Turning U.S. Back-to-School Sales into Compelling Customer Experiences

With the busiest weeks of the back-to-school shopping season still on the horizon—expected to span from July 30 to August 26, based on region—there will be many opportunities for retailers to remind shoppers of the benefits of heading into stores. There’s no question that back-to-school shopping remains a mainstay of brick-and-mortar operations. Whether due to sentimentality, a desire to evaluate options in person or a mix of both, many U.S. consumers still opt to peruse store aisles to pick out their kids’ backpacks, binders, and ballpoint pens.

Last year, 76% of back-to-school shoppers said they intended to do their shopping in stores while only 54% indicated they would shop online. Retailers who succeed in delivering exceptional back-to-school experiences in their physical stores will more likely see significant revenue from the season. After all, spending on school supplies in the summer months topped $36.9 billion in 2022. 

However, the prize this back-to-school season goes beyond sales of school supplies. 

Setting the Stage with Back-to-School Data

Robust enterprise-wide analytics programs can help retailers turn daily operations into invaluable insights—and the back-to-school season will provide a wealth of data.With shoppers across demographics planning to head to store locations during this period, the back-to-school rush may be a perfect opportunity to kick-start improvements to shopper experiences. Doing so will rely on turning location-level insights into meaningful investments that showcase everything in-store retail has to offer. 

Retailers that have made initial investments in connected analytics suites to streamline operations can use those systems to improve shopper experiences. Data streams from these solutions can help retailers:

• Reduce friction. Today’s shoppers increasingly equate “satisfying” with “convenient,” so streamlining experiences is critical to success. However, keeping things moving during peak hours can be difficult, especially if those peaks come unexpectedly.

Traffic analytics suites not only help retailers predict when their busiest days will come but help remove friction from shopper journeys when they do. Wholistic tagging programs can support more accessible self-checkouts and reduce wait times for cashiers by allowing retailers to deploy hard tags more strategically, cutting wait times associated with removals. They can also cut down on physical barriers in aisles (like locked cases) that can lead customers to abandon purchases.

• Avoid stocking and merchandising hiccups. Along similar lines, item-level inventory management supported by RFID can help make out-of-stocks and excess inventory things of the past. Programs that focus on inventory management can provide insight into where, when, and how merchandise moves throughout the store to provide visibility into not only what customers buy but the things they choose not to. 

Furthermore, these systems can show the impact of retail crime in detail so retailers can get a clear picture of what’s left on shelves—even if an item left the store with a thief. This information can help merchandising teams make informed decisions about what to restock while boosting loss prevention efforts.

• Allocate labor more strategically. Although experts can predict peak traffic days for different regions or business types, every store location is unique. Implementing a traffic monitoring program can help retailers begin to compile a historical record that shows their actual performance under different circumstances—like weather, holidays, local events, and more—to make more precise traffic predictions. As these records get more comprehensive, insights will improve alongside them, driving more strategic staffing choices on the busiest days and the quietest.

• Embrace personalization. It’s no secret that what works in one location may not work in another, but understanding the reasons behind these variations is another story. While focus groups can help, these endeavors provide anecdotal and self-reported feedback at best.However, artificial intelligence (AI)-enabled monitoring through computer vision and other technologies can help bring shopper preferences and motivations into clear view. These systems can illuminate shoppers’ reactions to different areas of the store in real-time, highlighting the displays, promotions, or departments that aren’t meeting customers’ needs and taking the guesswork out of the process. Armed with these insights, retailers will also be able to develop more customized loyalty programs and inventories based on the unique findings in their stores.

Success This Summer—and Beyond

While it’s a typically lucrative event, back-to-school shopping is also a good stress test of current operations that can reveal opportunities for improvement ahead of the holiday season. The choices shoppers make and operational roadblocks that arise during peak traffic times this July and August can act as a guide for operational excellence in the second half of the year, which means the summer rush associated with back-to-school shopping is a perfect opportunity to uplevel analytics programs with an influx of consumer and operational data.