It was a few years ago that the ‘AI hype cycle’ really began in the retail industry, where companies were thinking about the possibilities that AI could bring to the IT process. However, soon as the early promises did not come to fruition, they started hearing AI and tuning it out, without understanding that it was in its nascent stage. However, the application of AI has evolved dramatically, and today it is truly fulfilling its promise with much more untapped potential, making retailers realize that it is just the tip of the iceberg. Subsequently, the retail industry is taking numerous steps to leverage AI and implement it into their IT stack. Helping them in their quest is Quicklizard, leveraging this continued move toward AI-based real-time dynamic pricing. “We believe that AI will touch every element of retail. As businesses will spend more time focusing on their ROI, while Quicklizard will recommend the price needed to deliver on corporate ROI goals,” states Pini Mandel, the CEO of Quicklizard.

Dynamic pricing began in the travel industry and has entered the eCommerce and brick and mortar stores today, which has increased business’ reliance on cloud computing and a need for a dynamic computing capability. Through its solution, Quicklizard ensures that AI no longer sits in this black box. The system looks at multiple data sources, including customer clickstreams, existing inventory levels, and competitor’s pricing, and combines that data, along with user-based rules and constraints, to recommend prices that meet the company’s pricing criteria while delivering a competitive one at that.The system’s pricing recommendations are 80 percent based on the AI, and 20 percent based on user-defined rules, which ensures that the customers are not pushed into a race towards the inferior products.

“It is something that we explain to our customers so that they understand the reasoning that goes into a pricing recommendation. It is what we call explainable AI,” says Mandel.

He mentions an example to demonstrate the power of Quicklizard's solution, where an online grocery store was looking to increase profitability. The company implemented an AI pricing solution, which helped the client realize a 3-5 percent increase in gross profit per cart. The key to this increase was understanding the types of products that are viewed and purchased together. The Quicklizard system analyzed thousands of completed shopping carts, drawing correlations between products that were frequently viewed and/or purchased together. This allowed the grocer to reduce margins on the product in the purchase, while increasing margins on the second item, resulting in an overall profit increase.

The case stands as a testament to the understanding of customer behavior, competition, and the market which Quicklizard brings to the table. The company makes pricing recommendations that react in real-time to changes that are happening. In another case, the company assisted a client that wanted to A/B test AI pricing vs. their pricing manager recommendations. By delivering an AI-generated merchandise solution, Quicklizard ensured that the client’s profitability was higher than the control group.

Mandel believes that as Quicklizard moves into the future, its focus on customers will allow for companies to create different prices for different customer segments based on their historical purchases and user journeys. “Dynamic pricing is currently making its move from an early adopter technology to the mainstream of omnichannel retail and Quicklizard is the easiest and most flexible solution that can help customers of all verticals transform to full AI-based pricing,” he informs. The company will also be looking for ways to overcome the physical limitations of in-store pricing such as digital price tags so that both brick and mortars and e-commerce sites can benefit from dynamic pricing.