What Is Dynamic Pricing?
The price tag is a suggestion
Walk into a grocery store and everything has a fixed price. A can of beans costs $1.29 today, tomorrow, and next week. But open a ride-sharing app during rush hour and you’ll notice something different: the price changes. It responds to demand, supply, time, and context.
This is dynamic pricing — the practice of adjusting prices in real time (or near real time) based on market conditions.
Where you already see it
Dynamic pricing is not new. Airlines have done it for decades. A seat on a Tuesday morning flight in November costs a fraction of the same seat on a Friday evening in December. Hotels, electricity markets, and concert tickets all follow similar patterns.
What is new is the scale and sophistication. With modern data infrastructure, even small e-commerce shops can implement pricing strategies that used to require teams of revenue analysts.
“The right price is whatever someone is willing to pay” is a common oversimplification. In practice, dynamic pricing tries to find the price that maximizes a specific objective — revenue, profit, or market share.
The core idea
At its simplest, dynamic pricing asks:
- What is the current demand?
- What is the available supply?
- What price maximizes our objective given the above?
The “objective” varies. An airline might optimize for total revenue across all seats. A ride-sharing platform might optimize for market balance — enough drivers on the road to keep wait times low.
What this series will cover
Over the next few posts, we’ll build up from basic economic intuition to working pricing models:
- Demand curves and price elasticity
- A simple pricing model in Python
- Multi-product pricing and cannibalization
- Real-time pricing with bandit algorithms
No PhD required — just some comfort with Python and basic statistics.
A word of caution
Dynamic pricing is powerful, but it comes with real ethical considerations. Surge pricing during emergencies, price discrimination that disproportionately affects certain groups, and opaque algorithms that customers can’t understand — these are all active areas of debate.
We’ll touch on these issues as they come up. Good pricing isn’t just about maximizing a number.