Foodservice distributors (FSD) are somewhat unique in the world of wholesale distribution in that many of their products have a short shelf life, temperature requirements, and transportation restrictions, complicating their day-to-day business operations. All of these layers of complexity make it difficult for FSDs to be agile and responsive to rapid changes in the market.
Broadline food distributors, for example, sell thousands of products and serve a very diverse portfolio of customers. They have the ability to provide most categories of food that a restaurant, school, hospital, or other institutions might use—from fresh produce to processed products. The combination of customers and products creates a very complex business with some fixed costs and some highly variable costs.
Pricing is recognized as one of the most accessible and powerful tools available to FSDs to grow sales and maintain margins. Like many businesses, they have set margins that have to be met in order to stay in business. No matter what happens upstream, however, the end game is maintaining those margins. But the pricing challenge is complicated for FSDs. In order to determine the price of each product, they have to continually calculate their variable costs. This has to be done for each product or at least each product category on a daily basis to avoid underpricing (losing profit) or overpricing (losing sales).
Although investments in AI-driven solutions are occurring among the largest FSDs, others are still somewhat hesitant to jump in. We have observed that most FSDs continue to rely on a pricing matrix approach, where the calculations are complex, time-consuming, and involve a lot of guesswork. These calculations are based on market competitiveness, product type (perishables versus non-perishables, for instance), landing costs, and other factors. At a medium-sized distributor, for example, there could be 25 – 30 different categories of product and hundreds of individual product matrices to be continually updated, as well as thousands of potential price differences to be considered in the context of maintaining margins.
To further complicate matters, each customer is different, with varying purchasing behaviors driven by known and unknown forces. Yet AI has the capability to drill down in the sales data to refine FSDs’ understanding of their customers’ purchasing behaviors. There is a wealth of “intelligence” hidden in the data that AI uncovers with its analysis of visible and invisible correlations and dependencies, patterns and anomalies. AI models can detect changes in purchasing patterns and adjust pricing to maximize the probability of a sale at a given price in a new circumstance.
The complexity of large SKU volumes, customer preferences, and business rules translates into large volumes of data – oftentimes never used. With AI-driven pricing solutions, millions of data points can be analyzed in seconds to deliver optimized pricing recommendations. AI models can also consider data points from external sources that impinge on customers’ purchasing behavior—factors such as season and local weather and events.
The benefits to FSDs from exploiting their own data and the power of AI are great: AI models offer speed (through automation), accuracy (through continual learning), and continuity (minimal disruption) to workflows, since they can be performed off-site in the cloud and deployed within your infrastructure through APIs. In addition, if done well, AI-driven pricing solutions can take the typical SaaS solutions’ ROI timeframes from years to months.
Analytics2Go has configured a price optimization solution for the food distribution industry that is affordable and easy to implement. Price-Right AI has already been tested in both the wholesale distribution and the online retail environments, allowing FSDs to optimize prices on a daily basis, improving sales by 3% and gross margins by 5% in weeks to months, not years. https://youtu.be/JrAl4vbrj7c