New app predicts COVID-19 product shortages

Simporter's Epidemic Demand Surge Protector is based on sentiment, demand and community transmission data.

Simporter-image

Retail tech company Simporter has a new app it believes can help predict product shortages caused by COVID-19.

Simporter’s Epidemic Demand Surge Protector platform identifies products at greatest risk of running out of stock. The app tracks key CPG products like over-the-counter medicine, food, beverages, cleaning products, baby products and 12 other supermarket categories.

Tim Hall, CEO of Simporter, says the EDSP app tracks the pandemic based on real-time community transmission rates from official sources, outputting provincial and state-wide virus heat maps. However, Hall says, consumer anxiety and confidence can be a more useful source of information than transmission rates when it comes to predicting demand and shopping patterns. To that end, it also uses natural language processing AI against data from social media and e-commerce reviews to “look at what consumer conversations are,” and to predict behaviour. This is bolstered by biweekly consumer panel data conducted on purchasing in specific categories, search data and point-of-sale stats from Nielsen’s Connected Partner Network.

The application can connect manufacturers, distributors and retailers with the way consumers are thinking while isolated at home and ensure they are able to find supplies they need from their local stores.

In addition to helping retailers and brands head off supply chain issues they have been struggling with in recent months, having things in stock will minimize the number of shopping trips consumers need to make and reduce the risk of community transmission.

Hall says the platform is not for categories like paper towels and hand sanitizers where shortages have been obvious, but for things like diapers or infant formula that are vital to consumers and where shortages may come as a surprise. Marketers can benefit from knowing which categories are going to face the most demand and make the best decisions with that data.

Hall says most of his clients have relied on tools and applications that have long-tail data, looking back at two to three years of sales stats for benchmarking – which he says doesn’t work in a marketplace disrupted by coronavirus.

”The marketplace is upside down right now,” he says, adding that shopper patterns have changed, as have products being purchased, and how much discretionary income shoppers have compared with a only few months ago.

Founded in 2018, Simporter typically uses AI to forecast sales for products before they hit the market, and some of that work ended up having clear applications to the current retail environment. The startup worked with Calvin Klein on a product launch last year, expanding its work to its underwear, shirts and its Tommy Hilfiger retail channel. Once COVID-19 started, Hall says, and customers and big retailers like Macy’s closed, the fashion company was able to tackle further challenges with the app, such as looking into how its consumers were searching for its product in different ways.

Simporter also worked with Unilever and its Knorr brand, initially to help compete against the likes of home meal kits like Blue Apron – but has also monitoring shocks in the supply of ingredients Knorr is mixed with, like meat.