December 8, 2014
By John Squire
Returned goods cost United States retailers a staggering $267.3 billion in lost revenue last year, according to The Retail Equation. Now that is a harsh returns reality.
But it does not have to be such an uphill battle for retailers looking to enhance reverse logistics.
By connecting data across an organization, retailers can learn where they can improve on returns to bring profitability back to the enterprise.
While determining a cause for individual returns is certainly a qualitative exercise, it is just as importantly a quantitative one. At what volume of returns should you be alarmed? How do you know when to dig deeper to find the root cause?
The answers will not magically appear. But when you use an intelligent approach to connect and take action on your enterprise-wide data, you will realize what is truly impacting their returns.
Customer reviews: listen to the voice of your customer
Gathering customer review data from across your entire product line and comparing that to return rates by category, product and style can be a daunting project. But keeping track of the ratings, open-ended responses and reason codes yields incredibly valuable information on returns causes.
With intelligent technology, surfacing problems and outliers can help you focus on taking the right action quickly instead of spending hours analyzing return rates.
Through connecting returns data with customer reviews and reason code data, for example, retailers can see that an item color was misrepresented on the Web site and immediately update the dress’ product page.
One size does not fit all
Product issues such as incorrect sizing or quality are the most common reasons behind high returns.
Sometimes the exact issue can be difficult to pinpoint, so retailers should investigate the product and order details to find the culprit behind the problem at hand.
Customer reviews may help, but without first knowing the order details for these customers and their exact return information, it can lead to a misdiagnosis as to whether returns were due to a single color or size of a particular product.
Do your research. Find out who ordered what, when and check reviews to understand why they were unhappy.
Your return code data is vital to understand sizing issues as well.
One high-end apparel retailer found that its primary culprit in returns was not color, fabric or quality (only 3 percent), but a sizing issue between the brands it carried (representing 26 percent of returns).
Another retailer found that it had more than $200,000 worth of merchandise returned because of the difference in color between its product image and the actual dress received by customers.
The culprit of returns is different for every retailer and every product assortment, so it is vital to pull together reviews and returns data to understand your unique concerns.
Limit financial impact by leveraging marketing campaign data
You may already know the reason behind the high return rate of a product, but until you can put a fix in place, it is crucial to minimize any financial loss.
Knowing what your marketing teams are promoting can diminish additional returns and associated costs.
Marketers that deal with fast-changing promotional campaigns can sometimes miss the connection between promoted products with issues and negative margins.
The ability to monitor this data and pause specific campaigns brings measurable value back to retailers, and saves marketing dollars from going to waste on low performing or unpopular items.
Whether it is an email campaign, search term or display advertisement, marketing channels may be driving additional traffic to products with high return rates, wasting marketing dollars and eroding product profitability.
As your returns and marketing data become more connected, promotional campaigns can be monitored and thusly adjusted.
Missed deliveries means big returns
Sometimes returns have nothing to do with the product at all.
Missed delivery-on-promise such as the UPS holiday snafu of 2013 or shipping the wrong items can be a large contributor to high returns and low customer satisfaction.
When time-sensitive items such as food or seasonal merchandise miss their delivery date or are incorrectly packaged, the retailer may not be able to connect the dots without visibility into operations, shipping and handling.
By connecting order data with returns data and operations, retailers can reach out to the affected customers with alternative shipping options to hopefully achieve the goal of ensuring customer satisfaction, retaining those customers and reducing returns.
But it does not stop there.
Too often reverse logistics evaluation ends at the reason codes and does not look at how quickly the returns department gets the product conditioned and in stock.
Retailers need to address the full returns process that includes getting returned products back on the site and ready for resell.
What you see is not always what you get
If you have high returns due to product issues, but you still have inventory on the shelf that you need to sell, looking at product pages can be an essential remedy.
Inaccurate product descriptions or imagery are certain to result in high returns, since customers expect to receive an item identical to what they paid for online.
The way a product is showcased on your Web site can affect returns just as much as the attributes of the product itself.
Adding something as simple as an easy-to-navigate sizing guide and suggestions on related accessories can give shoppers a better idea of the product and what to expect if they purchase.
Understanding how accurate your portrayal of a product is on your Web site can help reduce returns related to sizing, fit, style and other features or flaws.
RETURNS WILL NEVER be completely eliminated. But retailers can take intelligent steps to reduce them, increase profitability and keep customer satisfaction levels at their highest.
Starting with these five critical connections for reducing returns will lay a strong foundation for intelligent commerce that is powered by data connection, and ultimately lead to a better understanding of how to make the shopping experience seamless for your most loyal customers.
John Squire is president for North America at OrderDynamics, Redwood City, CA. Reach him at firstname.lastname@example.org.