Australian E-commerce Stores Reduce Returns by 18% with AI
AI tools reduce e-commerce returns
Mirai Team
August 17, 2026
The Australian e-commerce market has experienced rapid growth in recent years, with sales projected to reach $35.2 billion by 2025. However, this growth has also led to an increase in returns, which can be costly for online retailers. According to the National Retail Association, the average return rate for Australian e-commerce stores is around 20%. To mitigate this issue, many Australian e-commerce stores have started using Artificial Intelligence (AI) tools to reduce returns. By leveraging AI, these stores have been able to reduce their return rates by an average of 18%.
The Cost of Returns
Returns can be a significant burden for e-commerce stores, with the average cost of processing a return ranging from $10 to $30. This cost can quickly add up, especially for stores that have high return rates. In addition to the direct cost of processing returns, e-commerce stores also lose out on potential sales when a customer returns an item. By reducing returns, e-commerce stores can increase their revenue and improve their bottom line.
How AI Reduces Returns
AI tools use machine learning algorithms to analyze customer data and predict the likelihood of a return. This analysis takes into account various factors, such as the customer’s purchase history, browsing behavior, and demographic information. By identifying high-risk returns, e-commerce stores can take proactive steps to prevent them. For example, a store may offer a personalized sizing chart to customers who have a history of returning items due to sizing issues.
One Australian e-commerce store that has seen success with AI-powered return reduction is The Iconic. The Iconic is an online fashion retailer that uses AI to analyze customer data and predict returns. By leveraging AI, The Iconic has been able to reduce its return rate by 15%. The store has also seen an increase in customer satisfaction, with customers reporting higher levels of confidence in their purchases.
Practical Applications of AI
AI can be applied to various aspects of the e-commerce experience to reduce returns. Some practical applications of AI include:
- Product recommendations: AI can be used to recommend products that are likely to fit the customer’s needs and preferences.
- Size and fit guidance: AI can be used to provide customers with personalized sizing charts and fit guidance to reduce the likelihood of returns due to sizing issues.
- Customer service chatbots: AI-powered chatbots can be used to provide customers with immediate support and answer questions about products, reducing the likelihood of returns due to misunderstandings.
Case Study: Cotton On
Cotton On is an Australian e-commerce store that has seen significant success with AI-powered return reduction. The store uses AI to analyze customer data and predict returns. By leveraging AI, Cotton On has been able to reduce its return rate by 20%. The store has also seen an increase in customer satisfaction, with customers reporting higher levels of confidence in their purchases. Cotton On’s success with AI-powered return reduction can be attributed to its ability to provide customers with personalized product recommendations and size and fit guidance.
Measuring the Success of AI
To measure the success of AI-powered return reduction, e-commerce stores can track various key performance indicators (KPIs). Some common KPIs used to measure the success of AI-powered return reduction include:
- Return rate: The percentage of orders that are returned.
- Return cost: The total cost of processing returns.
- Customer satisfaction: The level of satisfaction reported by customers. By tracking these KPIs, e-commerce stores can determine the effectiveness of their AI-powered return reduction strategies and make adjustments as needed.
Next Steps
To reduce returns and improve customer satisfaction, Australian e-commerce stores can take the following next steps:
- Implement AI-powered product recommendations to provide customers with personalized product suggestions.
- Use AI-powered size and fit guidance to reduce the likelihood of returns due to sizing issues.
- Integrate AI-powered customer service chatbots to provide customers with immediate support and answer questions about products. By taking these steps, Australian e-commerce stores can reduce their return rates and improve their bottom line.
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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.