The product price life cycle includes several key phases: the new product introduction phase, where the initial price is set to attract consumers; the promotional phase, which aims to drive traffic and sales through discounts and promotions; and the clearance phase, where strategies are implemented to manage excess inventory effectively. Each phase requires tailored pricing strategies to optimize sales and profitability.

AI plays a significant role in optimizing pricing strategies by identifying slow-selling products and initiating discount processes earlier, which can help recover margins that might otherwise be lost. It can analyze product attributes and sales data to recommend localized markdowns and transfer products to more successful selling locations, thereby streamlining inventory management and enhancing overall pricing effectiveness.

Retailers often struggle with excess inventory at the end of the selling season, which can significantly impact profitability. A one-size-fits-all approach to markdowns can lead to fewer sales and deeper discounts than necessary. Additionally, timing is crucial; markdowns that are not implemented at the right moment can result in unsold inventory that must be liquidated, ultimately affecting the bottom line.