Questions we can investigate
- Net sales, refunds and order trends
- Margin by product or category when cost data is available
- Marketing spend and acquisition measures where source data supports them
Industry solution
E-commerce analytics
Are sales growth and product margins moving together?
Business areas for this industry
Explore the relevant analytics areas
These are applicable areas to consider. Your agreed question and available data determine which ones are included in a project.
Need a different combination? Custom Analytics can be scoped around your requirements.
Orders, refunds and product economics
Understand what remains after the sale
Order totals can hide discounts, refunds and uneven product margins. We agree a net-sales definition first, then connect orders, product lines and cost data to show what is driving the result.
A focused dashboard can compare products, categories and sales periods. Marketing data can be added when channel labels and attribution rules are sufficiently consistent. The analysis describes what the data supports; it does not turn a channel correlation into proof of incremental sales.
The synthetic store below has €92,400 of June net sales across 960 included orders, with €37,884 gross profit before fulfilment and marketing expenses.
Useful starting data
- Orders, order lines, dates, product IDs and net amounts
- Refunds, discounts and product costs
- Marketing exports and attribution definitions when needed
Start with column names. Remove personal identifiers and confidential values from any example.
What you receive
A scoped dashboard, agreed KPI definitions, data-quality notes, written observations and a documented handover. The Fit Check identifies which questions your available data can support.
View a labelled sampleMake the calculation rules explicit
Net sales
Confirm VAT, discounts, refunds, cancelled orders and the reporting date. In this example, net sales are stated after €3,600 of refunds and exclude VAT.
Gross margin
41% in the example: (€92,400 − €54,516) / €92,400. Product cost is included; fulfilment and acquisition costs are not. Gross margin is not net profit.
Average order value
€96.25 from €92,400 / 960 included orders. The dashboard rounds the display to €96. Order inclusion rules and return timing must be agreed.
Customer and channel contribution
Add context before reallocating budget
The example’s channel view assigns orders to an illustrative last-click source. It reconciles to the order total, but the assignment is descriptive. An email channel’s sales share is not a causal estimate of what would happen if that channel stopped.
Customer analysis can add repeat-purchase patterns, concentration and segment comparisons when consistent identifiers are available. The customer preview shown here is a separate illustrative dataset, included to demonstrate the type of additional report.
Before production, we confirm the join keys, attribution window, treatment of unknown sources and whether aggregate data can answer the question without personal identifiers.
Before you begin
Can you combine store and advertising exports?
Where their date ranges, currencies and campaign identifiers can be reconciled. A Fit Check identifies missing fields and reporting mismatches before scope is confirmed.
Will the report prove which campaign caused sales?
A conventional dashboard describes attributed activity. Causal claims need a suitable experimental or analytical design and cannot be inferred from channel totals alone.
What if costs are unavailable?
We can scope sales and refund reporting, while clearly excluding margin conclusions. Cost data can be added as a later agreed extension.
Example project scope
From store exports to a recurring decision view
Start with a clear period and an accepted net-sales definition. The first scope can compare category contribution and refund treatment, with missing costs visible rather than hidden inside an average margin.
If stock balances and movements are available, an inventory report can be added to review availability and cover. The stock illustration is a separate synthetic dataset and does not explain the sales figures on the store preview.
The final scope specifies the question, accepted sources, excluded calculations and the output to be delivered. Any additional view is an agreed extension rather than an implied inclusion in every package.
Start with one business question
Start with your question and a description of your data.