Retailers in the back-to-school space experienced a once-a-century year in 2020, and as the season comes to a climax, companies selling school-related products, like apparel and electronics, are using the learnings from the last year to better forecast the actual demand, determine assortment and optimize inventory levels. They are taking sales and other financial statistics from only the most immediate past periods and applying AI and machine learning to optimize their assortments and sharpen their pricing strategies.
The back-to-school season is critically important to both consumers and retailers. A recent survey from the real estate group JLL reports that spending per child is jumping 21.4 percent to an average of $356.94 per child this year, compared to $294.11 last year. The survey also showed that consumers started their back-to-school shopping earlier than usual to avoid pandemic-related supply chain disruptions.
The disruptions from COVID have not only impacted supply chains, but accelerated several retail and consumer trends already in place. Chief among these is the growth of online sales for consumables like school supplies. While shoppers are still ordering considerable volumes online for home delivery or pickup in store, many are going back to physical stores. The JLL survey reveals that 47.6 percent of parents are shopping at open-air centers and 40.1 percent are visiting enclosed malls, compared to 31.6 percent in 2020.
Still, the increase in online shopping has pushed evolutionary change in the industry and is impacting the way retailers go to market for the back to school season. From pursuing showroom concepts and moving away from a standard merchandising approach, to using advanced data analytics to help create personalized offers and pricing both in the store and online, companies are implementing tactics that make buying and fulfilling orders from them easier. This is especially true with seasonal merchandise, like back-to-school, where consumers are now getting better prepared for home schooling and hybrid/remote learning by investing in home study centers and equipment to give students a workspace similar to their parents’ home offices.
While many retailers expected a return to normal for back-to-school this year, they also hedged their bets on inventory and aren’t risking investing in products that haven't been proven to sell-through at the store level or online. They are, however, making sure to have full inventories on the basics – pens, paper, notebooks and the like. Other items that have been marginal contributors in the past are now receiving the same merchandising attention as these categories. On the positive side, they expect a refresh of wardrobes for school kids and also for adults returning to work (this won't be suits and fancy dresses but rather more casual dress).
In addition to the assortment challenge, retailers are working on fixing the disruptions in the supply chain that were pervasive last year by adjusting their inventories to make them more precise and put mechanisms into place to respond to changes in demand faster. That means they need more accurate and timely data to make quicker decisions. So, as ecommerce penetration continues, there will be more inventory being held in backstock ready to be shipped for on-line orders or to fulfillment in store. Managers that have access to more accurate predictive analytics sooner will make the adjustments that ensure profitability.
Retailers are also using analytics from financial services and healthcare, as well as the transportation and hospitality industries, to understand how best to serve the customer during the back-to-school season. A good example here is the deployment of revenue management from the airlines, which rapidly prices flights based on changing demand and several other factors. Another example is footwear with retailers using technology to determine what shoes are selling to get more product out to the stores, and which shoes are not selling so they can stimulate sales by offering discounts.
While the use of analytics in areas like pricing is not new to most retailers, what is new is how leading-edge retailers are using these tools to drive their business more precisely. Retailers are realizing that customer response to price varies not only by product and time, but by channel and offer. Especially during the last two years, retailers are paying more attention to which products drive top line revenue and market share, and which products drive margin and customer loyalty. By identifying these opportunities by product and site earlier than ever, retailers can make purchase quantity decisions, channel and store level allocations and optimal pricing to achieve both growth and profit.
The back-to-school season this year also represents a once in a generation opportunity for many retailers to keep their inventories clean. Retailers have paid a steep price over the last 16 months in reducing inventory. The question now is how to keep inventories lean. Enhancing merchandising processes with advanced analytics that identify true demand – not just historical unit movement – allow the retailers to order back into inventory judiciously to keep the hard-fought gains on controlling inventory in place.
Additionally, retailers find themselves with new pricing power. With supply and inventories lean and demand resurgent, traditional heavy discounting can be avoided. However, this type of across-the-board pricing power is temporary. Key to maintaining customer loyalty and building a stronger brand, especially online, is a better understanding of price. Pricing power can hold for products that are deemed essential or of high value to customers. But over-pricing basics can risk eroding price image and lead to customers abandoning a brand as quickly as they embraced it. Using price to drive department or category goals is not good enough anymore. Pricing has to be precise to the product level.
Bottom line is that for retailers to run successful back-to-school campaigns, or any seasonal campaign in the current environment, they need to have new toolsets that specifically help drive performance. These toolsets must apply AI and machine learning to optimize inventory, assortment, promotions and pricing in a fashion that customers will be most receptive to in the channels they are most likely to shop. Only then can a retailer effectively engage the shopper while profitably fulfilling that shopper’s demand for products.