BYOB pricing: percent, fixed, and buy X get Y

\n\nA build-your-own-box on Shopify is not one product. It is a shape. And that shape can be priced four different ways, each with different consequences for what the shopper sees, how the cart maths behaves, and what the merchant can honestly report on.

This is the decision matrix. Four pricing shapes, one at a time, with the tradeoff named.

1. Percent off

The most common. The shopper picks their items. The total of their picks is calculated at retail. A percentage discount is applied to the total at cart.

Pick any 6 snacks. Get 15% off.

What the shopper sees at cart: Six snacks at full retail, then a single Bundle: 15% off discount line. The cart total drops.

What the maths does: Applied through Shopify's Discount Function. Bundle savings scale with the customer's picks. A shopper picking six ₹200 snacks saves ₹180. A shopper picking six ₹350 snacks saves ₹315.

Where it fits: Categories where the retail-price variance across items is meaningful and the merchant wants premium picks to feel appropriately more discounted. Skincare kits, snack boxes, coffee samplers.

The tradeoff: The discount is not a fixed number. The shopper cannot pre-compute the "bundle price" from a landing page. Campaign creative has to speak in percentages, which converts less crisply than a hard number.

2. Fixed amount off

The shopper picks their items. A flat currency discount comes off the total.

Pick any 3 candles. Save ₹300.

What the shopper sees at cart: Three candles at retail, minus a flat ₹300 discount.

What the maths does: Applied through the Discount Function as a fixed monetary reduction. Predictable to the rupee.

Where it fits: Merchandising drops where the merchant has done the AOV maths beforehand and wants the shopper to see a specific savings number in the campaign creative. "Save ₹500 on your 3-candle set" reads harder than "15% off".

The tradeoff: Fixed amounts do not scale to the shopper's basket. A ₹300 discount on three ₹250 candles feels great. The same ₹300 on three ₹1,200 candles feels stingy. If your BYOB pool has wide price variance, fixed amount off can misalign perceived value with actual value.

3. Fixed bundle price

The bundle is priced as a single number. The shopper picks their items; the total resolves to the bundle price regardless of the underlying retail total.

The 6-snack box: ₹899. Any 6.

What the shopper sees at cart: Six snacks and a single bundle line at ₹899. Individual snack prices may or may not display depending on merchandising choice.

What the maths does: Applied through the Discount Function as a compensating discount — retail total minus ₹899. If the shopper picks six premium snacks whose retail totals ₹1,400, the discount is ₹501. If they pick six standard snacks whose retail totals ₹950, the discount is ₹51.

Where it fits: Categories where the shopper's picks should feel equivalent. Any 6 for ₹899 tells the shopper the merchant has done the pricing work and the answer is the same regardless of their choice. Gift boxes, starter kits, subscription samplers.

The tradeoff: Merchants have to be careful about the retail-price spread in the pool. If premium items are ₹300 and standard items are ₹100, savvy shoppers will always pick the premiums. The bundle economics need to survive that.

The alternative is to gate the pool — the premium items are only available in a higher-tier bundle. Wolfpack supports this through step-based configuration: the ₹899 bundle draws from a standard pool; the ₹1,499 bundle draws from a premium pool.

4. Buy X, get Y

The shopper adds N items of one category. A free or discounted item unlocks from a different category.

Add 3 shirts. Get 1 tie free.

What the shopper sees at cart: Three shirts at full retail, plus a tie priced at ₹0.00 (or with a highlighted discount).

What the maths does: Applied through the Discount Function with a conditional rule. The Discount Function detects that three qualifying items are in the cart and adds or discounts the reward.

Where it fits: Merchandising the merchant would otherwise struggle to sell. Slower categories become the reward. Attach rate goes up. This shape is particularly good for launching new SKUs — the "free" item introduces the shopper to a product they would not have picked deliberately.

The tradeoff: Complexity. Buy-X-get-Y is the most likely shape to confuse shoppers if the categories are not visually obvious. It requires clear category boundaries in the bundle configuration and merchandising copy that is unambiguous about what qualifies.

Which shape wins

There is no universal answer, but there is a small decision tree:

• Do you want the shopper to see a specific "bundle price"? → Fixed bundle price.
• Do you have a specific savings number that reads well in creative? → Fixed amount off.
• Do you want savings to scale with the shopper's basket? → Percent off.
• Do you want to attach a slower category to a hot one? → Buy X get Y.

Merchants often start with one and evolve. A BYOB that launches on percent off may migrate to fixed bundle price once the AOV is stable and the pool is priced consistently. A launch bundle with buy-X-get-Y may move to fixed amount off once the reward SKU becomes independently viable.

Where Wolfpack sits

Wolfpack Bundle Builder, BYOB supports all four pricing shapes through Shopify's Discount Function. They are configured in the merchant admin — no theme edits, no code deploys. Bundle subscriptions ride the same discount shape as one-time bundles, so a merchant can migrate a bundle between one-time and subscription without re-doing the pricing rules.

The shape does not change the storefront layout. The Classic, Standard, Compact, Horizontal, and BOBW templates all render any of the four pricing shapes the same way. The choice is purely a merchandising decision — which is where it should live, not buried in the app's plumbing.

If you are picking a pricing shape for a new BYOB and want a second read, the BYOB guide walks through the structural side of the bundle — categories, steps, min/max rules — that determines what pricing shapes are even eligible.\n