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Do your promotions increase the average order value or reduce your profit margin?
Schedule a meetingLearn about our promotions managementThe average basket size is the average amount spent per customer on each checkout or order: revenue ÷ number of transactions. It is one of the key performance indicators for retail, because revenue = foot traffic × conversion rate × average basket size.
The Essentials in 6 Questions
The average amount of a receipt or order.
Store management, category managers , e-commerce, pricing.
Daily in-store monitoring, analyzed weekly.
By store , channel, department or customer segment.
Growing revenue without depending on foot traffic.
Revenue ÷ number of tickets .
The average basket size is read in terms of value; its version in terms of quantity is called the sales index.
| Indicator | Formula |
|---|---|
| Average Basket | Revenue ÷ number of tickets (or orders) |
| Sales index (basket quantity) | Number of items sold ÷ number of tickets |
| Average price of the item | Average basket size ÷ sales index |
It is always specified whether the average basket size is calculated excluding or including tax, and over which period. For the version based on the number of items, see the sales index .
A store that makes €84,000 including VAT in a week with 2,400 tickets has an average basket of €35.
Average basket size: €84,000 ÷ 2,400 tickets.
items per ticket: 7,200 items ÷ 2,400 tickets (sales index).
average price per item: €35 ÷ 3.
The same basket can come from more items or more expensive items: the two are not managed in the same way.
By selling more items per ticket or higher value items, without destroying the margin.
Suggest a complementary product
Cross-selling: the case with the phone, the sauce with the pasta.
Offer the next range up
Up-selling: a more complete, more durable or larger version.
Building bundled offers
The bundling: a package at a single price, which makes the savings visible.
Set thresholds
Free delivery or discount starting from a certain amount, set slightly above the current basket.
These levers are combined: cross-selling , up-selling , and bundling . However, a basket that grows thanks to overly generous promotions can reduce the margin: the margin per transaction is always tracked based on the average basket size.
Mixing pre-tax and post-tax prices, comparing incomparable periods, forgetting about the margin.
Short answers to the most frequently asked questions about the average basket size.
The average order value (AOV) is the average amount spent by a customer on each in-store purchase or online order. It is calculated by dividing the revenue for a given period by the number of transactions or orders during that period. It is one of the three drivers of revenue, along with foot traffic and conversion rate: revenue = foot traffic × conversion rate × AOV. Increasing the AOV therefore allows you to boost sales without relying on an increase in the number of customers, which is often more expensive to achieve.
The formula for average basket size is: average basket size = revenue ÷ number of transactions (or orders). Example: a store that generates €84,000 (including VAT) in a week with 2,400 transactions has an average basket size of €35. It is always specified whether the calculation is done excluding or including VAT, and over what period. It is often broken down into two factors: the number of items per transaction, called the sales index, and the average price of the item. Average basket size = sales index × average price of the item.
The average basket size measures a monetary amount, while the sales index measures the number of items. The average basket size is revenue divided by the number of transactions; the sales index is the number of items sold divided by the number of transactions. The two are often interpreted together: a rising average basket size can be due to customers buying more items, or more expensive items. Distinguishing between the two reveals which lever is truly at play: product assortment and placement on the one hand, and price and premiumization on the other.
To increase the average basket size, you can adjust the number of items per transaction and their value. Classic levers include cross-selling , which suggests a complementary product; upselling , which offers the next product range up; bundling , which highlights the savings of buying a bundle; and thresholds, such as free delivery above a certain amount. Store layout and sales staff training also play a role. Each lever is measured by the profit margin per transaction: a larger but less profitable basket is not progress.
Average basket size can be calculated either excluding or including tax; the key is to maintain consistency over time and across channels. Including tax is more meaningful for in-store teams, as it reflects the actual amount paid by the customer. Excluding tax is more accurate for analyzing profitability and comparing products subject to different VAT rates, for example, food at 5.5% and non-food at 20%. Mixing the two between reports creates false discrepancies, especially when the food and non-food mix changes.
A store's revenue is the product of three factors: foot traffic (the number of visitors), conversion rate (the percentage of visitors who make a purchase), and average basket size. In other words, revenue = foot traffic × conversion rate × average basket size. A 5% increase in average basket size, with constant foot traffic and conversion rates, therefore translates into a 5% increase in revenue. This is often the quickest lever for growth, as it targets customers already in the store.
Key Takeaways
Do you want to increase your average order value without sacrificing your profit margin?
Booper simulates the effect of your prices and promotions on the basket and margin, before launching them.
Let's talk about your average cart value →Learn about our promotions management
The sales index (IDV) is the average number of items sold per sales receipt: items sold ÷ number of receipts. It should not be confused with the average basket size, which measures an amount, not a volume. It is directly influenced by category management decisions: layout, product assortment, and cross-merchandising.

Faced with current market volatility, B2C pricing can no longer rely on intuition and instead requires a data-driven strategy. This analytical rigor makes it possible to adjust prices in real time to maximize profitability without sacrificing volume. A successful transition to this model offers profit growth potential of up to 9%.
Among the strategies tested, the psychological price point (€9.99) remains one of the easiest to implement.

Retail promotion management must rely on rigorous data analysis to ensure profitability. By mastering uplift and cannibalization, retailers can transform a high-risk lever into a tool for healthy growth. Precise monitoring is vital, as six out of ten promotions today prove to be unprofitable.
The purpose of BOOPER’s Promotions Management module is to automate this process rather than calculate it manually: to simulate uplift and cannibalization before launching a campaign, not after.