Term: Average Order Value
Definition: Average Order Value (AOV) is a performance metric that measures the average total of every order placed with a company over a defined period.
Alternative Names: Mean Order Value, Average Purchase Value
Expanded explanation: Average order value is an e-commerce term that helps businesses understand their customers’ purchasing habits. This metric is often used to analyse and benchmark the effectiveness of sales and marketing strategies. It is calculated by dividing the total revenue by the number of orders.
Benefits or Importance: Average order value is critical for understanding customer behaviour and profitability. By improving AOV, companies can increase revenue without needing to attract new customers. It can also help with forecasting revenue, managing inventories and setting sales targets.
Common misconceptions or pitfalls: One common misconception is that increasing the number of customers will automatically increase the AOV. However, AOV is independent of the number of customers and is more related to the behaviour and buying patterns of the existing customers.
Use cases: Businesses might use their mean average order value to set goals and measure the success of marketing campaigns. For example, an e-commerce store might introduce a free shipping threshold that’s slightly higher than their current AOV to increase the amount customers spend per order.
Real-world examples: Amazon utilises the technique of upselling and cross-selling to increase their AOV. When a customer adds a product to their basket, Amazon suggests related products that other customers have bought together with the chosen item. This strategy encourages customers to spend more in a single transaction, thus increasing the AOV.
Calculation or formula: The formula for AOV is quite straightforward:
For example, if an e-commerce store generated £10,000 in revenue from 200 orders in a month, the AOV for that month would be:
Best practices or tips:
- Offer product bundles or sets that cost less than the total cost of individual items.
- Provide incentives, such as free shipping or discounts, for orders above a certain value.
- Upsell and cross-sell products by recommending complementary items or upgrades.
- Monitor AOV regularly and adjust your marketing strategy as needed.
Limitations or considerations: While improving AOV is beneficial, it’s important to do so in a way that doesn’t pressure customers or deter them from making future purchases. Also, businesses should not inflate prices unreasonably to increase the AOV, as this can lead to a loss of trust and potentially decreased sales in the long run.
Comparisons: Average Order Value is often compared with Customer Lifetime Value (CLV). While AOV focuses on the value of individual transactions, CLV considers the total value a customer brings to your business over the entirety of their relationship with you. Both are important metrics but serve different purposes.
Historical context or development: AOV is a fundamental metric in commerce and has been used since the inception of retail businesses. With the growth of online retail, its importance has only increased, as businesses have access to more detailed data about customer purchases.
Resources for further learning:
- Shopify: 11 Ways to Increase Your Average Order Value
- Geckoboard: Average Order Value
- Databox: 12 Effective Ways for Increasing Your Average Order Value (AOV)
Related services: At our agency, we offer the following services that can help increase your AOV:
- E-commerce Optimisation – Ask us to help optimise your website to maximise its e-commerce potential.
- Data Analytics – Discover why Bird Marketing is so trusted to interpret data analytics professionally.
- Digital Marketing – Gain greater outreach and market share with a host of online marketing techniques.
We specialise in using data to drive decisions and implement strategies that lead to improved AOV and overall business growth. Contact us to learn how we can tailor our services to your business needs.
Related terms: Upselling, Cross-selling, E-commerce Metrics, Customer Lifetime Value, Conversion Rate
