Updated November 8, 2026
Begin with a decision, not a bigger percentage
Two bundle offers can both look attractive while having different economics. Before changing from 10% to 15% off, write down what you want to learn. Are you trying to sell another eligible unit, improve completed orders or retain a minimum contribution per order? The answer determines what to measure. A discount should solve a customer problem while leaving enough room for the costs of supplying that order.
A worked example with explicit assumptions
Suppose a fictional two-item basket normally costs $60. At 10% off, the shopper pays $54; at 15% off, the shopper pays $51. Assume both baskets contain $24 of product cost and $6 of variable fulfillment cost. The first leaves $24 and the second $21 before payment fees, returns, acquisition and overhead. These are made-up inputs for an arithmetic illustration, not measured merchant performance.
Compare the number of completed orders needed
If 100 completed orders at the first discount contribute $24 each on those assumptions, their total is $2,400. Matching that contribution at $21 per order requires about 115 completed orders. Extra purchases could justify a deeper discount, but the offer has to generate them. More clicks or a higher add-to-cart count alone cannot settle that question. Recalculate the comparison with your actual costs before using it.
Keep the comparison fair
When comparing historical periods, record changes in traffic sources, prices, stock availability and other promotions. A seasonal sale or a new paid campaign can alter the customer mix. If you run a controlled experiment through a separate testing system, define the assignment and measurement approach before starting. Avoid changing the price, copy and product assortment together and then attributing the entire result to one discount.
Treat small samples carefully
There is no universal number of days or orders that makes every offer comparison reliable. Low traffic, refunds and a few unusually large orders can change the result. Track uncertainty and keep a minimum acceptable contribution in view. If there is not enough evidence, retaining the current offer and gathering more data can be a reasonable decision. Do not manufacture confidence percentages from a simple before-and-after table.
Check qualification and combinations
Before comparing results, confirm each offer actually works as intended. Check below-threshold and qualifying quantities, eligible variants and other active discounts. Your checkout total should agree with the price shown on the product page. Shopify discount-combination settings affect which savings apply together; a result from one cart does not prove all combinations work.
What BasketPeak provides today
BasketPeak’s current public listing describes configurable Quantity Breaks, Buy X Get Y and Mix & Match offers, live styling previews, automatic eligible checkout savings and bundle analytics. This article is an educational comparison method. It does not describe an included automatic A/B testing or Autopilot feature. Review the current listing and your available reporting before choosing how to evaluate a change.
Build and test your own offer
Explore Quantity Breaks, Buy X Get Y and Mix & Match in BasketPeak. Start with one useful offer and check your storefront and checkout before publishing.