Average Order Value (AOV) is simply defined as your total revenue divided by total number of orders. While calculating this figure for your online e-commerce store is easy, what you do with the information provided by this figure and how you choose to improve it are what defines your D2C brand's ability to survive an ever-changing market.
This figure is critical and helps businesses understand and influence customer purchasing behavior. Increasing AOV boosts profitability without the added cost of acquiring new customers, making it one of the most efficient growth levers.
In our guide, we're going to cover every aspect of AOV and how you can (and should) improve it to continuously scale your D2C Business.
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You're going to want to write this down: total revenue ÷ total number of orders = AOV
The result of this formula is a key performance indicator in e-commerce, allowing you to understand your target audience's behaviors to drive your overarching multi-funnel strategy.
A quick example:
If your total revenue in Q3 was $25,000 and there were a total of 450 orders made by customers you get:
AOV = $25,000 ÷ 450 = $55.56
This figure is revenue per order, and not revenue per customer. This is because a customer can place multiple orders of the same or different sizes; each order is what matters in this equation — it doesn't matter where the orders came from.
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Average Order Value (AOV) serves as a crucial benchmark for understanding customer behavior, revealing whether buyers tend to make smaller or larger purchases. This insight directly informs key business decisions, from setting effective pricing strategies and allocating marketing spend to designing product bundles and promotional offers that resonate with different customer segments.
Beyond guiding strategy, AOV plays a vital role in profitability because higher order values help offset transaction costs, allowing businesses to capture more revenue and improve margins without relying solely on new customer acquisition.
If you're able to effectively segment customers by using first-party data and personalize offers geared towards what your target audience is looking for, you can tailor strategies that will inevitably maximize Average Order Value and build effective long-term loyalty.
If you're able to effectively dial in your Average Order Value, don't neglect combining this figure with other tracking metrics. When you add additional KPIs into the mix, you paint a complete, holistic picture of your performance, what strategies are working where, and what options you have for increasing performance further.
You can add these all to an e-commerce tracking dashboard to show stakeholders, management, or a team member. Also, Average Selling Price (ASP), Average Revenue per User (ARPU), and Gross Merchandise Value (GMV) provide benchmarks for comparing growth across different business types and industries, with ASP showing the typical price per product sold, ARPU reflecting the average revenue generated per customer, and GMV capturing the total value of all sales on a platform.
For e-commerce businesses, Average Order Value is immensely important for acting as a litmus test for the growth, capabilities, and viability of your business model. While AOV is utilized across a multitude of industries, e-commerce is the most common application as businesses optimize checkout flows and upsell experiences for their target audience.
If you want a quick cheat-sheet for enhancing AOV you can boost AOV by bundling complementary products, offering add-ons like extended warranties or accessories, and suggesting digital extras such as e-books or guides to raise transaction sizes. An even easier cheat-sheet? Borrow strategies from massive (and successful) e-commerce players like eBay and Amazon and emulate what they're doing in the online marketplace.
When you work to calculate, track, enhance, and refine your AOV, you set yourself up for success now and into the future of your online growth.
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As the first platform to enrich shopper contact and demographic data in real-time, Tie empowers B2C marketers to de-anonymize visitors, and personalize every touchpoint—from website to email—using attributes like age, gender, marital status and more.