Australian E-commerce Stores Reducing Return Rates by 18% with AI
AI workflows to predict returns
Mirai Team
July 3, 2026
Australian e-commerce stores are leveraging Artificial Intelligence (AI) to reduce return rates by an impressive 18% on average. This significant reduction is attributed to the implementation of AI-powered workflows that predict and prevent returns. By analyzing customer data, order history, and product information, AI algorithms can identify potential return risks and enable e-commerce businesses to take proactive measures. For instance, online retailers can use Machine Learning (ML) models to detect anomalies in customer behavior, such as unusual purchase patterns or mismatched product orders.
Reducing Return Rates with Predictive Analytics
Predictive analytics is a crucial component of AI automation in e-commerce, enabling businesses to forecast return probabilities and take preventative actions. By integrating predictive models into their workflows, online retailers can identify high-risk orders and intervene early to prevent returns. For example, an e-commerce store selling clothing and apparel can use predictive analytics to identify customers who are likely to return items due to sizing issues. The store can then proactively offer size recommendations or provide detailed sizing charts to reducing the likelihood of returns.
Real-World Example: Online Fashion Retailer
A prominent Australian online fashion retailer, The Iconic, implemented an AI-powered return prediction system to reduce its return rates. By analyzing customer data, including purchase history, browsing behavior, and product reviews, the system identified high-risk orders and flagged them for intervention. The Iconic’s customer service team would then contact the customers to confirm their orders, provide sizing recommendations, and offer personalized styling advice. As a result, The Iconic saw a significant reduction in return rates, with an estimated 22% decrease in returns over a six-month period.
The cost savings from reducing return rates can be substantial. According to a study by the National Retail Federation, the average cost of processing a return is around $10.30 per item. For an e-commerce store processing thousands of returns per month, the cost savings from reducing return rates by 18% can add up quickly. By implementing AI-powered workflows, online retailers can minimize the financial impact of returns and allocate resources more efficiently.
Implementing AI-Powered Workflows
To implement AI-powered workflows for reducing return rates, e-commerce businesses can follow a few key steps. First, they need to integrate their data sources, including customer data, order history, and product information, into a single platform. This will provide a unified view of their data and enable AI algorithms to analyze and identify patterns. Next, they need to develop predictive models that can forecast return probabilities and identify high-risk orders. Finally, they need to automate their workflows to intervene early and prevent returns.
Key Benefits of AI Automation
The benefits of AI automation in e-commerce extend beyond reducing return rates. By automating routine tasks and workflows, online retailers can improve operational efficiency, enhance customer experiences, and gain a competitive edge. For example, chatbots powered by Natural Language Processing (NLP) can provide 24/7 customer support, answering frequent questions and resolving minor issues. Meanwhile, AI-powered recommendation engines can suggest personalized products and offers, increasing average order values and customer loyalty.
To achieve these benefits, e-commerce businesses need to invest in AI technology and develop the necessary skills to implement and manage AI-powered workflows. This may involve hiring data scientists and AI engineers or partnering with AI solution providers. By taking a strategic approach to AI adoption, online retailers can stay ahead of the competition and thrive in a rapidly evolving e-commerce landscape.
In the Australian e-commerce market, the opportunities for AI adoption are vast. With the e-commerce industry projected to reach $32.3 billion by 2025, online retailers that invest in AI technology can gain a significant competitive advantage. By reducing return rates, improving operational efficiency, and enhancing customer experiences, AI-powered workflows can help e-commerce businesses achieve sustainable growth and success.
To get started with AI-powered workflows, e-commerce businesses can take the following next steps:
- Assess their current data infrastructure and identify opportunities for integration and automation
- Develop a strategic plan for AI adoption, including investments in technology and talent
- Explore AI solution providers and partners that can help them implement and manage AI-powered workflows
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.