Choose the decision you need the numbers for.
Do you need to prepare more parcels, understand a quieter collection or see whether customers return? Those are questions you can use. They help you choose a meaningful number and comparison.
Look beyond the total. Connect the observation to the orders, products and customers behind it. That relationship gives you a clearer place to investigate.
A number becomes useful when you know what to do with it.
More orders sounds good. But what does that ask of you today, and which products or customers deserve attention? Daymerce brings insights and the workspace closer together.
Start with your question.
Are you preparing the next packing round, looking for products that need attention or trying to understand repeat purchases? Choose the question before the chart.
Read the trend and its explanation.
In Daymerce, see the order trend and the observations beside the numbers. Check the period and what the displayed amount or count represents.
Move to the work behind it.
Use the result to investigate an order, product or customer group. Then choose a specific next step, such as preparing the work or a relevant campaign plan.
Keep a direction for your working day, rather than another report to translate into a task later.
Give each amount a clear meaning
| Measure | Question to check |
|---|---|
| Gross sales | What product-sales amount does this report start from, before its specified deductions? |
| Discounts and returns | Which deductions are included, and on which date does the report recognise them? |
| Net sales | Is this product sales after the report’s discounts and returns, excluding its separate tax and delivery amounts? |
| Total sales | Which tax and delivery amounts are added to net sales? |
| Average order value | Which sales amount and order count form the numerator and denominator? |
| Payout | What did the provider transfer after fees, refunds, adjustments or timing differences? |
For the standard overview, Woo describes net sales from gross sales less returns and coupons, with taxes and shipping treated as separate metrics. The Revenue report has additional refund-date and refund-allocation details. Full and partial refunds, including their tax and shipping allocation, need careful matching to the report and version you use.
Do not reconcile unlike totals by changing labels until they happen to match. Keep the source report, selected settings and export alongside your explanation. Neither net sales nor a payout is a complete profit calculation.
Two weeks, one useful interpretation
The following is an independent fictional worked example in euros. It is not a screenshot export or a reported Daymerce customer result. “Returns” here means the worked example’s product-sales deduction; taxes and delivery are separate. We use net product sales divided by the qualifying order count for the illustrated average.
| Measure | Week A | Week B |
|---|---|---|
| Gross product sales | €1,000 | €1,200 |
| Discount deduction | €100 | €180 |
| Product-return deduction | €90 | €120 |
| Net product sales | €810 | €900 |
| Qualifying orders | 18 | 20 |
| Illustrative average | €45 | €45 |
| Separate delivery amount | €50 | €60 |
| Separate tax amount | €180 | €200 |
| Worked-example total | €1,040 | €1,160 |
Week B has two more qualifying orders and €90 more net product sales. The illustrated average remains €45. Discounts rose by €80 and product-return deductions by €30. Those observations support questions, not a conclusion that a promotion succeeded.
Ask which products and orders changed, whether the same sale was active in both periods and whether return timing explains part of the difference. Review costs before saying the extra sales improved profit. This example leaves out product costs, labour and provider fees, so it cannot tell you whether profit increased.
Keep periods, statuses and dates consistent
Compare equal periods in the same time zone and record which order date the report uses. Seven complete days and seven days that include an unfinished afternoon are not equivalent. Weekday mix, seasonality and a launch can all affect the comparison.
Check included and excluded order statuses and whether imported or recently updated records have been processed by Analytics. A difference between an order list and a report may reflect filters, processing or recognition dates. Woo documents refund reporting by the refund event rather than simply moving every amount back to the original order date.
If the records do not match, take one order or refund and trace it through the source before interpreting the whole chart. Keep the order’s payment and fulfilment context in view. Never clear a discrepancy by editing a real order solely to make a report look tidy.
Turn one signal into one next question
| Observation | Investigate | Possible next step after checking |
|---|---|---|
| Orders rise; average stays flat | Which items, quantities and customer groups changed? | Adjust packing capacity or review a relevant product pairing. |
| A range becomes quiet | Is it available and visible, and was demand comparable? | Correct an actual availability/content issue or investigate demand. |
| More repeat purchases appear | Is identity matching and the comparison period consistent? | Review a relevant follow-up for an eligible customer group. |
| Returns rise | Which products, reasons and recognition dates explain them? | Improve a verified product detail or address an operational issue. |
Choose one action that fits the observation.
If a product group is receiving fewer orders, first check whether its products are available and their information is clear. That is more focused than immediately discounting everything.
Then prepare an action that fits what you found: improve a product detail, plan a relevant campaign or adjust the work schedule. Later, compare the same period and definition again. A change after your action was not necessarily caused by it.
Official sources
Metric and report guidance was checked against official WooCommerce documentation on 23 October 2026. Check the definitions and periods in your report. The worked calculation is separate from the fictional data in the Daymerce capture.