Implementing AI-based Dynamic Pricing for Restaurants

Customers continuously examine restaurant menu prices for reasonable acceptance with fairness and sensibility. A fixed item pricing strategy may no longer be effective for optimizing revenue as ingredient costs, market preferences, labor expenses, and seasonal specialties change. Despite its value as a partial indicator of market conditions, individual price elasticity is often out of sync with many important internal and external factors. It is also possible that traditional dynamic pricing, aimed at discounted happy hours, peak surges, and event offerings, doesn’t adequately reflect business conditions.

A recent technological initiative that integrates artificial intelligence (AI) with dynamic pricing includes supply chain, day part, competitive scaling, weather, and customer preferences. Data sets and real-time analytics can be automatically applied to suggest price adjustments. Recently, several tech providers began offering AI solutions that streamline restaurant operations, enhance decision-making, and improve pricing using smart rules and algorithms.

Traditionally, dynamic pricing models, designed to help restaurants remain competitive and profitable, tend to focus on predictable market conditions of supply and demand. The recently released 2025 FSTEC Insider Report claims traditional dynamic pricing is no longer sufficient and may be becoming irrelevant. The report cites the fact that menu prices based purely on demand shifts ignore the fact customers often develop emotional attachment to restaurant prices. Upgrading the application with AI-based decision rules enables data collection, and analysis, from a variety of sources. The goal of AI-based dynamic pricing is to enhance sales, frequency, profitability, and customer satisfaction. This vibrant approach, often used in the airline and hotel industries, is now being adopted by restaurants hoping to optimize both revenue and customer satisfaction.

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