Inventory is a fine balance of art and science. It takes smart planning to achieve optimal inventory levels, yet many retailers find themselves struggling. The advent of online and its subsequent growth have made returns a necessary cost that is increasing. But this cost can be mitigated through better demand forecasting and more dynamic pricing. Moreover, customers returning purchases are an additional touchpoint – a very real opportunity to further engage and create value. The question is how do you optimise your returns process to unlock these benefits?
Create a returns strategy for retail
Accurate and timely visibility of inventory and its movement is vital. Customer returns are expensive to manage and pose a logistical nightmare for businesses, and these challenges are only continuing to grow. Despite this, most retailers still don't have an effective returns strategy in place. Online’s share of sales varies across developed economies, and its rate of growth will also vary. But the overall trend is upward. Returns in each retail sector are very different, but in apparel, return rates range between 30-40% - some higher dependent on category and price point. Customers will frequently buy several of an item (colour, size, etc.) and if the retailer is lucky, they will keep one while returning the rest. As online share grows, this percentage will rise, eroding even more margin. To prevent this, retailers must take a proactive approach to incorporate returns into the overall planning process. Integrating your planning processes and systems creates opportunities that may not be as obvious while planning and strategy teams operate in silos.
Understand returns through data analysis
After years of online development, there has been a widespread acceptance that returns are simply a cost that must be borne. Today, a growing number of retailers charge customers, and this may eventually be the norm. However, few have tried to mitigate the costs by deploying data science to better understand the process and manage it optimally.
Returns have a significant impact on the bottom line. Research shows that even a 5% reduction in return rate on an item can double the profitability (before income and taxes) for an online retailer. Having centralised visibility is the first step towards taking control of returns, increasing profitability, and improving ways of working. Integrated planning offers great potential for managing the returns process and harnessing data science capability.
Making investments in data science and machine learning can enable smarter decisions in critical areas like assortment, flow, pricing, and timing, and materially improve cash flow.
Personalise the returns process
Another opportunity lies within consumer data. How can retailers improve the returns experience for customers? Personalisation is useful especially since customers who return the most product tend to be the most loyal, making the most purchases. There is an opportunity to analyse this customer base, working to mitigate return costs by better understanding the process from the customer's point of view.
Integrating returns insights into your reporting should be an essential part of better demand management.
Online retailing is growing its share – the only way is up. And being part of that growth is a strategic attraction. However, making good margins from online retailing is challenging. Returns are a threat to that profitability. This is why investment in optimising returns management represents a significant opportunity to transform your trading economics and improve your margins.
Considering optimising your retail returns process with an integrated planning approach?
We can assist with selecting and implementing an innovative data science-led approach. Every client engagement we work on involves adding value and insight to optimise the management of retail businesses.
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