Minimize Your Product Returns This Holiday Season
The online sales have been growing consistently for years but is likely to break all records in 2020.
Holiday season means great business opportunity for retailers. It enables them to close the year with strong sales. However, with pandemic-led business disruptions, store closures and the consequential economic downturn, the importance of a profitable holiday season has manifold this year. Various retail outlets have scaled up their eCommerce capabilities while expecting a never seen before response in the online sales for the upcoming season.
Unfortunately, too many returns may dampen their holiday spirit. Returns have been a major concern for retailers even before COVID-19 struck. They see returns worth billions in merchandise each year including around 30% of returns in online sales. And the pressure to offer a generous return policy to compete with online bigwigs doubly hits the retailers by trimming into profits.
Besides, with a greater volume of online purchase and a new rush of customers, including those who are not used to shop online, the potential for returns is even higher this year. So how to control this? Well, a proactive deployment of technology such as AI and predictive analytics can predict key trends and fix the problem before it snowballs. Here's how it can help you:
Analyze historical returns data: AI serves as the much-needed seatbelt as you drive your business online. It saves you from encountering a bad hit in the retail ecosystem. AI capable of analyzing large datasets and multiple SKUs can detect patterns that humans might miss. This can help zero in on products with a higher likelihood of return. Pre-emptive measures can then be taken to prevent a surge in returns. Apparel typically has a higher than the average return rate. Here, AI can help you identify problems such as size disparities among manufactured goods. This information can then be incorporated with product descriptions so that customers are able to make better-informed decisions.
Predict customers with more likeability of returning: Analytics can also reveal which buyers return the most merchandise. Although most returns can be linked to genuine mistakes in understanding while ordering, there are often customers who misuse the retailer’s supportive and easy-return policies. Amazon has banned many customers for generating too many returns, however, the exact purchase-to-return ratio to impose a ban is unknown. Here, AI-driven data analysis can provide a heads-up so you can proactively address such problems.
Identify customer actions that signal a potential return: Certain actions such as adding multiple sizes of the same SKU to the cart reflects customer’s confusion and a possibility of return. The practice is quite common amongst online shoppers who order multiple sizes of the same product to try at home and initiate a return for those that don't fit. This issue can be averted at the ordering stage itself if online retailers can figure out the reasons associated with the returns.
Besides the issues with product returns, an unexpected surge in shopper activity online may flood servers. So if you face site issues while trying to replace a server, especially during the holiday rush, look at your cybersecurity system as a diagnostic resource. According to Chad Carter at WALLIX, a privileged access management (PAM) system with robust session monitoring can help you identify the problem quickly - so you don’t have to call on a business continuity plan.
The upcoming holiday season is different in a lot of ways and thus, the elevated expectations. The online sales have been growing consistently for years but is likely to break all records in 2020. This means more tech intervention for the retailers to stay competitive under such unique circumstances. Then, while others prepare to merely serve the customers, you are already better equipped with the wisdom to deflect returns and keep your holiday ‘sail’ flying high.
Disclaimer: The views expressed in the article above are those of the authors' and do not necessarily represent or reflect the views of this publishing house
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