Leveraging Product Returns For Data

Leveraging Product Returns For Data

When simplified to the basics, the commerce process is a wonderful thing. A customer gets excited about purchasing a product, he or she recognizes the additional value a retailer added, such as discounts, great customer service or special rewards, and then finalizes the purchase by completing the ordering process. Go through this process a few times, and your business ends up with a high value lifetime customer.

Repeat customers who feel engaged have such a high value to business that, on average, they account for 40 percent of total revenue and drive between 3 to 7 times the amount of revenue to your business per visit when compared to one-time buyers, according to the Adobe Digital Index Report. The report estimates that for every 1 percent of return shoppers, a business’ overall revenue will increase by roughly 10 percent.

However, when a product that fails to live up to expectations disappoints a customer, the repeat customer cycle can be permanently broken. Excitement becomes disappointment, and the likelihood of the customer having a positive feeling toward the retailer plunges along with the chance they ever make a repeat purchase again.

In these moments, it’s important for a company to decide on the best strategy for encouraging repeat business and how to best foster a continuous shopping cycle. By far the best strategy for encouraging repeat business is ensuring your products consistently meet or exceed expectations. This encourages all of the positives feelings mentioned above about your products, while ensuring they don’t get returned.

Tracking data on returned products, however, offers tremendous insight that can actually make returns a great thing for a retailer. The quicker you spot a potential defect or problem with a product that consumers dislike, the sooner you can replace or discontinue selling that product. This in turn lowers the likelihood of alienating a potential lifetime customer. Unfortunately, many retailers fail to utilize data on returned products despite the huge benefit this data offers to an improved customer services experience.

Analyzing return data can reveal a variety of details you may not spot any other way. For example:

Learning that customers find the fabric used in new type of sweater irritating to the skin and scratchy.

Hearing that an entire shipment of a specific style of rain jacket is missing the drawstring for its hoodie.

Finding out that 34-inch inseam listed in the product description online is actually only 32 inches.

Occasionally, analyzing returns data can result in a quick resolution, like a change to a product description or the return of faulty merchandise. Other types of returns could influence which vendors your business orders from in the future or types of fabric in which to avoid. All of these types of action can help increase future sales by improving quality and overall customer satisfaction.

Gaining the benefit from these types of insights require very little additional effort on the part of your business. Here are a few easy steps how:

Improve Data On Returns

Inaccurate reason codes can often obscure the real problem a customer had with a returned product. Improve your reason codes so they better fit the merchandise, and add a comment section to the return form so customers can provide additional information. Also make an effort to review social media comments that mention a poor customer experience or why a product was returned.

Examine Returned Products

Your sales associates offer a potential bounty of untapped product information. Implement a process for your sales staff to quickly examine at least some percentage of returned products. Record not only the reason codes, but also product categories, vendors and any noticeable problems with the product when cataloging a return. You may also want to consider taking photos of returned products as part of the recording process, especially in cases where poor packaging contributed to the return.

Use Analytics to Quickly Spot Patterns

Using analytics as part of your returns process can help your business quickly gain insight into the experience customers are having with your products. Use the information you gather this way to improve future orders.

 

While a lot of businesses have implemented expanded returns policies, including free shipping and money back guarantees, a return is always a disappointment to a business no matter how risk free the process is for the consumer.

Return prevention offers a much higher payoff for businesses when compared to any customer friendly return policy. Quickly identifying the primary cause of returns and making necessary changes to prevent them in the future will not only prove cost effective, they also help to preserve your relationship with the customer.

The best lifetime customers are those who enjoyed their experience with a business very from the very beginning, and therefore make it a point to keep coming back. Despite this type of relationship being the very foundation of most business, few do enough to protect and nurture these types of relationships.

An analytics based return process offers businesses a great tool they can leverage against product returns and toward improved customer satisfaction. Those who fail to get onboard may very well find themselves behind the competition.

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