Ecommerce Average Order Value: 2026 Benchmarks, Data & Key Insights

TL/DR summary

The Average Order Value sits at $150 as of October 2025. Luxury‑led baskets remain the largest, beauty remains lean, the Americas lead regions, and desktop orders outsize mobile. Use thresholds, attachments, and disciplined pricing to boost order value without denting conversion rates.

Key points

• Definition: AOV = total revenue divided by the number of orders; track it with conversion rate and profit.

• Monthly path: stable across most months, with April–May highs and a July trough.

• Industry spread: Luxury & Jewelry $328 vs Beauty & Personal Care $67; Consumer Goods at $296 in October.

• Geography: Americas $183, APAC $135, EMEA $128.

• Device: Desktop $192, Tablet $139, Mobile $133.

• Actions: set free shipping thresholds by market, cross-sell complementary products, use dynamic pricing, and strengthen loyalty programs.

Aim for sustainable increases in average order value. Encourage customers with clear thresholds and relevant bundles, and use purchase history data to guide offers so average order values rise without sacrificing margin or trust.

Data at a glance

Introduction

Average Order Value in ECommerce is not just a vanity figure. It is the signal that tells you how buyers translate intent into basket size, how pricing lands across segments, and how product mix and incentives shape each checkout. With the latest readings putting the global average order value at $150 in October 2025, leaders are revisiting what the number says about customer behavior, channel mix, and product economics.

For businesses, the attraction is simple. Average order values concentrate revenue into fewer transactions, help control customer acquisition costs, and inform decisions on thresholds, bundles, and margins without slowing conversion. The sections below bring the facts together and explain how to read them as an operator would.

Understanding the metric of the Average Order Value in ECommerce

A short refresher helps align teams on terms before we dive into the numbers.

Definition and formula

Average order value is the average amount buyers spend per transaction over a defined period. 

The average order value formula is straightforward: 

AOV = Total Revenue ÷ Number of Orders.

To calculate aov, simply divide the total revenue for the selected window by the order count. Many leaders track this alongside conversion rates to see whether merchandising changes shift basket size or only shift who converts. Tools like Google Analytics make it easy to calculate the average order and watch the revenue generated per checkout over time.

Why the metric matters

Average order value is a key performance indicator because it connects pricing strategy, merchandising, and the customer journey. When average order values rise without depressing conversion rate, money generated per session increases, often with better profit margins because fulfillment and servicing costs do not scale linearly with basket size.

Analyzing aov alongside purchase history reveals which product pages and offers encourage customers to add one more item, and which tactics risk lowering perceived value.

The latest picture on average order value (AOV): Month‑by‑month view

Below is the twelve‑month snapshot of the average order. The figures reflect the global series from November 2024 through October 2025. The values are reflected in the average dollar amount.

Monthly AOV (USD)

• Nov 2024: $154

• Dec 2024: $140

• Jan 2025: $160

• Feb 2025: $156

• Mar 2025: $156

• Apr 2025: $175

• May 2025: $177

• Jun 2025: $165

• Jul 2025: $45

• Aug 2025: $167

• Sep 2025: $157

• Oct 2025: $154

The series shows a stable corridor between $140 and $177, with April and May peaking as higher-average-order-value months, and a one‑off trough in July that warrants root‑cause analysis. Use this view to time campaigns that increase aov and to plan free gifts or volume discounts when order value normally softens.

Bar chart available in the workspace: Global AOV by Month (Nov 2024 – Oct 2025).

Benchmarks that matter

Benchmarks are context, not targets. Use them to calibrate expectations by category, geography, and device.

By industry

Over the past twelve months, Luxury & Jewelry recorded the highest average order values at $328, while Beauty & Personal Care averaged $67. In October, Consumer Goods fell to $296, a 2% decline from September.

Pricing strategies and bundles differ by vertical. For high‑ticket categories, cross-selling add‑ons and protection plans can lift the order value without heavy discounting. For lower‑ticket beauty assortments, free shipping thresholds and curated sets often move the needle more than single‑item markdowns.

By region

Regional differences are persistent. Americas $183, APAC $135, EMEA $128.

Set free shipping threshold levels by region rather than a single global rule. Customers tend to respond to thresholds that sit just above the typical basket in their market. This encourages customers to add the next best item, but it should not force them into a minimum purchase behavior that feels artificial.

By device

Device choice maps to intent and screen real estate. Desktop: $192, Tablet: $139, Mobile: $133.

Mobile sessions convert at scale, but product pages on small screens must surface bundles and cross-selling without friction. Desktop traffic can support richer comparison blocks and post‑purchase upsells that increase aov.

Notable swings and what likely drove them

Two sharp moves stand out in October:

Pet Care & Veterinary Services fell 14% from $76 to $66, and Luxury & Jewelry fell 40% from $378 to $253.

Short windows rarely justify sweeping business decisions, yet they are useful tripwires. Review pricing strategy, marketing strategies, and merchandising changes around those dates. Check whether changes to free shipping, other incentives, or bundling coincided with the drop. 

Examine order frequency and repeat purchase patterns among existing customers to determine whether a cohort effect is at play.

Acting on AOV without hurting profit

Below are operator‑level moves that increase revenue while protecting the unit economics.

Design smart thresholds

Use free shipping thresholds that sit 10–20% above the typical order value. This encourages customers to add one more item, increases total revenue, and prevents margin erosion. Free shipping still works, but be explicit about the fine print and exclusions.

Merchandise for attachment

Cross-selling should feel natural. Cross-sell complementary products on product pages and in cart, using purchase history signals rather than broad rules. Customers spend more when recommendations align with their intent. Imitate what repeat buyers choose next and what products customers commonly pair.

Nudge with programs, not one‑off promos

Loyalty programs, especially well‑structured ones, reward behaviors that lead to repeat purchases. Over time, customer loyalty improves customer lifetime value by increasing the average order amount and the number of orders per customer.

Price with intent

Dynamic pricing can move inventory while maintaining perceived value. Align pricing strategies with seasonality and stock position. Use offering discounts sparingly, and reserve volume discounts for bundles where the margin can support them.

Measure like a finance partner.

Avoid chasing a higher average order value at the expense of conversion rate. Track profit margins and the revenue generated by each tactic. When you calculate aov, also monitor the customer base segments affected and whether customers spend more only when incentives are present.

Closing remarks on the average order volume in eCommerce

Order value is not a contest to push baskets ever higher. It is a lever to align pricing, merchandising, and experience with how people actually buy. The data shows predictable spread by category and region, modest device gaps, and a few useful jolts that tell you where to look.

Treat AOV as an operator’s dashboard: calibrate thresholds by market, make cross-selling feel obvious, keep discounts purposeful, and let loyalty do the compounding. When teams run that playbook, the average order grows in a way that strengthens the business rather than stretching it.