Discount Analytics That Explain Every Order

Short Answer

To judge promotions by what they earn instead of what they sell, you need three things joined per order: which campaign applied, how much it discounted (including shipping), and what the products cost. Discount Prime's Analytics page does this for orders that carried its campaigns, using Shopify's "Cost per item" as the cost source, and reports an Estimated Profit per order and per campaign. Read it for what it is: attributed, gross-level profit on discounted orders. It is not incremental profit, it does not reflect refunds, and it is only as good as your cost data.

Merchant Scenario

EverPeak Commerce is a fictional multi-brand Shopify retailer selling outdoor equipment, apparel, and accessories. It runs many campaigns at once: wholesale pricing, Buy X Get Y, tiered discounts, shipping incentives, flat product discounts. Marketing reports record revenue, finance sees margins shrinking, and nobody can say which promotions earn money.

Alternatives Compared

Check which reports your Shopify plan includes before deciding you need an app for this. A BI setup is the right choice when you need refunds, payment fees, fulfillment, and ad spend in the same number.

What Discount Prime Reports

How Estimated Profit is calculated

Per order: revenue (after discounts) of the lines that have a cost, minus their product cost, minus the shipping subsidy the merchant absorbed. Lines without a cost are left out of both revenue and cost, so they neither inflate nor reduce profit. It excludes payment fees, fulfillment and packaging, returns, ad spend, app fees, and taxes. Call it gross profit after discounts and shipping subsidy, not net profit.

Limits to know before you trust the numbers

• Paid orders only. Orders enter analytics when Shopify marks them paid.
• No refunds or cancellations. Refunded and cancelled orders are not subtracted. For categories with high return rates, adjust before drawing conclusions.
• Attribution is per line. A line is attributed to a campaign when its variant belongs to that campaign; set-layer offers (bundles, cross-sell, gifts, upsells) and codes are matched from the order's line properties and discount applications. Only campaigns still active when the order is processed are considered. Discounts from other apps appear as unaccounted.
• Discount given includes compare-at savings. The figure adds campaign discounts and the gap between compare-at and selling price on those lines.
• Cost timing. Costs come from Shopify's cost per item and refresh nightly; the nightly job also recalculates costs on the last 30 days of orders. Profit on recent orders therefore reflects the current cost, not necessarily the cost on the day of sale. After fixing a missing cost, use "Calculate again" on older orders.
• AOV uplift is a comparison, not a cause. It compares the average order value of campaign orders with non-campaign orders. Shoppers who buy more are more likely to qualify for spend-based campaigns, so a positive uplift does not prove the campaign raised order values.

Anatomy of One Order

Illustrative assumptions: four products, all with cost set; a Tiered Spend Discount of 15%; standard shipping cost $12.40 given free.

This lets support explain the price the customer paid and lets finance see the gross result. It does not say whether this customer would have bought without the discount.

Reading Two Campaigns

Illustrative figures for one month, as the Top campaigns view would show them:

On revenue, A looks stronger; on attributed profit, B does. Before scaling B or cutting A, check:

• Incrementality. Attributed profit counts every order that carried the campaign, including orders that would have happened at full price. A campaign with lower attributed profit can still add more profit if it brings orders that would not otherwise exist. Compare against a baseline period or, better, a holdout (a period, region, or customer group without the campaign).
• Product mix. If A covers low-margin categories, its color reflects the category as much as the discount.
• Refunds. If A's categories have higher return rates, its real result is lower than shown.
• Cost coverage. If many of A's lines lack cost, its profit is calculated on a subset.

A Review Routine Instead of Alerts

Discount Prime does not send margin alerts. The colors are on the Analytics page, so make a habit of looking:

1. Weekly, sort Top campaigns by margin and open any yellow or red campaign.
2. In the Orders tab, open recent orders from that campaign and check for highlighted lines with missing cost.
3. If margins thinned without a settings change, check whether a supplier cost rose in Shopify (the nightly sync will have applied it to recent orders).
4. Decide: adjust the discount depth or threshold, reprice the category, narrow the campaign's products, or end it.

The weekly email is a useful reminder to open the app, but its figures count all orders in the last seven days, not only discounted ones, and its "top campaign" is ranked by discount given. Do not read its revenue line as revenue the campaigns caused.

Measurement for the Analytics Program Itself

• Primary: Estimated Profit per campaign, adjusted for refunds, next to its baseline.
• Guardrails: share of campaign revenue with cost data; discount given as a % of revenue.
• Next decision: campaigns with persistently thin or negative margin get a parameter change or an end date; campaigns with healthy margin are candidates for a controlled test of a deeper or broader offer.

Common Mistakes

• Reading attributed profit as incremental profit.
• Ignoring refunds and returns, which the app does not subtract.
• Trusting profit figures while many lines lack Shopify cost per item.
• Treating AOV uplift as proof that a campaign raised order values.
• Waiting for an alert that does not exist instead of reviewing margin colors on a schedule.
• Quoting the weekly email's revenue as campaign-driven revenue.