Seller worksheet
Ad Budget Readiness Worksheet
Use this worksheet before increasing budget on TikTok Shop, Amazon PPC, Meta ads or other paid traffic. It connects campaign metrics with product economics.
Worksheet
| Contribution before ads | Profit available before acquisition cost | This is the real spending ceiling. |
| Current cost per order | Ad spend divided by paid orders | Review by campaign type, not only total account average. |
| Break-even ROAS or ACoS | Revenue efficiency needed to avoid losing money | Compare against target margin, not just break-even. |
| Listing conversion signal | Conversion rate, click quality and buyer objections | Weak pages make traffic more expensive. |
| Return or refund risk | Refund rate by product and traffic source | Paid cold traffic may return differently. |
| Budget rule | Maximum spend before pausing or revising | Write the rule before scaling starts. |
Worked example
If a product has $12 contribution before ads and the seller wants to keep $4 profit per order, the practical ad budget is $8 per order. A campaign producing $10 cost per order may still generate sales, but it is below the seller's target economics.
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 Ad Budget Readiness Worksheet, the most important lens is usually advertising efficiency. That means the seller should review cost per order, conversion rate, contribution before ads and profit after ads before treating the result as reliable.
If a campaign looks strong on revenue but weak after ad spend, the seller should not scale the budget until the product has a clearer margin buffer. 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 separate branded, retargeting and cold traffic before judging whether the product is ready for more budget. 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?