Covid-19 accelerated omnichannel shopping trends, such as BOPIS (buy-online-pickup-in-store) and BORIS (buy-online-return-in-store). Now retailers need to have a deep understanding of those consumer omnichannel purchase and return behaviors. Case in point, shopping data suggests that some items have a much higher return rate when they are purchased online and shipped versus being purchased or picked up in the store. Savvy retailers should find ways to encourage store visits to lower online delivery costs and use the opportunity to deliver a positive consumer experience. It’s also a win/win strategy to increase foot traffic and incremental spending.
The Real Cost of Returns
The reality is that online orders usually have a higher return rate as a major driver of overall return growth. The 2021 Consumer Returns in the Retail Industry Report from NRF and Appriss Retail found that the amount of merchandise returned as a percentage of total sales averaged 16.6 percent in 2021. Broken down by channel, the percentage of online returns was even higher, 20.8 percent—representing a cost of $218 billion in merchandise alone. Further, the Omnichannel Returns 2022 report from Incisiv in partnership with Appriss Retail, found that ecommerce average return rates are two to three times greater than store-bought purchases within the same retail category.
Findings in a recent study of an omnichannel retailer reveal that just two percent of 1150 sub-departments account for roughly 20 percent of all returns whether in-store or online. If online return rates in these sub-departments were identical to in-store return rates, then the retailer could save an estimated $18.5 million.
Second, being able to answer key questions about each shopper’s behavior across channels can help retailers provide personalized incentives or disincentives to limit returns and the associated costs.
- Does the shopper buy more online than in-store, or vice versa?
- Does the shopper return more online than in-store?
- What items does the shopper return, and through which channel?
Return Rates: The More You Know …
In addition to channel variations, some categories and items pose a greater risk of being returned. The 2021 Consumer Returns in the Retail Industry Report found that there is a large variation in retail return rates depending on merchandise category, with auto parts seeing the highest blended return (of both online and in-store sales) rate of 19.4 percent, followed by apparel (12.2 percent), and home improvement and housewares (11.5 percent).
When retailers analyze their shoppers’ behavior, it can become clear where to implement adaptive, real-time return policies on specific items to save money. Closer examination may reveal certain SKUs within a particular category that have extremely high return rates when purchased online and shipped. Using dynamic policies to require in-store purchase or pick-up for just those items can result in tremendous savings for the retailer and the chance to interact with consumers.
Findings in a recent study of an omnichannel retailer reveal that just two percent of 1150 sub-departments account for roughly 20 percent of all returns whether in-store or online. If online return rates in these sub-departments were identical to in-store return rates, then the retailer in this example could save an estimated $18.5 million. Even if only the two worst performing sub-departments were to decrease online return rates to match those in-store, over $4 million would be saved.
Analyzing Consumer Purchasing Patterns
Based on the preceding example, it seems pretty obvious that retailers across any category should analyze their shoppers’ purchasing patterns to determine areas where they can encourage certain behaviors to save money and improve overall satisfaction.
- Fragile items: Glassware, light fixtures, and glass tables or furniture have a high risk of damage or breakage and often require extra protective packaging. If an item arrives damaged, the disappointed consumer will likely return or exchange it, leaving the retailer with significant costs to replace the damaged item and re-ship it. This is where incentivizing or requiring in-store pick-up could reduce costly returns. Similarly, adding a surcharge for shipping could help reduce the number of consumers asking for home delivery of risky purchases to help recoup some of the costs.
- Hard-to-fit: Footwear is notoriously tricky to size and largely due to the introduction of Zappo’s return-friendly policies, consumers are now willing to buy everything from sandals to cleats online when they can’t try them on. It’s great consumer service, but a costly practice to any retailer. To compensate for size issues, it’s not uncommon for a shopper to “bracket” purchases–buy multiple sizes of the same item to see what fits best, choose one, and then return the rest. For these shoppers, retailers might want to charge for return shipping to discourage this behavior. If shoppers know they will be charged a fee to return their multiple sizes in the same style, they may be less inclined to bracket purchases.
The Two-Edged Sales Proposition
Your best shoppers buy the most, so it’s not surprising that they also make the most returns. When you look at it in this light, in-store returns are actually an opportunity to increase interaction with your best consumers by providing them with a great experience and engendering their loyalty for future shopping trips.
One approach could be to sell the statistically most-returned products online but require returns in-store instead of removing those products from online inventory. Since more than 80 percent of consumers tend to research online before purchasing in-store, a wider, more attractive inventory available online serves consumers better, despite the return rates. A survey from Digital Commerce 360 and BizRate Insights found that:
- 15 percent of shoppers made an additional purchase when completing an in-store return for products purchased online. (This figure has remained consistent over the past three years, despite the Covid-19 pandemic.)
- 19 percent of shoppers made an additional purchase in-store while picking up products they bought online. (This figure is slightly below the rate of 21 percent seen over the two previous years.)
Are You Maximizing Opportunities In-store?
Many retailers’ return policies are static and rigid, leaving little room for interpretation based on important context such as a shopper’s lifetime value or returns history. However, retailers have many options to reduce the burden of returns and encourage greater in-store purchases.
- Collect and analyze return data to determine what percent is due to inaccurate product descriptions, quality or sizing issues, shipper mistakes (sending wrong size or color), etc. Include a return code option with each return form to gather this valuable data. Over time this data, plus investments in AI, will allow retailers to recommend new purchases that better fit the shopper’s need and prevent yet another return.
- Encourage profitable behavior during the returns process by analyzing consumers’ shopping activities. Determine which consumers are likely to make a return, and of these, which are financial risks — or which are still considered “best shoppers” due to their overall volume of spend. Then, target them with appropriate messaging to encourage profitable actions. For example, “Try store pick-up today and get 10 percent off,” “It’s FREE to order online and pick up your purchase in as little as one hour,” and “No order minimum. Shop now for pick-up.”
- Offer shoppers incentives to return their online purchases in-store. When the consumer calls for a return merchandise authorization (RMA), the consumer support representative could offer a discount on a new purchase if the item will be returned in store.
- Disincentivize those shoppers who are making frequent, costly, online returns by using dynamic return policies eliminating free online returns or charging for returns. These policies can be provided in real-time at the time of purchase and targeted to appropriate consumers.
Note: Appriss Retail is a Robin Report Innovator. Appriss Retail provides artificial intelligence-based solutions to help retailers protect margin, unlock sales, and cut shrink. Its data-science-driven solutions streamline processes, optimize operations, boost efficiencies – all while engaging consumers and building brand loyalty. Visit https://apprissretail.com/ to learn more.
About Fin Bauer
Fin Bauer, PhD, is a Princeton graduate data scientist at Appriss Retail who develops models that help omnichannel retailers use artificial intelligence and analytics to become more profitable.