Grocery 'AI'sle: How AI is helping grocery startups evolve – Silicon Canals


Over the next decade, the humble, everyday grocery store will be the next to go all-in on the capabilities of AI to drive trade, writes Pini Mandel, CEO and Co-Founder of Quicklizard.

Up until just a few years ago, grocery store managers tracking inventory levels with a pencil and paper was a common sight. By now, most manual systems have been replaced with sophisticated inventory systems. 

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In recent years, as the grocery sector has begun to embrace digital technology, stores have been competing in a challenging environment, surviving on razor-thin margins. But digital tools have not proven particularly useful in aiding the growth margins. Supermarkets are continuing to evolve, to the point where many grocery stores are now integrating sophisticated AI technology into multiple elements of their business. 

First – for the uninitiated – let’s get into dynamic pricing. On the most basic level, dynamic pricing uses internal and external data to recommend prices. Historical sales, competitor pricing, and inventory levels are just three types of data these AI-based platforms use in their calculation. The goal for most companies is improving profit margins, but price, as we’ll soon see, has other functions as well. 

Dynamic Pricing in a Grocery Setting

Going back to the grocery aisles, dynamic pricing enables pricing recommendations on tens of thousands of items in store. On a regular Thursday, for example, it might recommend an increase in the price of beer as beer sales start to pick up. 

Dynamic pricing can also be used during special occasions, such as major sporting events, like the World Cup. Using historical data coming from the POS, the system knows that in England, demand increases on cod, haddock or pollock during the tournament. There is also greater demand for potatoes and beer, as well as the other ingredients used in fish and chips. 

In these circumstances, dynamic pricing will use AI and machine learning to determine the best pricing strategy for each of those in-demand items. It may recommend reducing the price of fish, while increasing the cost of the other ingredients, or may suggest raising the prices of all in-demand items. It then learns from consumer behavior, allowing it to optimize those pricing recommendations. It is important to remember that the goal for most grocery stores is to increase the profit margin of the cart as a whole, without necessarily being focused on the individual items.

Dynamic pricing can also be used to help reduce food waste. Groceries are notorious for discarding thousands of dollars’ worth of food every day. Elastic pricing can be used to motivate consumers to buy products that are nearing their expiration date by lowering prices on those items. This can be used to drive sales of produce, dairy, bakery goods, deli meat, and other products nearing the end of their shelf life.  

While many groceries find the idea of dynamic pricing very appealing, some hold concerns about implementation. Without the technology needed to dynamically update prices on shelves, deploying shelf stackers to change prices as needed can cut into the profit margins that dynamic pricing has to offer. 

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Fortunately, digital electronic shelf labels (ESL) are making their way into the supermarket. Now expected to grow in Europe by 9% a year over the next 6 years, ESLs are poised to become a familiar sight to shoppers. While the benefits of ESLs include creating a better shopping experience for consumers and a reduced environmental footprint, it will also enable managers to change prices without deploying their shelf stackers. 

Through ESLs, dynamic pricing can be deployed effectively in supermarkets. Using any number of communication technologies, including wifi and NFC, dynamic pricing engines can adjust prices as needed on every item in the store. 

Dynamic pricing is just one area where we are seeing artificial intelligence in grocery stores. AI coupled with ultra-wideband geo-positioning is helping consumers and store pickers find more items on their list, faster. The data generated through geo-positioning applications can even be harnessed to improve product locations, better understand in-store traffic, and optimize queue management. 

We’re starting to see AI appear in ordering systems as well. These systems monitor purchases and can accurately predict the right levels of inventory to carry to meet demand. 

Grocery stores may have been one of the last of the retail holdouts to jump on the AI bandwagon, but all indications point to them embracing the new technology and all the benefits that will come with it. 

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