Retail pricing methods are essential for optimizing gross sales and earnings. Efficient pricing influences shopper conduct and maximizes income by contemplating demand, market situations, and competitors. For instance, retailers can strategically alter costs and apply reductions to spice up gross sales and enhance profitability.
This paper explores a reinforcement studying strategy utilizing the Deep Deterministic Coverage Gradient (DDPG) algorithm to optimize pricing methods. By dynamically adjusting costs and reductions, we are able to enhance pricing choices. Moreover, SHAP (Shapley Additive Explanations) values present insights into the impression of worth, low cost, and gross sales on the mannequin’s choices. This mixed strategy enhances the standard pricing mannequin by incorporating real-time evaluation and explainable AI strategies.
Pricing methods in retail may be mathematically modeled to optimize gross sales and earnings. The gross sales operate may be written as:
This suggests that gross sales depend upon numerous elements, primarily worth and low cost. Sometimes, an…
