May 20, 2026
The Analytics page helps you understand the relationship between your revenue and advertising spend. It calculates Return on Ad Spend (ROAS) automatically and visualizes daily trends so you can see which campaigns are driving results.
Three metrics at the top of the page provide a quick overview for the selected period:
Filter data by:
The date filter applies to both orders (for revenue) and expenses (for ad spend).
Shows how many units customers bought each day in the selected period. Each bar is the total quantity sold (line item quantity minus refunds) for that day. A dashed orange line marks the period average per active day.
When the selected range supports it, the chart also compares against the previous comparable period so you can see whether sales are picking up or slowing down. The previous period is chosen automatically:
When a comparison is active, each day’s bar is paired with a grey “Previous period” bar (drawn to the left), a thin dashed grey line marks the previous-period average, and a badge above the chart shows the change versus the previous period in both absolute units and percent.
Shows how customers tend to buy: how many orders contained 1 item, 2 items, 3 items, and so on. Each bar represents the number of orders with that exact item count. Item count is the line-item quantity minus refunds, summed across the order. Orders that net out to zero items (fully refunded) are excluded.
Badges above the chart summarise the period: the total number of orders counted, the average items per order, and — when a comparison is available — the change in average items per order versus the previous comparable period.
When the selected range supports it, each bucket also shows a grey “Previous period” bar to the left of the current one, with a thin dashed grey line marking the previous-period average. The previous period is picked using the same rules as the Daily items sold chart (today vs. yesterday, this month vs. last month, etc.); all-time has no comparison.
An interactive chart shows daily revenue and ad spend side by side. Each advertising source (e.g. Google Ads, Meta Ads) appears as a separate series so you can see exactly where your budget is going.
Revenue is the sum of net payments across all active orders for each day. Net payment is the amount actually received after refunds and adjustments. Ignored orders are excluded from the calculation.
Ad spend is pulled from your expenses that are categorized as “Ads”. If an expense covers a date range (e.g. a monthly ad bill), the amount is spread evenly across each day in that range, clipped to the selected period.
For VAT-registered shops, the net (ex-VAT) amount is used, and linked VAT expenses are excluded to avoid double-counting.
Below the chart, a table breaks down ad spend by expense name. Each row shows:
This helps you compare spending across advertising channels at a glance.
To see data on the Analytics page:
If you’d rather not enter Facebook/Instagram ad spend by hand, connect your Meta ad account from Settings > Facebook Ads. Once connected, Panelque pulls your daily ad spend each morning and records it as expenses in the “Ads” category. The Analytics page picks them up automatically.
Open Analytics > Best sellers to see what’s actually moving in your store. The page ranks items by units sold within the selected date range (today, this month, last month, all time, or a custom range) and offers three views:
Each row links to the product or variant detail page so you can drill in.