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COVID-19 Data Modeler by Crisp Lets U.S. Grocers and Food Manufacturers Better Predict Consumer Demand for Food Categories
Crisp’s DemandWatch Leverages Real-time European Grocery Purchase Data for U.S. Inventory Planning
COVID-19 Data Modeler by Crisp Lets U.S. Grocers and Food Manufacturers Better Predict Consumer Demand for Food Categories
Crisp’s DemandWatch Leverages Real-time European Grocery Purchase Data for U.S. Inventory Planning
Published 03-26-20
Submitted by Crisp
A new data modeling tool is available from Crisp that leverages real-time European consumer food-buying data to help U.S. grocers and food manufacturers better predict American consumer behaviors during the pandemic. As European countries were impacted by the COVID-19 virus two-to-four weeks ahead of the US, the real-time grocery data from Europe enables U.S. retailers and food suppliers to forecast what consumer demand will be for their particular products.
By using Crisp’s DemandWatch modeler, U.S. grocers and food manufacturers can easily identify categories of food that have experienced greater or lesser demand and proactively modify their supply chain and production capacity to more effectively meet the demand for specific categories of products in the coming weeks, possibly months.
Examples of categories being modeled include dry goods, fresh including meat, frozen, dairy, beverages and non-food items such as paper goods.
The DemandWatch data model is updated in real-time and is free to grocers, retailers, suppliers, brokers, distributors, CPG manufacturers and other organizations along the supply chain, as well as news media at www.gocrisp.com/demandwatch.
“By working with our European customers, we are modeling customer buying behaviors in real time,” said Are Traasdahl, co-founder and CEO of Crisp. “Having this data available and knowing that U.S. behavior is following European behavior at a two to four-week time span is critical for U.S. grocers and food manufacturers as they try to predict demand for categories of food and grocery products, restock shelves and meet the needs of citizens.”
AI-Driven Demand Forecasting
Organizations using Crisp’s demand forecasting platform gain immediate insight into consumer food demand down to the store or SKU level based on a variety of market factors. The platform applies advanced machine learning and AI in order to generate forecasts in minutes, bringing together all available data from sales, inventory, third party marketing sources, and promotions. This helps organizations across the globe create more efficient supply chains and reduce common issues such as food waste, out-of-stocks, and discounted goods, resulting in optimal transactions up and down the supply chain and increased sales, all while reducing global food waste.
Crisp is applicable to specialty and artisan food brands as well as multi-billion-dollar brands. Customers that have realized significant cost savings include Gilbert's Craft Sausages, SunFed Perfect Produce, Nounós Creamery, Hofseth and Superior Farms, among others.
About Crisp
A third of the world's food production is wasted before it reaches a consumer. Crisp facilitates a more efficient food supply chain with technology that consolidates complex data into value-based solutions. Crisp uses every byte of data available to create a precise forecast for food suppliers, retailers and distributors in order to optimize profitability and drive production efficiency. Crisp was founded by Are Traasdahl, the founder of Tapad, acquired by Telenor for $360M, and Thumbplay, now called iHeartRadio.
