Inventory management can make or break an online retailer. But there’s more to managing your inventory than just making sure you have products ordered or in stock. In today’s fast-paced, eCommerce-driven world you need to know what products shoppers want before they come looking for them. This means predicting your inventory as much as maintaining it.
The two sides of inventory management
Effective forecasting is more important than ever before because it allows eCommerce operators to stock products ahead of consumer demand. Not only does this ensure you’re staying in favor with shoppers, it offers a domino effect towards an overall positive customer experience. In-stock products mean faster fulfillment, which means happier customers, which means better loyalty and brand advocacy. You could even argue better inventory management keeps you ahead of the competition.
For as many positives as good inventory management delivers, poor inventory management has an equally negative effect. Constantly running out of stock, stocking the wrong products, or overstocking can quickly collapse a business. Inefficient inventory management results in a poor customer experience, fulfillment nightmares, and crucial capital tied up in inventory.
Using data to better manage inventory
While good inventory management may be a learned skill, predicting trends in a cyclical retail industry is something anyone can accomplish with the right data. And, with the amount of data tracking and aggregation available to eCommerce operators today, there’s no shortage of insights when it comes to forecasting your inventory.
You can translate data from just about every point in the sales funnel into better inventory management, from inbound keyword rankings to on-site navigation patterns and final checkout items to demographic data. Big data fuels better inventory forecasting and management by:
- Identifying customer trends, preferences, purchase patterns, and other factors that affect demand
- Planning to meet demand with more accurate inventory numbers and products
- Proactively satisfying consumer demand instead of reactively trying to fulfill requests
Robust data can also be deployed in the form of predictive analytics. Knowing what your customers will buy even before they do based on purchasing habits is a powerful way to increase your conversions and bottom line. For example, being able to aggregate broad shopper data from your business and pull out trends, then apply those trends to individual habits means being able to predict the products those shoppers want to see. These predicative analytics can then fuel everything from targeted email marketing to product suggestions or even what items you should inventory.
For savvy eCommerce operators, more information means more opportunities to curate an inventory that is better-geared towards the needs and wants of customers. Good data aggregation platforms also offer dashboards that allow you to easily review and spot trends.
Forecasting better for success
Big data forecasting is only the start of modern inventory management. When you add advancements like machine learning or predictive analytics, an entirely new set of possibilities open up, including:
- Strategic planning to anticipate consumer interests based on social trends or emerging sales trends
- Real-time adaption for inventory, so purchase orders are automatically made as thresholds dictate
- Consumer influencing of add-on or peripheral sales based on data analysis of shopper trends and available inventory
While good inventory management has a positive effect on business operational successes, predictive inventorying and forecasting have the power to bolster these successes even further. In a cyclical industry like retail, these opportunities can be your gateway to long-term success.