US E-commerce Businesses Boost Average Order Value by 18% with AI
AI strategies to increase e-commerce average order value
Mirai Team
July 8, 2026
The e-commerce landscape in the US is becoming increasingly competitive, with businesses constantly looking for ways to stay ahead of the curve. One key metric that can make or break an e-commerce company is Average Order Value (AOV). By increasing AOV, businesses can boost revenue without having to acquire new customers, making it an attractive strategy for growth. For instance, a 10% increase in AOV can result in a 10% increase in revenue, assuming all other factors remain constant.
Understanding Average Order Value
AOV is the average amount spent by customers in a single transaction. It’s calculated by dividing total revenue by the number of orders. For example, if an e-commerce business generates $10,000 in revenue from 100 orders, its AOV is $100. Artificial Intelligence (AI) can be leveraged to optimize AOV by analyzing customer behavior, identifying trends, and providing personalized product recommendations.
Strategies for Boosting AOV with AI
One effective way to increase AOV is through upselling and cross-selling. AI can analyze customer purchase history and browsing behavior to suggest complementary products or upgraded versions of items already in their cart. This can be done through personalized product recommendations on the website, email marketing campaigns, or even during the checkout process. According to a study, personalized product recommendations can increase AOV by up to 20%.
A notable example of an e-commerce business that has successfully implemented AI-driven upselling and cross-selling strategies is Sephora. The cosmetics retailer uses AI-powered chatbots to offer personalized product recommendations to customers based on their purchase history and browsing behavior. As a result, Sephora has seen a significant increase in AOV, with customers who interact with the chatbots spending an average of 15% more than those who do not.
AI-Powered Product Bundling
Another AI strategy for increasing AOV is product bundling. By analyzing customer purchase behavior and product relationships, AI can identify opportunities to bundle complementary products together, increasing the average order value. For instance, an e-commerce business selling outdoor gear could use AI to identify customers who have purchased a tent and offer them a bundle deal on a sleeping bag and camping stove. This can result in a higher AOV and increased customer satisfaction.
Real-World Example: Outdoor Gear Retailer
Let’s consider a real-world example of an outdoor gear retailer that has seen success with AI-powered product bundling. The retailer, which sells camping equipment and hiking gear, used AI to analyze customer purchase behavior and identify opportunities to bundle complementary products together. As a result, the retailer was able to increase its AOV by 12% and see a significant increase in customer satisfaction.
Leveraging Customer Data
To effectively implement AI strategies for increasing AOV, e-commerce businesses need to have access to high-quality customer data. This includes data on customer purchase history, browsing behavior, and demographic information. By analyzing this data, AI can identify trends and patterns that can inform personalized product recommendations and product bundling strategies. For example, an e-commerce business could use customer data to identify customers who have abandoned their shopping cart and offer them personalized product recommendations or exclusive discounts to encourage them to complete their purchase.
Some key customer data points that can be used to inform AI strategies for increasing AOV include:
- Purchase history
- Browsing behavior
- Demographic information
- Search queries
- Social media activity
By analyzing these data points, e-commerce businesses can gain a deeper understanding of their customers and develop targeted strategies for increasing AOV.
Actionable Next Steps
To start boosting AOV with AI, e-commerce businesses should take the following concrete next steps:
- Conduct a thorough analysis of customer data to identify trends and patterns that can inform personalized product recommendations and product bundling strategies
- Implement AI-powered upselling and cross-selling strategies, such as personalized product recommendations and product bundling
- Continuously monitor and evaluate the effectiveness of AI strategies and make adjustments as needed to optimize results.
Ready to implement this in your business? Mirai deploys AI automation for SMBs across the US, UK, Canada, and Australia — typically in under a week.
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Written by Mirai Team
The Mirai team builds AI automation systems for Western SMBs. We write about what we're building, what we're learning, and what's actually working.