The Hidden Causes Behind Mass Retail Returns
Day to day you probably try to reduce returns using procedures, product information, and technology. You may, therefore, be surprised when, seemingly out of nowhere, you see a surge.
A calendar can reveal some potential triggers that cause whole groups of people to initiate the same return behavior. The clearest example is December 26, which Appriss Retail’s analytics consistently find to be the day with the highest volume of retail returns for the whole year. We all know why. Related to that are elevated returns throughout the winter holiday season.
Tech companies such as Apple tend to release new products about the same time every year. A spike in returns after the release date can be a signal of confusion—consumers may need more support in adopting new technology. You can anticipate and plan for that confusion based on the launch schedule.
Analyze your returns
Sometimes seasonal wardrobing/renting patterns emerge in which consumers return used goods as new, and they do it en masse, leaving stores with overstocks. By considering your product focus and events that may impact sales, you can get an idea of where to start your analysis to find the hidden causes behind spikes in returns.
Have you looked for patterns by product category? If so, you may be a step ahead of your competitors. The next question is: Have you analyzed those returns lately? Recent research by Appriss Retail shows that these externally-driven return patterns can change over time.
Example Analysis: TV Returns and Football’s Big Game
Appriss Retail analyzed returns data for televisions 46 inches and larger correlating to the NFL football playoffs. These televisions have dramatically lower prices in the last few years. Analysts examined data from 40,000 retail locations for the time period approaching and immediately following the Big Game.
A surprising pattern emerged in 2018 that was not present at the start of the decade when the company conducted a similar analysis. You can view the results of the new research in this video. If video is not your preference, the findings are available in this white paper.
A surprising finding was that was that a rental pattern that had been nationwide became regional. Retailers unaware of the shift in consumer behavior may have over-staffed certain stores or made contracts for refurbishment that were geared for higher volumes.
If you have never analyzed returns by category, now is a good time to look back on last year’s data to find unexpected patterns. You can start with the data, or you can start with the calendar to look for a logical connection.
If you looked for wardrobing/renting patterns years ago, it may be time for a refresh. Changes in pricing, shopping channels, and even how events are being celebrated can impact consumer behavior on a grand scale.