Previously Easycom, now Inretrn

Achieving profitability in E-commerce returns

In today’s dynamic world of e-commerce, returns have become as common as sales, necessitating a fresh perspective on profitability. Welcome to the realm of reconverting returns, where we uncover the secrets to maximizing your Return on Returns (ROR). In this article will explore the concepts of “profitable returns” and “return on returns,” providing insights on how to gain the upper hand.

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The path to automated profitability

In this fast-paced era of commerce, we are inundated with data. The sheer volume of information can be overwhelming, making it impractical to manually make countless decisions aimed at maximizing profitability in every transaction. Our solution lies in automation. Algorithms and automated processes can efficiently guide these decisions. However, before fully embracing automation, it is crucial to ensure the quality and completeness of our data.

Selecting the right data for customer segmentation

The initial question in customer segmentation revolves around data selection. Should we rely on transactional data or opt for behavior-generated 360-degree data? While debates abound on this topic, one crucial aspect often goes overlooked: the purpose behind these customer segments.

When enhancing your website, optimizing customer journeys, increasing conversion rates, and automating marketing efforts, behavioral patterns are undoubtedly valuable. However, when your aim is to provide the right offers to the right customers for revenue and profitability, things get complex. We argue that understanding your transactional data thoroughly to identify the purchasing patterns that drive profitability should be the foundation. Afterward, refine this analysis with other metrics, such as behavior mapping on the site. Reversing this order can lead to severe negative consequences from a profitability perspective, and here’s why.

The evolution of customer segmentation models

Let’s step back and examine the models underpinning customer clubs, VIP offers, discounts, and more. The most prevalent model is RFM (Recency, Frequency, Monetary), with variations. Some use LFV (LiFetime Value) models, but their effectiveness in sales and marketing raises concerns. These models are better suited for slow-moving, long-term customer relationships with predictable purchase intervals, a far cry from today’s e-commerce and fashion landscape.

RFM originated before e-commerce and was primarily employed by traditional retailers. The challenge lies in the “Monetary” parameter, typically equating to revenue per customer. While this metric held true in traditional retail, it falls short in e-commerce, especially in the fashion industry. Additional factors, such as operational and logistical costs, now play a pivotal role, substantially impacting profitability. These costs vary based on return rates, and high revenue no longer guarantees high profitability due to these added expenses.

Introducing “true profitability” segmentation

So, what’s the ideal method for segmenting customers to drive revenue and profitability? The answer lies in “profitability,” specifically, “true profitability.” This concept unveils your actual net profit per customer, accounting for all operational and logistical costs tied to new purchases, returns, and exchanges in the modern retail landscape. While 360-degree analyses and qualitative mapping of customer journeys have their merits, “true profitability” takes center stage, as it generates tangible value for your company, sustains your workforce, and ensures long-term well-being.

Summarizing the approach

In summary, we present three essential takeaways for customer segmentation in e-commerce:

  • Always align your chosen segmentation method with your intended purpose.
  • Begin by ensuring the quality of transactional data, encompassing the entire purchase, return, and exchange journey.
  • Gradually integrate more qualitative elements, with each addition directly linked to its intended use.
Conclusion

In conclusion, our journey through customer segmentation in the e-commerce landscape emphasizes the significance of “true profitability.” While there are numerous areas where “true profitability” algorithms can elevate your bottom line, it’s vital to acknowledge that not everything comes without cost. Nevertheless, we hope that our collective knowledge will contribute to the flourishing of the new commerce era, benefiting suppliers, e-commerce businesses, distributors, and customers alike.