TSTN increased gross profit by 23% using artificial intelligence

2024: Dynamic Pricing Implementation

"Trading Network" TECHNONIKOL Imprice and conducted a pilot project for implementation. dynamic pricing Imprice announced this on September 30, 2024. Three test and three control regions were selected for the experiment. Within the pilot algorithms , Imprice optimization was responsible for pricing more than 90% of the range. Using the capabilities of AI, the algorithm experimented with the elasticity of demand: it changed the price and analyzed how it affects demand. Further, the system independently found the optimal price balance, at which revenue and margin are maximized.

Our main task is to be a convenient, understandable and profitable supplier of materials for our customers, while taking into account the goals of the business. All projects that we launch are considered exclusively from this point of view - a balance between the benefits of the client and the goals of TSTN. We will see the result of the work done in the future, but we already note the positive impact of the dynamic pricing project on the company's performance. At the same time, the client receives a price that suits both the company and himself. In turn, we learn to use the capabilities of AI in work. This significantly increases the pace of sales and appeals to our customers, - commented Anatoly Nesterov, CEO of TSTN.

B2b pricing has its own specifics. The main goal of the pilot project was to test the capabilities of AI algorithms to take into account all the nuances. The algorithms of the Imprice system were adapted to the features of b2b sales and showed themselves perfectly during the pilot, - said Yulia Yuskova, project manager for TSTN pricing.

During the pilot project, a number of interesting solutions were implemented that take into account the peculiarities of existing business processes. Among them are taking into account different units of measurement for the same goods in competitive pricing in the field of building materials, as well as calculating optimal prices based on AI, taking into account multi-column prices for wholesalers. As a result of the experiment, the company managed to increase gross profit by 23%. After graduating from the pilot, the TECHNONIKOL Trading Network decided on further plans to digitalize pricing.

An unconditional contribution to the overall test result is the clearly stated goals of the customer and trust in the vendor's methods to achieve them. How the design of the experiment was drawn up determined the success of the project. This is always an interesting work at the intersection of expertise of its business on the part of the client and advanced approaches of Data-Driven pricing, "said Pavel Perov, Commercial Director of Imprice.