By: Ronen Lazar
When it comes to holiday inventory, most retailers use their intuition and industry knowledge to make their sales projections, plan their promotional calendar, and schedule product reorders. This was fine when the season’s promotions were merely percentages off and customers purchased products in stores. But as the retail world becomes more complex, so too must retailers’ holiday plans. With an estimated 40% of retailers’ yearly profits on the line, intuition this holiday season just isn’t enough.
JC Penney learned this first-hand in 2014. The drive to turn the company ‘cool’ again led to poor management of product reorders. After a successful Black Friday, the company was left without stock for many of the season’s best-selling products on which their customers had come to rely, basics such as boots and home goods. Having ignored historical sales data and purchasing trends, JC Penney’s inventory stock was instead items that had been identified as ‘cool’ or ‘on-trend’. The company not only had massive amounts of lost sales, but it also had unhappy customers who had come to JC Penney for those basics and had been told they were out of stock.
While this inventory mishap was under the leadership of former CEO Ron Johnson, JC Penney’s new CEO, Marvin Ellison, has since stepped in and is investing in the “science of retail” and believes firmly in stronger backend systems for the company. “We have tons of customer data, we just don’t do anything with it,” stated Ellison.
Ellison is not the only one to adopt this tech-data mentality. Walmart has also invested heavily in inventory management systems and technology solutions. To be successful in today’s tech-driven, complex retail environment, other retailers would be wise to follow suit. Retailers with a tech-data mentality will benefit from both the streamlined and automated workflows the actual technology provides as well as the incredibly valuable data that can be collected, analyzed and used to help with sales projections, promotions and inventory management.
Inventory and customer behavior data are two of the most impactful pieces of information for retailers. Prior to every season—and the holiday season in particular—retailers must reconcile their inventory from every channel through which they sell their merchandise. And this is becoming more and more challenging as the ways in which buying, distributing, and returning products grow. Such growth in complexity simply underscores the importance of retailers’ ability to have real-time inventory tracking and a full understanding of their products to maintain proper inventory management.
While this inventory data alone is critical to retailers, coupling it with customer behavior data can lead to bottom-line-altering results. By using historical trend data, tracking real-time top selling items and loss-leaders, and identifying purchasing frequencies, optimal price-points, and key locations, retailers can put together a solid profile of what their customers expect, look for and will buy, both during the holiday season and all year long.
And this information is gold. Retailers can use this information as the backbone to their holiday planning, knowing what to stock in what quantity and at what price. They can also use this information to help plan markdowns and identify product considered unsellable and direct that through off-price channels pre-holiday.
Retailers today benefit from a complex and tech-driven environment that allows them to engage with customers and sell product through multiple channels. This new-found complexity has also raised the bar when it comes to sales projections, promotional strategies and inventory management, especially around the holidays. To be successful, retailers can no longer rely solely on intuition; they must use carefully collected and mined data to get it right.
Ronen Lazar is co-founder and CEO of Inturn, which enable brands to efficiently sell excess inventory to retailers in private, online showrooms and provide improved decision-making to turn inventory faster, improve cash flow, and optimize returns.