Making purchasing decisions for a store or retail business is a complicated proposition. The decision-making becomes especially complex when you are trying to determine which products deserve permanent shelf space on your store floor; and which need to be discounted or sent back to the warehouse to make room for new inventory. It can also be difficult to know the answer to sourcing questions such as when to respond to trends, how much to purchase of a specific item and what price-points to sell at for maximum profitability. As a result, an increasing number of retailers are relying on predictive analytics to make more informed purchasing decisions. In fact, according to Martech Advisor, 57 percent of B2B marketers said predictive analytics was their “primary tool” for 2017.
Consider the following to learn more about how predictive analytics are helping companies to maximize sales and to make the most of their inventory budgets.
Determine Top-Performing Categories
Before a retailer can begin using predictive analytics to make better purchasing decisions, they have to determine the top-performing categories in their existing inventory. These can be found by collecting data on factors such including: sales numbers their POS system, consumer engagement with product images in specific categories and high-traffic areas on the company’s website. From here, a retailer can determine which categories are the most profitable, as well as what categories could be expanded to increase future sales.
Forecast Future Seasonal Inventory
Once a retailer knows where to expand their existing inventory, it is time to measure seasonal sales from past years against current industry trends to forecast seasonal sales. This helps determine how large of an order to place for a specific item, as well as where to take a well-calculated risk with a new trend or category. Targeted purchasing recommendations can be derived from this information, so retailers can order only what they need, when they need it – thus boosting seasonal sales and reducing the risk of end-of-the-season discounting.
Adjust Strategy Where Necessary
The capabilities of predictive analytics don’t stop once a retailer rolls out their new inventory. Analytics-based software monitors and reports on sales performance, so retailers can keep track of which seasonal inventory categories are the most successful and make modifications to their orders whenever necessary. This means that only the best-selling merchandise gets a place on the show floor. Since NectarOM uses the “Test and Learn” method, we are able to quickly respond to sales activity, so that clients can adapt their purchasing strategy in order to augment ROI.
Keeping Abreast of Trends
It is essential for retailers to utilize predictive analytics when making seasonal purchasing decisions to remain competitive. In fact, Martech Advisor reports that 82 percent of B2B companies used predictive analytics in last year – and of the companies who did not, 67 percent intend to implement predictive analytics in 2018. It is not only important for retailers to have access to the consumer data, but also to have data-based forecasting software which enables them to quickly respond to industry trends and customer behavior. At NectarOM, we provide clients with software with real-time reporting capabilities that clearly outline actionable recommendations – so they can amplify seasonal sales and adjust to changing consumer preferences.