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How Retail Science Minimizes Back To School Stock-Out

Troy Parent
Senior Director, Retail Science & Insights

The National Retail Federation’s annual survey on back-to-school (BTS) spend reports an anticipated record spend of $80.7 billion on school and college supplies this year. As of mid-August consumers were only about half way done with BTS shopping, as many reported that they wait until the last two weeks before school starts to finish up. Many retailers have had their BTS retail store sections ready for prime time since the end of the previous school year to take advantage of early shoppers.



When shopping for school supplies, some shoppers prefer to get it out of the way early – finishing in July – to avoid stressing out about finding the purple folder or yellow notebook specified on the supply list in the final days of shopping in August. Most BTS shoppers have to visit at least two brick-and-mortar stores to check everything off the supply list, and even then hard to find items end up being purchased online.

Some stores have insight into local schools’ supply lists so they can plan their inventory better, and some design their assortment broadly enough you would think you could find everything on your list but that inevitably results in excess inventory. If retailers could plan their assortments and demand just right, BTS shopping stress could be reduced and parents would be more likely to re-visit the store that bore the most fruit in terms of check marks on that master school supply list. 

What Tech Should Retailers Leverage to Max Out BTS?

The answer depends on the primary business objective. A Demand Forecasting Solution for example would solve the shortage of the purple folder, but there are a number of other considerations such as reacting to in-season trends. With a solution like Oracle Retail Assortment and Item Planning Cloud Service in place, retailers can quickly and effectively react to season-to-date actuals and trends with exception management. This drives an increase in profits while enabling a proactive in-season item management and exception-driven process.

To solve for problems that take into consideration multiple data sources across the enterprise, e.g., merchandising systems, ecommerce, social, customer engagement and so on, retailers can also use holistic offerings like Oracle Retail’s Science Cloud Services, which combine AI, machine learning, and decision science with data captured from Oracle Retail SaaS applications and other third-party data. The unique property of these self-learning applications is that they detect trends, learn from results, and increase their accuracy the more they are used, adding massive amounts of contextual data to get a clearer picture on what motivates outcomes. This allows a retailer to move beyond understanding what will happen (predictive) to influencing the next outcome (prescriptive). 

In our experience, the approach to a specific business problem has more than one answer and in the case of retail, we find that companies with a dedicated data science team are incredibly innovative but are challenged to operationalize new innovation and speed time to market. In this scenario the Oracle Retail Innovation Workbench is an efficient and scalable solution. In the case of BTS, and specifically answering the purple folder out-of-stock use case the platform can identify:

  • items trending during BTS from the initial few weeks of data from July and August, 

  • customers with similar purchasing behavior for products such as BTS folders, and

  • the customers who have shopped for BTS folders in a previous year and either promote the hard to find purple folder or send them a promotion indicating the availability of purple folders or other items with a coupon to drive sales.

Running effective promotions is one of the most important aspects of any season. There are a few essentials to consider when defining promotional strategies, here are some examples of solutions that help to run effective promotions for BTS and the upcoming Christmas shopping season:

  • Advanced Store Clustering – Nation-wide schools have different school-year start dates, so retailers can cluster stores based on those start dates to decide when stores need to do a back-to-school promotion.

  • Customer Segmentation – Retailers can segment and prioritize customers by looking at historic BTS purchase data and run promotions against various criteria, e.g., most revenue, most profitable, lifetime value, etc

  • Offer Optimization – Building upon initial customer segmentation, retailers can use offer optimization to target customers with promotions based on preferred brands or styles and/or segment by level forecast to target promotions at customers that are not buying as first expected.

By using the right technology retailers can stock just the right assortment and offer the perfect back-to-school promotions to drive revenue, profit and keep happy parents coming back to the store.

Learn More About Retail Science and Advanced Analytic Strategies

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