Q&A: Dynamic Pricing in Grocery With Quicklizard CEO Pini Mandel

Pini Mandel is co-founder and CEO of Quicklizard, an AI-driven retail pricing platform. The company, which has its global headquarters in Israel, seeks to help retailers make more-strategic, data-driven and dynamic pricing moves on a wider variety of their products. Mandel spoke with Winsight Grocery Business about where AI-based dynamic pricing stands in grocery, how grocers can use price optimization to support their sustainability initiatives and the business case for automated pricing in an inflationary environment.

Christine LaFave Grace: What can dynamic pricing do for grocers? You've talked about macroeconomic factors, specifically inflation, and digital transformation—what makes now a compelling time to invest in pricing optimization?

Pini Mandel: Pricing optimization does a few things. First, it increases the profit and revenue, the bottom line. When you think about a multichannel grocer with 30,000 to 40,000 items, it’s simply impossible for items to optimize prices of each item. The logistics and the labor involved in updating prices are really complicated. Typically, grocers will create formulas, and maybe they take 5% of the high-volume product and check their competitors, but it’s not competitive pricing at scale.

With pricing optimization, they actually create prices and pricing for each item based on different characteristics while factoring in all kinds of associated costs, such as shipping, warehousing and the like. And I think that’s one thing that pricing managers do not really realize. It’s actually the idea of selling the cart rather than the item.

Using AI, scanning hundreds of thousands of receipts on a daily basis, we can pretty accurately identify the items that are bought together. And this is the next step in pricing, where retailers can strategically lower or increase prices on a specific item, and the lower-priced item functions as a low leader, bringing in customers, while the other items make up the discount and help to increase the overall profit or revenue of the cart.

As more customers are aware of price increases they’re seeing at the grocery store and hearing more about “shrinkflation” and dynamic or surge pricing, what are some keys to doing pricing optimization and dynamic pricing right?

On the grocery side, in the end, a full reaction on one said to the cost but on the other side to the breadth. They cannot look just at the cost; they need also to see the customer. And so when they have pricing optimization platform, it actually automates that. So it’s not something you need to do manually and then react for every cost increase or inventory decrease. You don’t do things just because you think that’s the right thing; you actually have a [data-based] strategy that automates that.

What’s a good place to start with price optimization?

We haven’t talked about waste, but waste is one big topic with grocers. Price optimization also helps with that. It can use AI to identify the right price that will help supermarkets move products that are nearing their expiration date so you don’t have to throw out so much food. With a project like this, you want to have quick wins, so I would start trying to tackle food waste. As food ages, it gets more difficult to sell, and then it gets thrown out. There are a few areas in the supermarket where this is really extreme—bakery section, meat section. We usually suggest to start with these kind of departments. Baked goods might see a discount at a different point every day as you get closer to the sale date.

QuickLizard’s news release says that just 2.8% of American businesses have adopted machine learning. Where are we on the adoption curve? How has the pandemic accelerated interest in advanced AI for purposes such as dynamic pricing?

AI pricing optimization has gained traction. When you think about the adoption curve, we are clearly past the innovator stage. And we are now in between early adopters and early-majority phase. I think over the next year as more grocers digitize their operations, we are going to see an explosion in pricing optimization.