue instead.
Each scenario deliberately answers one question: what if every order looked like this? Tiers are competing structures for the same traffic, and comparing them as pure scenarios shows which structure to lead with. In reality your promotion will land a mix of baseline and tier orders, so your blended result sits between the baseline bar and your winning tier's bar.
A note on free shipping, because most tier models (including the original version of this tool) get it backwards: crossing the threshold is not a saving. You were collecting a shipping fee below it, and now you are not. The calculator treats the fee as revenue below the threshold and waives it above, so multi-unit tiers that unlock free shipping carry that cost honestly instead of being handed a phantom bonus.
Setting each tier's conversion uplift honestly
The uplift you assign each tier is the assumption that decides the ranking, so ground it in evidence:
- Use your own promo history first. In GA4 or Shopify, compare conversion during past multi-buy or bundle offers to the surrounding weeks. That relative lift is your anchor.
- Scale by attractiveness, not depth. A "buy 2" tier is a small ask: uplifts of 10 to 30% are common. A "buy 4" tier asks for real commitment; its uplift is usually lower than the shallow tier's unless the product is consumable and price-driven.
- Use negative uplifts where honesty demands it. If most customers only want one unit, an aggressive tier can add friction and hurt conversion. The break-even column tells you how much negativity the tier can survive.
The break-even uplift column is your safety margin. It shows the uplift at which each tier exactly matches full-price profit. A tier showing minus 32% beats full price even if conversion falls by a third, which is a robust bet. A tier that needs +80% is leaning entirely on an optimistic assumption. "Never" means the order itself loses money and no conversion rate can save it.
A worked example
The example data models a $60 product with a $20 unit cost, 3% baseline conversion, an $8 carrier cost, an $8.95 shipping fee and free shipping over $100. At full price a single order nets about $41 of gross profit (including the shipping fee you collect), which at 3% conversion is roughly $1,230 of profit per 1,000 sessions.
The "buy 2, save 10%" tier prices the pair at $108, which clears the free-shipping threshold and waives the fee, and makes $60 per order. With a 20% conversion lift it produces about $2,160 per 1,000 sessions, three-quarters more than baseline. Its break-even uplift is minus 32%: the bigger basket means this tier wins even if the offer somehow reduced conversion by a third.
The "buy 4, save 20%" tier is the striking one: $104 of profit per order despite the deeper discount, because four units absorb the shipping cost and the discount only applies to a $240 basket. At +50% conversion uplift it generates about $4,680 per 1,000 sessions, nearly four times baseline. Even that number needs scepticism: its whole advantage rests on customers actually wanting four units. Drop its uplift to minus 40% and it still beats baseline, and the model shows exactly where the crossover sits.
Designing a tier ladder that works
- Anchor the first tier just above current behaviour. If your average customer buys 1.3 units, "buy 2" is an easy yes. Starting at "buy 3" leaves the first rung of the ladder out of reach.
- Make each step earn its depth. A good ladder increases the discount slower than the quantity: 2 units / 10%, 4 units / 20% keeps margin per order growing. If margin per order shrinks as customers climb, the ladder is upside down.
- Let free shipping do some lifting. Setting the threshold so your second tier clears it stacks two incentives at the same basket size: you pay the waived fee once but gain both nudges.
- Cap the ladder where inventory or repeat-purchase logic says stop. A deep tier that clears your stock at thin margin steals from next quarter's full-price sales. This model prices the order, not the pull-forward.
Assumptions and limitations
- Single product, pure scenarios. Every order in a scenario takes that tier. Real promotions land a mix, so blended results sit between baseline and the winning tier.
- You supply the uplifts. The model does not predict customer response to tiers. It makes your assumptions comparable and shows the break-even, so you know how much error each tier can absorb.
- Gross-profit level. Ad spend, payment fees and overheads are excluded, since they apply roughly equally across scenarios and cancel out of the ranking. For discount modelling with CAC and breakeven ROAS, use the Optimal Discount Calculator.
- Static snapshot. No pull-forward, stock-up behaviour, returns, or long-term effects of training customers to buy in bulk.
Treat the winning tier as a hypothesis with a known safety margin, then confirm it with a real test. If you want help designing the offer around it, from landing pages to bundles to the media plan, that is what we do.
