Testing a Shopify discount means checking the cases that should fail as well as the basket that should succeed. A code may work for the intended product but also apply somewhere it should not, or disappear after a customer follows a different link. Use a small set of real checkout scenarios and compare every result with the offer's written rules.
Translate each rule into a scenario
Start with the minimum spend, eligible products, customer restrictions, usage limits, and expiry. Create a basket below the threshold, exactly at it, and above it. Include an excluded item and a customer who should not qualify.
If the offer interacts with other promotions, test those combinations too. Use controlled records and avoid creating unnecessary real transactions. Record the expected result before testing so a surprising outcome is not mistaken for intended behavior.
Build a small matrix with expected outcomes
For an illustrative 15% offer on selected products above a $50 subtotal, start with $49.99, $50, and $50.01 eligible baskets. Then add an excluded product, an ineligible customer, an expired code, and a second discount. Write whether each case should qualify and what the resulting total should be before opening checkout.
You do not need to test every possible basket in a large catalog. Cover each rule separately, then test interactions that could change the result: an excluded item contributing to minimum spend, a discount reducing the qualifying subtotal, or a shipping incentive applying at the same time. Prioritize combinations that are likely, costly, or difficult for support to correct.
Keep customer state in the matrix too. A returning customer who already redeemed a single-use offer is a different test from a new eligible customer. Use approved test records and the store's supported testing process so your checks do not create misleading sales data or unwanted customer messages.
Follow the customer's actual route
Open the link from the Sendvio campaign preview or test message. Check whether the discount applies automatically or requires entry, and verify the code shown in the email. A correct code entered manually does not prove the campaign link works.
Inspect mobile checkout and the destination language. Confirm that the email's description, displayed price, and final discount agree. Keep shipping eligibility and product availability in view when they affect the promise.
Trace a failure to the responsible step
If a code works when entered manually but fails from the email, investigate the link, destination, and automatic-application behavior. If it fails through both routes, inspect the offer configuration and eligibility. If checkout applies it correctly but the displayed email price is wrong, the copy or content data needs correction.
Record the campaign version, language, device, scenario, expected result, and observed result. A screenshot can help, but the written rule matters: a reviewer should know why the result is wrong without reconstructing the campaign. Remove personal information and private checkout tokens from any evidence shared outside the team.
Retest after the final edit. Changing a product collection or combining rule can affect scenarios that previously passed. Keep that retest focused on the changed rule and its dependencies, while always confirming the main customer route from the final message to the intended destination.
Resolve failures before activation
Fix the configuration or revise the copy when the rule cannot behave as advertised. Do not rely on customer support to explain a known mismatch after the send. Retest the affected scenarios rather than repeating only the successful path.
Save the checklist with the campaign and note what changed. It becomes a useful starting point for similar offers, provided dates and product rules are updated. A promotion should be easy for the customer precisely because the team tested its complicated edges in advance.
A promotion is ready when its important promises are supported by successful tests and any remaining limitations are accurately communicated. If you cannot enforce a complicated exception reliably, simplifying the offer is often the better release decision. A smaller, dependable promotion is easier to trust and easier to evaluate afterward.