Peak 2023 Prep: Using Predictive Analytics to Keep Costs in Check

This peak, retailers are shifting their focus from last year’s struggle with supply chain disruptions to meeting customer expectations while controlling costs and boosting profits. Inflation and talk of a recession continue, and transportation and freight costs are high. However, customers continue to shop and their behavior has not been significantly altered. They continue to expect convenience, omnichannel options, multiple fulfillment options, real-time order tracking, and easy returns. Retailers are turning to predictive analytics to help keep costs in check and streamline operations.

Many retailers are still grappling with overstock and offering discounted products to move inventory. One pandemic lesson is that predicting inventory demand has become exceedingly difficult without real-time inventory visibility and data. The more accurately retailers can predict and order inventory, the easier it is to control costs. Predictive analytics uses real-time and historical data to inform retailers about which items are currently popular based on purchasing behaviors. It also helps determine appropriate inventory levels at each location. By reducing the risk of excess inventory, retailers can mitigate costs this peak season.

Hiring continues to be difficult for retailers. Despite wage increases, most retailers remain understaffed, which will mean every associate will need to work harder during peak. Figuring out how many additional peak season employees or additional shifts you need can be easier when you use predictive analytics. It can help forecast foot traffic and online shopping volumes before peak, so retailers can prepare earlier for staffing increases or work with temp agencies to fill gaps. In tight hiring markets, competing for talent earlier is the best way to ensure you have the employees you need to support a great holiday shopping experience.

Part of inventory forecasting consists of knowing what customers will want. Targeted marketing campaigns often drive their desires, so retailers that use their data and predictive analytics to target marketing campaigns, anticipate customer channel preferences, can more accurately predict inventory needs.

Customers continue to use BOPIS and store fulfillment options to meet their shopping needs. Stores that appropriately predict staffing needs for store fulfillment will be able to meet customer needs even after holiday shipping deadlines pass. BOPIS and options like ship from store enable retailers to reduce transportation and freight costs while still giving customers the convenience they need during busy peak season.

Radial predictive analytics can help retailers more precisely forecast inventory, staffing, fulfillment, and marketing to help control and mitigate costs and improve profitability.

Follow Radial on LinkedIn, Facebook and Twitter.