Shopify Returns Data: Real-World Examples Ecommerce Managers Can Learn From

Have you ever felt like you're staring into a data abyss when trying to understand your Shopify store's returns? You're not alone. Many eCommerce managers struggle to get a clear picture of their returns, exchanges, and the overall impact on their bottom line. The lack of clarity makes it difficult to make data-driven decisions that could significantly improve customer satisfaction and profitability. This guide will explore real-world examples and actionable strategies to help you navigate the complexities of Shopify returns analytics.

Why Understanding Returns Data Matters

Returns are an unavoidable part of the eCommerce landscape. But they don't have to be a source of frustration. When you understand your returns data, you can identify the root causes of returns, improve your product offerings, and optimize your customer experience. This leads to increased customer loyalty and a more profitable business. But how can you analyze your data? Let's look at some eye-opening statistics:

• Approximately 30% of all products ordered online are returned, compared to 8.89% in brick-and-mortar stores. Invesp
• Returns cost US retailers $816 billion in lost sales in 2022. National Retail Federation
• Nearly 70% of consumers check the returns policy before making a purchase. Statista
• The average return rate for online apparel is 20-30%. Marketing Dive

Key Takeaway: Returns aren't just about lost revenue; they're a critical indicator of customer satisfaction, product quality, and the overall shopping experience. Analyzing this data enables you to provide a better shopping experience.

Example #1: The Mystery of the Unclear Return Reason

Imagine you're an eCommerce manager for a Shopify store selling handmade jewelry. You notice a surge in returns, but Shopify's basic analytics don't provide much detail beyond the fact that items are being returned. You're left guessing about the reasons behind the returns. This is a common pain point, highlighted in a Reddit thread where a user asked, "Does Shopify separate exchanges out from 'returns' in the analytics? Or is the 'returns' amount all returns regardless if some were exchanges?" Reddit

The Problem: Lack of granular data on return reasons and whether a return is an exchange or a true return.

The Impact: Inability to pinpoint the root causes of returns, leading to wasted resources and potential customer dissatisfaction.

The Solution:

• Implement a Detailed Returns Form: Integrate a returns form that requires customers to select a specific reason for the return (e.g., "Wrong size," "Defective," "Doesn't match description," etc.).
• Track Exchanges Separately: Manually track exchanges or use a Shopify app designed for this purpose to distinguish them from standard returns.
• Analyze the Data: Regularly review the data from the returns form and exchange tracking to identify patterns and trends. For instance, if "Wrong size" is a common reason, you might need to improve your size charts or product descriptions.

Example #2: The Cost of Shipping and Returns

Let's consider an eCommerce business selling electronics. High shipping costs and return shipping are significantly impacting your profitability. You analyze your Shopify data and discover that a large percentage of returns are due to customers being unhappy with the shipping fees. This problem is exacerbated by the lack of clear data on return shipping costs.

The Problem: High shipping costs and lack of transparency, leading to customer dissatisfaction and increased returns.

The Impact: Reduced profit margins and a negative impact on customer lifetime value.

The Solution:

• Offer Free or Discounted Shipping: Consider offering free shipping on orders over a certain amount or discounted return shipping. This has been shown to be effective, with 66% of consumers citing free shipping as a key factor when making a purchase. Pitney Bowes
• Optimize Shipping Options: Provide a range of shipping options (e.g., standard, express) to give customers more control and potentially reduce returns related to shipping costs.
• Transparent Shipping Policies: Clearly communicate shipping costs, return shipping costs, and return policies on your product pages and during checkout.

Example #3: Identifying Product Quality Issues

An eCommerce store selling home goods experiences a sudden spike in returns. A deep dive into the Shopify data reveals that a significant number of returns are due to product defects. This indicates a problem with the quality control process or the product itself.

The Problem: Product defects leading to returns and dissatisfied customers.

The Impact: Damaged brand reputation and lost sales.

The Solution:

• Enhanced Quality Control: Implement a more rigorous quality control process, including thorough inspections before products are shipped.
• Review Supplier Relationships: Evaluate your relationships with your suppliers to ensure they meet your quality standards.
• Improve Product Descriptions: Provide accurate and detailed product descriptions, including high-quality images and videos, to minimize returns related to unmet expectations.

Pro Tip: Integrating a customer feedback system can help you gauge customer satisfaction and understand the reasons behind returns. This data can be invaluable in identifying areas for improvement in your products and processes.

Common Patterns in Returns and Exchanges

Analyzing returns data often reveals common patterns. Here are a few to watch out for:

• Seasonal Fluctuations: Returns often spike after holidays or during peak shopping seasons. This can be due to gift returns, increased order volumes, and less careful purchasing decisions.
• Product-Specific Issues: Certain products may have higher return rates than others. This could be due to quality issues, sizing problems, or inaccurate product descriptions.
• Customer Behavior: Some customers may return products more frequently than others. This could indicate a need to adjust your return policies or identify potential fraud.

Warning: Be mindful of returns fraud. Implement measures to protect your business, such as verifying returns and monitoring for suspicious activity.

How to Apply This: Actionable Takeaways for eCommerce Managers

Implementing these strategies will require your eCommerce store to take action. Here are the key takeaways:

1. Enhance Your Shopify Analytics: While Shopify's built-in analytics provide a starting point, consider using third-party apps or custom integrations to get more granular data on returns and exchanges. These tools can help you track return reasons, shipping costs, and customer behavior related to returns.
2. Optimize Your Returns Process: Make your returns process as easy and customer-friendly as possible. Offer clear instructions, pre-paid return labels, and multiple return options (e.g., in-store returns, mail-in returns).
3. Refine Your Product Listings: Ensure your product descriptions are accurate and detailed, including clear size charts, high-quality images, and videos. This will reduce returns related to unmet expectations.
4. Monitor and Analyze Regularly: Make returns data analysis a regular part of your business operations. Set up a system for tracking returns, analyzing trends, and identifying areas for improvement.
5. Use CRO Benchmark for a Holistic View: Consider using a tool like CRO Benchmark to get a comprehensive understanding of your conversion optimization efforts. CRO Benchmark can help you identify areas where your website might be contributing to returns, such as poor user experience or unclear product information. By addressing these issues, you can improve your overall conversion rate and reduce the likelihood of returns.

By focusing on these areas, you can transform your returns data from a source of frustration into a valuable asset that drives profitability and customer satisfaction.