tl;dr
Your mean AOV is often misleading — this report shows the full distribution of order values so you can see what's actually happening
Use mean, median, and mode together: the median and mode are almost always lower than the mean, and they're often a better reflection of the typical order
The breakdown by value interval reveals where your orders cluster — usually well below your mean
The driver analysis shows whether higher AOV comes from more units per order or higher value per unit (it's almost always the former)
Use the report to set your minimum order value for free shipping, design upselling strategies, and measure their impact over time
Controls
Before reading the numbers, set up the four filters at the top.
Customer Type — filter on All Customers, New Customers, or Repeat Customers. Many brands see a significant difference in AOV between first-time and repeat buyers — and the right strategy to increase it will differ for each group.
Value Interval — orders are grouped into brackets of this size. You can go from €2.50 to €250. Pick an interval that fits your price range — if most orders are between €20 and €100, an interval of €10 gives a cleaner picture than €50.
Revenue Display — show revenue figures as totals or divided by number of orders. Switching to per-order makes the trend lines in the breakdown chart run consistently upward as order value increases, which is easier to read when comparing brackets.
Average Order Value basis — choose what "order value" means:
Net Revenue — after discounts, taxes, and returns
Gross Revenue — before any deductions
Gross Revenue excl. Shipping — the price the customer paid for the products only, excluding any shipping charges you collected. Useful if you want to understand the actual product value being ordered, independent of delivery pricing.
Note: In other Klar reports and dashboards (e.g. the Daily Overview), AOV is always shown as Net Revenue. The AOV Report is the only place in Klar where you can switch between Net and Gross.
What the report shows
Mean, Median, and Mode
The three cards at the top each represent a different way to define "average":
Mean — total revenue ÷ number of orders. This is what most people call the average, but it gets pulled upward by large orders. If you only look at this, you'll often get an inflated sense of what a typical order looks like.
Median — the middle value when all orders are sorted low to high. Half your orders are below this, half above. Usually 10–15% lower than the mean.
Mode — the most frequently occurring order value. Often the most actionable number — it tells you what your customers most commonly spend.
Typically: Mean > Median > Mode. If you see a large gap between mean and mode, a big chunk of your orders are well below what your mean suggests.
Order value distribution
The chart and table below the summary cards group your orders into the brackets you configured. For each bracket, you can see:
Order count and its share of total orders
Revenue and CM2 — in total or per order, depending on your Revenue Display setting
Units per Order — how many items are in an average order in that bracket
Value per Unit — the average price per item in that bracket
What you'll typically find: more than 50% of your orders cluster in brackets below your mean. The revenue distribution is less skewed than the order distribution — because fewer orders in the higher brackets is partially offset by their higher value.
The driver insight: look at Value per Unit across brackets. In most stores, this stays roughly constant as order value increases. That means higher-AOV orders aren't driven by customers buying more expensive products — they're driven by customers buying more units. This directly shapes your upselling strategy: add-ons and bundles that increase item count will move the needle more than premium product positioning.
AOV development over time
Two chart + table combinations show how order value evolves:
By calendar month — track how mean and median are trending, alongside the standard deviation (a measure of how spread out your order values are). If standard deviation stays high, you have a wide range of order sizes and the mean continues to be a poor proxy for typical behaviour.
By order count — shows how AOV changes as customers place their 1st, 2nd, 3rd order and beyond. You'll typically see AOV grow as customers reorder, driven again by units per order rather than value per unit. Voucher rate usually decreases with subsequent orders as customers become less reliant on discounts to convert.
Both tables include: Mean, Standard Deviation, Median, Mode, Units per Order, Value per Unit, Voucher Rate, and Refund Rate.
How to use it
Set your minimum order value for free shipping
The order value distribution tells you exactly where your orders cluster. If a large share sits just below a round number — say, 40–50% of orders in the €40–50 bracket — setting your free shipping threshold at €50 incentivises those customers to add one more item rather than pay for delivery. Combined with a small, relevant add-on product surfaced at checkout, you can move a significant portion of those orders into the next bracket.
Measure the impact of bundling and upselling
Once you've introduced a minimum order threshold, product bundles, or cart upsells, this report shows you whether it's working — not just in overall AOV, but in how the distribution shifts. Did the mode jump? Did the €40–50 bracket shrink and the €50–60 bracket grow? That's the signal you're looking for.
Analyse a specific product
Use the product filter to scope the report to a single SKU. For your top sellers, check whether their AOV distribution differs from your store average — and whether there's a specific bracket worth targeting with a bundle or add-on for that product specifically.
Understand customer lifecycle value
The AOV by order count view helps you set realistic targets for new customer orders and understand at which point repeat buyers start spending more. Use it alongside the Time Lag report to get a fuller picture of how customer purchasing behaviour evolves.