Returns Optimization and the Connected Post-Purchase Experience: A New Profitability Frontier for Australian Retailers

In the rapidly evolving landscape of Australian retail, the post-purchase experience—especially returns management—has emerged as a critical, yet often under-leveraged, lever for profitability and customer loyalty. As e-commerce continues to grow and omnichannel expectations rise, Australian retailers face mounting pressure to transform returns from a cost center into a strategic advantage. By harnessing data, artificial intelligence (AI), and integrated omnichannel strategies, retailers can optimize returns, reduce operational costs, enhance customer satisfaction, and unlock new sources of value.

The Returns Challenge: Why It Matters More Than Ever

Returns are a defining feature of modern retail, particularly in categories like apparel, electronics, and homewares. For many consumers, flexible and hassle-free returns are a prerequisite for purchase confidence—especially when shopping online. However, the operational and financial burden of returns is significant:

Profitability Pressure: Over half of Australian retail decision-makers report that e-commerce is less profitable than in-store business, with 52% saying their e-commerce operations are not currently profitable. Returns are a major contributor to this gap.
Customer Experience Impact: Nearly half of consumers cite easy returns as a key factor in choosing where to shop online. Yet, only 45% are satisfied with the online returns process, and 62% are dissatisfied with their ability to try on or try out products virtually.
Operational Complexity: Returns create challenges across the supply chain, from reverse logistics and inventory management to restocking and resale. Inefficient returns processes can erode margins and damage brand reputation.

The Opportunity: Data, AI, and Omnichannel Integration

Forward-thinking Australian retailers are reimagining returns as a connected, data-driven experience that benefits both the business and the customer. The most successful strategies share several key elements:

1. Predictive Analytics for Return Likelihood

By leveraging AI and advanced analytics, retailers can predict which products, customers, or transactions are most likely to result in a return. This enables proactive interventions, such as:

Enhanced Product Information: Providing detailed sizing guides, user reviews, and virtual try-on tools to boost purchase confidence and reduce bracketing (buying multiple sizes with the intent to return).
Personalized Recommendations: Using customer data to suggest the right product or size, minimizing the risk of returns.
Segmented Marketing: Suppressing or tailoring marketing efforts for high-return-risk segments or products.

2. Incentivizing In-Store Returns

Encouraging customers to return online purchases in-store delivers multiple benefits:

Lower Reverse Logistics Costs: In-store returns eliminate shipping and handling expenses associated with mail-in returns.
Increased Repurchase Rates: Associates can assist customers in finding the right replacement, turning a return into a new sale.
Enhanced Customer Engagement: In-store experiences provide opportunities for personalized service, loyalty program engagement, and upselling.

Retailers can drive in-store returns by offering exclusive incentives—such as instant refunds, bonus loyalty points, or personalized offers—when customers choose this option.

3. Dynamic Routing and Supply Chain Optimization

Returns optimization is not just about customer touchpoints; it’s also a supply chain imperative. Leading retailers are:

Using AI to Route Returns: Dynamically directing returned items to the optimal location—whether a local store, regional warehouse, or direct-to-resale channel—based on real-time inventory needs and demand forecasts.
Accelerating Speed to Resale: Improving inventory visibility and process automation to quickly restock returned items, maximizing margin recovery.
Reducing Waste: Leveraging data to minimize unnecessary transportation and packaging, supporting sustainability goals.

4. Returns Data as a Source of Insight

Every return is a data point. By systematically analyzing returns data, retailers can:

Identify Product Issues: Spot patterns in returns by SKU, supplier, or category to address quality or fit problems at the source.
Inform Merchandising and Inventory Decisions: Use returns trends to refine assortment planning, demand forecasting, and inventory allocation.
Enhance Customer Segmentation: Understand which customer segments are most likely to return and why, enabling more targeted engagement and risk management.

Best Practices: Building a Connected Post-Purchase Experience

To fully realize the profitability and loyalty potential of returns optimization, Australian retailers should embrace a holistic, omnichannel approach:

Unified Data Platforms: Integrate returns data across online and offline channels, supply chain, and customer service to enable real-time insights and seamless experiences.
AI-Driven Personalization: Deploy AI to tailor post-purchase communications, recommend optimal return methods, and proactively address customer concerns.
Frictionless Returns Journeys: Offer clear, flexible return options—such as buy online, return in store (BORIS), digital return labels, and instant refunds—while balancing cost and customer impact.
Empowered Store Associates: Equip in-store teams with digital tools and training to manage returns efficiently, provide personalized service, and capture repurchase opportunities.
Sustainability Integration: Use returns data to support circular economy initiatives, such as resale, refurbishment, or recycling, aligning with growing consumer demand for ethical and eco-friendly practices.

The Publicis Sapient Advantage: Transforming Returns into a Profit Center

Publicis Sapient partners with leading Australian retailers to design and implement end-to-end returns optimization strategies. Our SPEED capabilities—Strategy, Product, Experience, Engineering, and Data & AI—enable us to:

Build unified data and analytics platforms for real-time returns visibility
Deploy AI and machine learning to predict, prevent, and optimize returns
Integrate omnichannel solutions that connect digital and physical touchpoints
Modernize supply chain and reverse logistics for speed and efficiency
Design customer-centric post-purchase journeys that drive loyalty and lifetime value

The Path Forward

Returns optimization is no longer a back-office concern—it is a new frontier for profitability, customer experience, and brand differentiation in Australian retail. By embracing data, AI, and omnichannel integration, retailers can transform returns from a pain point into a powerful driver of growth and loyalty.

Ready to unlock the next wave of value in your post-purchase experience? Connect with Publicis Sapient’s retail experts to start your journey toward a more profitable, customer-centric future.