How Retailers Can Leverage Prescriptive Analytics to Maximize Sales and Avoid Layoffs

Looking ahead, 2021 will prove to be a critical year for retailers as they work to achieve financial recovery in the wake of COVID-19’s negative impact on their budgets and revenue. Typically, labor and inventory are retail’s biggest expenses, making them the logical choice when considering where to make cuts. Since inventory is a significant sales driver and has been optimized many times over in recent years, payroll is one of the first places to cut costs, resulting in layoffs or furloughs.

In the current economy, layoffs can be devastating to employees and overall company morale. Instead of searching for cost-cutting opportunities, retailers are focusing on strategies to give staff the tools to recover revenue losses by increasing sales and other key performance indicators (KPIs). One of the most efficient ways to do so is through advanced analytics solutions like prescriptive analytics.

Prescriptive analytics is a software solution that employs the latest in artificial intelligence (AI) and machine learning capabilities to identify areas for improvement and prescribe clear next steps. By turning retail data into descriptional insights and actionable next-steps, organizations are empowering their teams to increase revenue and productivity.

Below are three ways prescriptive analytics can empower your business to recoup 2020’s losses without layoffs.

1. Increase Store Associate Productivity

One of the most successful ways retailers are increasing sales is through upselling or cross-selling. However, these tactics require either hiring highly skilled store associates, or deploying continuous training. Unfortunately employee training can be a costly investment that does not always produce long-term results.

Prescriptive analytics solutions automatically analyze store data to identify areas for improvement that can increase employees’ selling power. For instance, consider one of my brick-and-mortar retail clients whose sales had been lacking. When analyzing cashier data, the store’s prescriptive analytics solution noticed that certain employees had a high level of single-item transactions, while other cashiers had a record of predominantly multiple-item transactions. The data indicated they were leveraging successful upselling techniques.

Rather than paying for expensive on-going training, the prescription for success was for store managers to adjust the schedule to pair the underselling associates with the higher-selling associates, allowing for cost-free, peer-to-peer training. The store also re-examined the items on display at the lower-selling cashiers’ registers, placing more attention-grabbing products front and center to encourage impulse purchases. By making these strategic updates, the store was able to drastically improve sales and better satisfy customers. Together, these benefits could be the difference between layoffs and success for an organization in the midst of financial recovery.

2. Monitor and Remedy Phantom Inventory

Phantom inventory occurs when an inventory management system (IMS) incorrectly reports an item as available in the store and on shelves when it is actually out of stock, often due to theft, supply chain delays, unreported damages, and other drivers of inventory inaccuracy. An empty shelf is frustrating to customers, especially during the pandemic when running out to the store is no longer a simple task, and one negative experience could result in the loss of a customer’s loyalty forever. In fact, a recent industry study found that 20% of shoppers wouldn’t return to a store if its website listed a product as available in-store, but they arrived to find it out of stock. Phantom inventory results in the loss of both current and future sales.

Prescriptive analytics solutions identify when a product suddenly stops selling despite having enough stock reportedly on hand. Store managers are alerted to the situation in real time, allowing them to quickly remedy the situation, especially when the inventory is sitting in the back of the store rather than on front shelves. In one example, a grocery store client was notified that blueberries had suddenly stopped selling despite typical weekly sales of $1,500. Upon investigation, the store manager realized there were no blueberries on the shelves or in the back cooler due to a glitch in the store’s OMS. With this information, the grocery store quickly overrode the system’s glitch and restocked the shelves with ample blueberries. Having a prescriptive analytics solution in place saves retailers thousands of dollars in lost sales every day due to phantom inventory.

3. Identify Complementary Items

Certain items in retail are naturally purchased together. It’s a well-known practice in retail to strategically pair items through in-store displays or in online shoppable content (the “Halo effect”). Some combinations are obvious: think shampoo and conditioner, wine glasses and corkscrews, burgers and buns. However, others might be less obvious, meaning retailers could be missing out on revenue opportunities.

Prescriptive analytics solutions give retailers visibility into the complementary items that can be strategically sold to maximize sales without any additional expenditure. By leveraging an advanced algorithm, the solution analyzes millions of historical online and in-store transactional data to specific combinations of products that are frequently bought together. Prescriptive actions are automatically shared with the store, merchandisers and e-commerce managers, directing employees to pair items in their next plan-o-gram or couple them in an online sales campaign. As a result, the customer experience is enhanced as they easily locate items they might not have even known they needed, and stores increase their sales. It’s a win-win.

Margins are tighter than ever, leading many retailers to make drastic and often unnecessary expense cuts like labor layoffs. By leveraging prescriptive analytics, retailers can glean clear insights and dispense actionable next steps that empower them to maximize sales and potentially even recoup 2020’s losses without touching payroll.

For more information on using prescriptive analytics in retail, visit www.zebra.com/prescriptiveanalytics.

Guy Yehiav, GM of Zebra Analytics, is a retail tech and business expert dedicated to helping companies harness the power of data through prescriptive analytics.

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