GK Software offers retailers a new dynamic pricing solution based on artificial intelligence (AI). The solution is also available through SAP under the name of SAP Dynamic Pricing by GK. The solution, which is based on GK's own Artificial Intelligence for Retail (AIR) platform, enables retailers to utilize the available customer and market data to optimize their omni-channel pricing strategies in real time. The AIR platform is based on an artificial intelligence process such as reinforcement learning which facilitates the provision of customized processes for retailers. Besides dynamic pricing, other solutions include personalization and fraud detection, for example.
The new dynamic pricing solution calculates the competitive market price for each product in the range in real time. This information enables retailers to automate the continuous adjustment of their pricing in line with the ever-changing market situation and other influencing factors. The solution makes it possible to deploy a variety of pricing strategies, such as sales-oriented or profit-oriented pricing, promotional pricing or minimizing obsolete stock. Hence, dynamic pricing can actively help to reduce food waste when the optimal pricing strategy is applied in order to offer discounts on the right products at the right time. The solution also supports long-term pricing strategies for selling off seasonal items (e.g. in the fashion sector) in order to minimize losses or huge price reductions. Retailers simply define which pricing strategy should be applied at which time, and then the self-learning AI-based pricing algorithms automatically optimize the prices, thus relieving the pricing burden on those concerned and increasing their efficiency.
Automated self-learning price optimization based on a clear strategy offers considerable benefits compared with the traditional experience-based and rules-based pricing approach. The AI algorithms not only take account of numerous factors affecting the price in near real time, but they are also suitable for large product ranges. Meanwhile, the solution offers retailers significantly more flexibility and enables them to continuously measure their dynamic pricing performance against the pre-defined goals.
The new dynamic pricing solution calculates the competitive market price for each product in the range in real time. This information enables retailers to automate the continuous adjustment of their pricing in line with the ever-changing market situation and other influencing factors. The solution makes it possible to deploy a variety of pricing strategies, such as sales-oriented or profit-oriented pricing, promotional pricing or minimizing obsolete stock. Hence, dynamic pricing can actively help to reduce food waste when the optimal pricing strategy is applied in order to offer discounts on the right products at the right time. The solution also supports long-term pricing strategies for selling off seasonal items (e.g. in the fashion sector) in order to minimize losses or huge price reductions. Retailers simply define which pricing strategy should be applied at which time, and then the self-learning AI-based pricing algorithms automatically optimize the prices, thus relieving the pricing burden on those concerned and increasing their efficiency.
Automated self-learning price optimization based on a clear strategy offers considerable benefits compared with the traditional experience-based and rules-based pricing approach. The AI algorithms not only take account of numerous factors affecting the price in near real time, but they are also suitable for large product ranges. Meanwhile, the solution offers retailers significantly more flexibility and enables them to continuously measure their dynamic pricing performance against the pre-defined goals.
