What is Dynamic Pricing?

A pricing strategy where businesses set prices for products or services that can change according to the market, customers, competitors, and other factors. Prices are set to change at the time of purchase or at pre-set intervals to enhance revenue and profitability.

Key components:

Algo-based price changes, real-time data analysis, customer segmentation, demand planning, competitive benchmarking, material / inventory level watch.

Common applications:

Airlines (price changes according to availability of the seat, time of the year, and demand), Hotels (rates are subject to change depending on the occupancy, season, and events), Ride sharing apps (surge pricing during peak hours), E-commerce sites (price of the product changes according to the user’s browsing history and the stock), Venues that sell tickets (price of the tickets vary according to popularity and time of the year), Utility companies (time of use pricing).

Implementation methods:

ㆍRule-based pricing: Price changes are triggered by predefined rules.
ㆍMachine learning: AI systems that learn from patterns and optimize the pricing.
ㆍSegmented pricing: Different prices for different customer segments.
ㆍTime-based pricing: Price changes at specific times according to time patterns.
ㆍCompetitive-based pricing: Price changes based on the actions of competitors.

Best practices:

ㆍOpenness in the handling of the pricing policies.
ㆍSetting some price ranges to avoid extreme fluctuations.
ㆍAlgorithm testing and optimization should be done on a regular basis.
ㆍEnsuring that there is enough market data to analyze.
ㆍThe conflict between the company’s revenues and the customers’ comfort.
ㆍGradual change is better than a sudden change in the price.