Successfully growing your ecommerce retail business can’t happen without paying attention to your customer lifetime value. This vital metric measures the value of a customer over the course of their entire relationship with a company.

In other words, it’s the amount of money a customer is expected to spend on a company’s products or services over their lifetime. However, understanding what customer lifetime value (CLV) is is a lot easier than actually attempting to measure it.

Using your returns data helps you measure your CLV more clearly.

Returns data can tell you a lot about your customers and their buying habits. By analyzing your returns data, you gain valuable insights into customer loyalty, reduce customer churn, and identify cross-selling opportunities.

How Returns Improve Customer Loyalty

How a company manages and communicates its return policy significantly impacts customer loyalty. Studies show shoppers are more likely to buy products from retailers who offer a customer-friendly return policy.

Buying online doesn’t come with the same luxuries as shopping at a physical store because the customer doesn’t get the chance to see and feel the product for themselves before they buy. Customers want to feel protected when they’re shopping online in case the product they purchased doesn’t work as expected.

Retailers in certain verticals, like jewelry, eyewear, or the CBD/Vape industries, also often offer warranty programs to further protect purchases in the case of damage. When warranty returns are handled effectively and efficiently, customers feel secure with the retailer, and their loyalty to the brand increases.

While improving customer loyalty with a good return policy and warranty program is great, it doesn’t take away the fact that returns cut down on profits. This can be mitigated by using your returns data to inform insightful decisions that make up the lost profit in other areas of your business.

When using an automated returns management system, you’re able to collect data on every RMA that comes through. This data can be used to discover patterns in product performance, returns reasons, manufacturing errors, etc. It lets you know which areas of your business need more attention, and in turn, creates a better experience for your customers as the business improves.

Additionally, your returns data allows you to segment your customers based off of returns or purchase history. You can then use the returns experience to personalize messaging to each customer to promote a repeat purchase while they’re initiating the return.

Not only will this save the sale, but it also makes the customer feel understood by your brand, which motivates them to shop with you again, ultimately increasing their customer lifetime value.

Overall, analyzing your returns data gives you a better understanding of why customers are leaving and what you can do to keep them.

How to Reduce Customer Churn

The other side of increasing customer lifetime value is decreasing your customer churn rate or the number of customers that completely stop doing business with you. While difficult to measure, it’s an important metric to keep track of as you’re trying to build a relationship with your customers.

Reducing customer churn is a key factor in increasing CLV. One of the main reasons for customer churn is dissatisfaction with a product or service. By analyzing returns data, you can identify the most common reasons for returns and take steps to address those issues.

For example, if customers are returning a product due to a lack of information or unclear instructions, you can improve your product descriptions and provide more detailed instructions. If a particular product is prone to defects, you can address the issue by improving the quality control measures in place during manufacturing.

By improving the customer experience and addressing the root causes of returns, you reduce the likelihood of customers switching to a competitor’s product. Additionally, automated warranty processes make it easier for customers to file claims and receive support, which increases customer satisfaction and reduces churn.

By making the warranty process simple and easy, customers are more likely to stick with your product rather than going through the hassle of returning it and finding a new one. This could be a big differentiator between you and your competitors.

Furthermore, analyzing returns data helps you identify patterns and trends in customer behavior. This helps build better product development, marketing and sales strategies. If you notice that a particular product has a high rate of returns, for example, you can adjust your marketing efforts to target a different audience or consider discontinuing the product altogether.

The decisions are ultimately yours to make, but the insights help to make the choice more clear.

Using your returns data to improve your business in any of these ways shows your customers the extra effort you’re putting into your relationship with them. That doesn’t go unnoticed, and it makes it a lot harder to switch to one of your competitors.

Opportunities to Cross-Sell

Automated returns and warranty messaging create opportunities for upselling and cross-selling. When customers initiate a return, they are already engaged with your brand, which makes it a great time to offer them additional products or services that complement what they have already purchased.

Imagine a customer is returning a camera due to a malfunction. This gives you the opportunity to offer the customer a replacement camera with additional features or a bundle that includes accessories, such as lenses or a camera bag.

At the very least, an interested customer will flip through the product description, which gives exposure to more of your products that they might not have known you were selling. In the best-case scenario, the customer will take you up on your offer and turn what would’ve been a returned product into a bigger purchase.

By using data analytics and customer profiling, businesses can send personalized recommendations based on a customer’s purchase history and preferences.

These additional purchases have a direct effect on calculating CLV. By increasing the amount of money a customer spends with your company, you’re increasing their lifetime value. And by suggesting products to shoppers that you know they’re interested in, you’re increasing their loyalty.

Furthermore, cross-selling and upselling can be automated, making the process more efficient and streamlined. By using data analytics and customer profiling, businesses can send personalized recommendations based on a customer’s purchase history and preferences. The chances of making a sale improve and the customer’s overall satisfaction with your brand increases.

Automated messaging provides a unique opportunity for businesses that, when taken advantage of, could increase their CLV and improve the overall customer experience.

Increase Customer Lifetime Value with ReturnLogic

Returns data can tell you a lot about your customers and their buying habits. Analyzing this data helps you gain valuable insights into customer loyalty, reduce customer churn, and identify cross-selling opportunities.

All of these initiatives will increase your customer lifetime value and grow your business.

To get started on gaining valuable insights from your returns data, book a demo with us today!

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