Bundle Pricing
Bundle pricing groups complementary products at a discounted total to lift AOV and attach rate. Here's the formula, typical AOV lifts by bundle type, and where it works best.
Bundle Pricing
Selling two or more products together at a discounted total to lift average order value and attach rate.
Bundle pricing is a merchandising tactic where you combine complementary SKUs into a single offer priced below the sum of their individual prices. The discount is the trade: you give up a few points of margin per unit in exchange for a larger basket, fewer single-item orders, and lower per-SKU pick-and-pack cost.
It works best for categories with natural complements — skincare routines, gift sets, supplement stacks, build-a-bundle apparel — where the shopper is already considering more than one item. Done well, it shifts the buying decision from 'which one?' to 'which bundle?', which is a much better question for your AOV.
Bundles fall into three patterns. Pure bundles are sold only as a set (a starter skincare routine, never the individual serum). Mixed bundles let shoppers buy the set or the components separately. Build-a-bundle gives the customer a slot-based builder — pick any three tees, get 15% off — which feels like personalisation while still locking in the basket size.
As a tactic within pricing psychology, bundling leans on anchoring (the strikethrough total) and loss aversion (the saving you'd forfeit by buying singles). The discount is real, but the perceived saving is usually larger than the margin you give up — which is why a well-built bundle can lift contribution per order even after the markdown.
Bundle Price = (Σ Component Prices) × (1 − Discount Rate)
Σ Component Prices
Sum of component prices
Total retail price if each item in the bundle were bought separately.
Discount Rate
Bundle discount rate
The percentage off the combined price, expressed as a decimal (e.g. 0.15 for 15% off).
Bundle Price
Bundle retail price
The single price the customer pays for the full bundle.
A Shopify skincare brand bundles a cleanser (€28), a serum (€42), and a moisturiser (€35) as a 'Daily Routine' kit with a 15% bundle discount.
Sum of component prices: €105.00
Discount rate: 15% (0.15)
→ Bundle price = €105 × (1 − 0.15) = €89.25
The customer sees a €15.75 saving versus buying singles. If the brand's blended COGS on the three items is €31, contribution per bundle is €58.25 — versus roughly €22 contribution on a typical single-serum order. AOV moves from ~€42 to ~€89, more than doubling, even after the discount.
The lift you can expect depends heavily on the category. Bundles that match a real usage occasion (a full routine, a gift set, a starter kit) outperform bundles built from whatever's overstocked. The benchmarks below give realistic AOV uplift ranges by bundle type — useful when you're deciding which format to test first.
Typical AOV lift and attach rate by bundle format
| Bundle format | AOV lift vs single-item order | Attach rate (bundle shown → bundle added) | Best-fit category |
|---|---|---|---|
| Routine / kit (pure bundle) | +80% to +130% | 8-14% | Skincare, supplements, coffee |
| Gift set (seasonal pure bundle) | +60% to +110% | 6-12% | Beauty, candles, food & drink |
| Build-a-bundle (3-for, 5-for) | +40% to +90% | 10-18% | Apparel basics, socks, snacks |
| Frequently bought together (mixed) | +20% to +45% | 4-9% | Electronics, accessories, pet |
| BOGO / volume tier | +15% to +35% | 12-22% | Consumables, low-AOV apparel |
Two operational notes before you launch one. First, treat the bundle as its own SKU in your catalogue so margin, returns, and stock-outs are clean — a bundle that breaks because one component is out of stock erodes trust fast. Second, A/B test the discount depth: shoppers often convert similarly at 10% and 20% off, and the cheaper test is usually the right one to ship.
Bundle pricing FAQ
10-20% off the combined price is the sweet spot for most DTC categories. Below 10% the saving doesn't feel meaningful; above 25% you're usually leaving margin on the table without buying much extra conversion. Test two depths against each other rather than guessing.
Some cannibalisation is normal and usually net positive, because the cannibalised orders are larger. Watch the blended contribution margin, not just unit sales of the hero SKU. If contribution per visitor goes up, the bundle is working even if single-SKU volume dips.
On the product detail page as a 'Complete the routine' or 'Frequently bought together' module, on the cart drawer as an upsell, and as their own collection page for paid traffic. PDP placement tends to drive the highest attach rate; cart placement protects AOV on already-converting sessions.
No. Volume discounts (buy 3 of the same SKU, save 10%) reward quantity of one product. Bundle pricing rewards combining different products. They can coexist — a build-a-bundle catalogue is essentially a volume discount on a curated set.
Return rates on bundles are typically 10-30% lower than on single items, because shoppers self-select bundles when they're more committed. But partial returns are messier — decide upfront whether you accept them and at what refund value, and configure that in your returns app before launch.
Yes. Most brands set the free-shipping threshold below the cheapest bundle price so every bundle qualifies. This stacks two AOV levers — the bundle and the threshold — and removes shipping friction at exactly the moment the shopper is committing to a larger basket.
Set the price at the bundle level, not the slot level: 'Any 3 tees for €60' converts better than 'each tee €22 with 9% off in a bundle'. The fixed total removes mental math and anchors the value clearly. Make sure component AOV in the slots is consistent so the maths works for you.
Yes, and you should. The highest-leverage tests are bundle composition (which 3 SKUs), discount depth (10% vs 20%), and placement (PDP module vs cart upsell). Run each as a single-variable test and measure revenue per visitor, not just bundle conversion rate.
It works, but the format changes. Above ~€200 AOV, shoppers respond better to 'frequently bought together' add-ons (a case with a camera, a stand with a monitor) than to large pure bundles. The accessory attach is the AOV lever, not a deep multi-product discount.
Plan for 2-4 weeks minimum so you cover a full purchase cycle and at least one weekend peak. Attach rate stabilises within a week, but revenue-per-visitor needs more samples because the bundle is a smaller slice of total orders. Don't call a winner on three days of data.
Test ideas before you ship them
Run unlimited A/B tests, attach hypotheses to outcomes, and build a searchable archive of what works — and what doesn't.