Seller worksheet
Product Profit Audit Worksheet
Use this worksheet to review one product before launch, reorder or advertising scale. It helps you separate visible gross margin from the costs that decide real contribution profit.
Worksheet
| Selling price | Expected checkout price after normal promotions | Do not use list price if shoppers usually buy with a coupon. |
| Landed product cost | Supplier cost, freight, duty and inspection | Use the cost per sellable unit, not only factory quote. |
| Fulfillment and packaging | Pick, pack, shipping, packaging and handling | Include variable costs that rise with each order. |
| Marketplace and payment fees | Referral fees, platform fees and payment processing | Check current platform documentation before final decisions. |
| Return allowance | Expected refund or replacement cost | Use a conservative estimate if history is limited. |
| Ad cost per order | Paid traffic or creator cost allocated per sale | Compare base and scale scenarios separately. |
Worked example
A product with a $32 checkout price, $9 landed cost, $5.20 fulfillment, $3.20 platform fee, $1.60 return allowance and $7 ad cost has $6 of contribution profit per order. That may be workable for a test, but it is not enough room for uncontrolled discounts or rising ad costs.
How to use this in a review
Use this worksheet with real numbers from your seller dashboard, payment reports, supplier invoices and campaign data. If a number is not yet known, use a conservative estimate and label it clearly. Unknown costs should be investigated, not ignored. The worksheet is most useful when it becomes part of a repeatable decision habit instead of a one-time calculation.
After completing the rows, write a clear next action. A good action may be to test a smaller coupon, improve product images, reduce bids, delay a reorder, request a better supplier quote or pause scaling until more orders arrive. Avoid vague actions like "monitor performance" unless you also define the metric, threshold and review date.
Quality check
Before acting, ask whether the result depends on optimistic assumptions. If the product only works with low return rate, cheap traffic, perfect fulfillment and a high conversion rate, it is not yet a strong product. Build a stress case with worse inputs and decide whether the product still deserves money, time or inventory.
Related resources
How to turn this page into an operating habit
Do not use this resource only once. The value comes from repeating the same review after new information arrives. Start by recording the current assumption, the source of the number and the date it was checked. Then decide which number is most likely to change the conclusion. For Product Profit Audit Worksheet, the most important lens is usually product economics. That means the seller should review selling price, product cost, fulfillment cost, platform fees, return allowance and ad spend before treating the result as reliable.
A product that appears profitable at gross margin level can become weak after fees, returns, discounts and acquisition cost are included. A good review does not need to be complicated. It needs to be consistent. Use the same rows, the same definitions and the same decision threshold each time. When the product changes, update the assumptions rather than starting from memory.
Seller review notes
The next practical step is to build base, conservative and scale scenarios before making a larger commitment. Write down the answer in a short note: continue testing, improve the offer, reduce spend, adjust price, delay inventory or pause the product. This written decision matters because ecommerce dashboards can change quickly. Without a note, it is easy to forget why a product was approved or rejected.
If several people work on the same store, use the note as a shared decision record. The operator, media buyer and sourcing person should be able to see the same assumptions. That makes the resource more useful than a private calculation because it turns numbers into a team workflow.
Questions to answer before acting
- Which input is estimated rather than confirmed by real store data?
- What happens if acquisition cost is 20% higher than expected?
- What happens if returns, refunds or shipping cost increase?
- Is the decision based on one product, one campaign or enough data to be trusted?
- What specific action will be taken if the result is below target?