Don’t Let Returns Spoil Your Holiday Cheer
Retailers count on the holiday season to close out the year with strong sales. This year, given widespread store closures and other economic effects of the pandemic, many stores need a profitable holiday season more than ever. Retailers have beefed up e-commerce capabilities in anticipation of a monster holiday season to close out a year of unprecedented online sales.
But too many returns might spoil everyone’s holiday cheer. Even before COVID-19, returns were a major headache for retailers. Customers return hundreds of billions in merchandise each year, including up to 30% of online purchases. Retailers feel pressured to offer a generous returns policy to compete with online giants, but the losses eat into profits.
Now the potential for returns is even higher due to greater online buying volume and a new mix of customers that includes many people who aren’t used to shopping online. So, what can you do? The best way to avoid a tsunami of returns is to be proactive and use technology like artificial intelligence (AI) and analytics to spot trends and fix problems before they get out of control. Here’s how:
- Analyze historical returns data: If you have AI capable of analyzing large datasets and multiple SKUs, it can detect patterns human analysis would miss. This can help you identify products with a higher likelihood of return so you can take proactive measures to prevent a spike when online shopping increases. Apparel typically has a higher than average return rate. AI can help you identify problems like size disparities among manufacturer goods. You can use that knowledge to add information to descriptions that help customers make better choices.
- Predict which customers are more likely to return products: Analysis can also reveal which buyers return the most merchandise. While most returns are tied to legitimate mistakes in ordering, there are customers who abuse retailers’ generous return policies. Amazon has banned customers for too many returns, although the exact purchase-to-return ratio required to trigger a ban is unknown. But AI-enabled data analysis can provide a heads-up so you can proactively address problems.
- Identify which customer actions signal a potential return: Another way AI can help is by identifying buyer actions that proceed a high return rate, such as adding multiple sizes of the same apparel item to a cart. It’s a fairly common practice at e-commerce sites: customers order several of the same item so they can try it on at home and send the items that didn’t fit back. If you can figure out what problems people are addressing with returns, you can help them make the right choice the first time.
In addition to returns, an unprecedented surge in online shopping means you’re relying more heavily than ever on IT systems running smoothly. If something happens to a server during the holiday rush putting your entire e-commerce out of commission, you’ll want to know exactly who did what, as soon as possible, to repair the damage and minimize losses. According to Chad Carter at WALLIX, a cybersecurity software company, a privileged access management (PAM) system with robust session monitoring can help you pinpoint the problem immediately, so you don’t have to invoke a business continuity plan.
The coming holiday season is expected to be unlike any other. The share of online sales has been growing steadily for years, but it’s likely to smash records in 2020. That means it’s more important than ever for retailers to use technology to their advantage. Businesses will almost certainly see an enormous increase in returns this year, but with the right technology and analytics, you can keep returns from spoiling your holiday cheer.
Dr. Anil Kaul is co-founder and CEO of Absolutdata.