Use returns analytics to enhance post-purchase experiences BEFORE customers check out.
In the past, the retail “finish line” was making the sale. Retailers had to understand what customers wanted and/or needed, carefully curate a product assortment, and develop a seamless shopping experience that steered customers toward that final checkout. Today, that finish line isn’t as clear.
While initial sales are essential, we know the post-purchase experience is vital to customer loyalty. When customers have positive return experiences, they’re more likely to shop again. That means a higher customer lifetime value and greater net revenue.
One thing remains the same, though. Promoting initial sales and improving the post-purchase experience requires work BEFORE customers enter a store or visit a website. Fortunately, returns analytics can help with both.
Read on and learn how to use returns analytics to enhance the post-purchase experience for happier customers and greater net revenue.
Use Returns Analytics to Develop a Customer-Centric Return Policy
Return policies are vital to the post-purchase experience, and they should always implement several key items. For example, they should be easy for customers to understand and locate. Additionally, whether they’re shopping in-store or online, it’s important to ensure the customer is presented with policy information at the point of sale.
However, none of that matters without a return policy that makes sense for the products, your business, and—most importantly—your customers. That’s why it's so important to continuously evaluate returns analytics, customer feedback, and industry trends.
Assessing specific KPIs, from return rates and length of returns to profitability and cost per return, can measure a policy's effectiveness. It can also help retailers make data-informed changes designed to create more positive customer experiences.
InsightFinderAi can quickly analyze the necessary information and generate insights about your return policy. For example, it could detect an operations issue involving a certain product type. If the product regularly runs into logistics issues due to its size or weight, this could add time to the return transaction, and customers could become frustrated.
In this instance, InsightFinderAi may recommend a no-return policy for certain products to avoid these negative experiences altogether. Conversely, it may recommend adding additional information to manage customer expectations.
Develop Policies That Reward Loyal Customers Post-Purchase
In the recent webinar Retail Returns: The Hidden Driver of Loyalty, Optoro VP of Customer Success Zach Kramer explained that the best customers are often the most frequent returners. He added, “that 95 percent of customers are less likely to shop at a retailer again if they have a poor returns experience…. So, returns should be viewed as an opportunity to delight your best customers.”
Determining who those loyal customers are, however, can be tricky. Depending on the return transactions, a customer who makes many purchases may still be less valuable over time compared to others.
Returns analytics can not only help differentiate between extremely loyal, potentially loyal, and first-time shoppers but also help you develop post-purchase policies that promote and reward loyal customer behaviors.
For example, a loyal customer who is highly unprofitable should be managed differently than a loyal and profitable customer. InsightFinderAi may recommend return policies that can be customized to segments within loyalty tiers. This can deter behaviors like returns abuse while offering valuable benefits to loyal customers, such as free returns, longer return windows, etc.
Use Customer Feedback to Reduce Unwanted Returns and Improve Post-Purchase Experiences
For specific information about your customer’s post-purchase experiences, start with their feedback. Whether in the form of reviews, testimonials, or ratings, customer feedback provides valuable information that can help improve products, enhance customer experiences, and reduce unwanted returns.
Acceptable returns are those that happen because a customer changes their mind or they don’t like a product. It happens, and if returning the product is the only way to guarantee their satisfaction, then that’s the best course of action. Whether or not that transaction can become an exchange, the interaction is still an opportunity to create a positive post-purchase experience.
Unwanted returns, on the other hand, should be minimized or eliminated entirely to reduce damage to loyalty and brand reputation, as well as minimize revenue losses. These can be damaged products, shipping issues, inaccurate product info, etc. Whatever the case, some of the largest customer signals regarding these issues can be found in customer feedback.
Many negative reviews regarding the same issue could mean a problem needs to be addressed. For example, if many reviews discuss how a piece of furniture arrived damaged, it may be beneficial to assess shipping carriers or packaging designs. In this scenario, ignoring negative reviews means risking additional negative customer experiences.
InsightFinderAi can cross-reference returns analytics with unstructured customer feedback to identify specific issues and develop an action plan. That means fewer negative customer experiences, fewer unwanted returns, and increased revenue.
Partner with Returnalyze for Data-Informed Post-Purchase Strategies
In reality, this is just the tip of the iceberg. Every business is different, and enhancing your post-purchase experience may involve adding detailed sizing information, creating personalized post-purchase marketing materials, etc. Fortunately, your returns data can help.
Returns analytics contains a wealth of untapped information, and InsightFinderAi makes it easier than ever to harness that data to improve your customers’ post-purchase experiences. Plus, with its recommendations, businesses can easily take corrective action that increases revenue.
In addition to the insights and recommendations from InsightFinderAi, a partnership with Returnalyze comes with step-by-step guidance from our data experts. We know how important it is to have an expert in your corner when you need it.
Ready to improve your post-purchase experience? Schedule a demo or contact our team today.
