Dynamic pricing is made possible by the use of sophisticated algorithms that analyze large amounts of data in real time to determine the optimal price for a product or service. These algorithms take into account a wide range of factors, including customer behavior, economic conditions, and supply chain factors, to determine the right price at the right time. AI can make dynamic pricing easier and better, as it facilitates continuous prediction, allowing for pivots for events in real-time.
Dynamic pricing is a common practice in several industries such as hospitality, tourism, entertainment, retail, electricity, and public transport.
Methods
- Time-based pricing
- Inventory-based pricing
- Demand-based pricing
- Competitor-based pricing
- Location-based pricing
- Personalized pricing
Challenges
- Complex algorithms
- Customer perception
- Competition
- Legal and regulatory considerations
- Data quality and accuracy
