How AI taps data to make ecommerce more dynamic

“Modern dynamic pricing architectures also analyze real-time data on competitors’ prices and stock collected from websites using web scrapers or robotic process automation (RPA) bots. It evaluates many internal factors, like stock or inventory, KPIs, etc. And also evaluates external factors, including competitor prices and demand, to generate prices that align with a company’s pricing strategy.
Price-optimization system: This approach utilizes self-learning ML models without human intervention. It is best suited for airlines, hospitality, and ecommerce industries, where several variables impact pricing decisions. Such an AI-based approach depends on a vast amount of data to impact variables on the price. As more and more data is fed into the AI system for training the model, it self-learns through reinforcement-based methods and automatically tweaks the system’s performance.”