Out-of-stock (OOS) is one of the biggest hurdles in the food retail industry and has gained even more attention in the pandemic environment as consumers are seeking high-demand products but are faced with empty shelves.
The causes of OOS vary widely, including problems with forecasting, deliveries, staffing, and shelf stocking—and, more recently, bottlenecks in global supply chains.
While the causes can be complex, the negative impacts are easy to understand. OOS in grocery stores results in bad experiences for consumers, who may switch brands, avoid a purchase or leave a store altogether to shop elsewhere. OOS can also result in declining shopper satisfaction and loyalty, lost sales for brands and retailers and even contentious relationships between trading partners.
Most of the time, CPGs aren’t solely to blame and struggle to fix these situations. The fault may lie with a distributor, retailer or even supply chain issues out of the CPG’s control.
CPGs have long struggled to gain better real-time visibility into their out-of-stock levels in food stores. Ideally, they would be able to collect OOS data by retailer according to state and metro areas, as well as other geographic groupings of stores. The data might show, for example, that a CPG’s product was out of stock at a key retail chain 60% of the time—and at any one time it impacted 20% of the stores in that chain.
Robust data collection about out-of-stock events are available using Datasembly, which uses an advanced proprietary technology platform to gather hyper-local, real-time competitive intelligence about product availability at retailers. Datasembly collects over 2 billion observations daily and provides insights for assortment availability, pricing and promotions.
This post is sponsored by Datasembly
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