You may search for a flight today at one price, then return to it later and find that the price has changed. You may also request a car at 5 p.m. for one price, only to find that nearly the same trip costs more after an event has ended or during peak hours.

The product has not changed much, but the price has changed.

This idea is called dynamic pricing: a company adjusts its price in response to changing market conditions instead of keeping it fixed all the time. But why would companies prefer a price that moves in the first place?

When time is part of the product

An empty seat on a plane that has taken off cannot be stored and sold tomorrow, nor can a hotel room that remained vacant last night. That is why these companies try to make the greatest possible use of limited capacity whose value expires over time.

Price then becomes a tool for managing demand.

If demand for a flight rises as its departure approaches and only a limited number of seats remain, the price may increase. If demand is weak, lowering the price may help attract more buyers.

In the airline industry, the International Air Transport Association (IATA) explains that dynamic pricing can take into account information related to the purchase, such as the time remaining before travel, the departure and arrival dates, competition, and the capacity remaining for sale. It also notes that airline pricing has been dynamic in various forms for decades, while modern technologies allow offers and prices to be adjusted more flexibly and in real time.

So here, price reflects not only the cost of providing the service, but also the value of the resource at a particular moment and the strength of demand for it.

When price is used to change behavior

Ride-hailing apps offer a clearer example.

When a large number of passengers request cars in a particular area while few drivers are available, prices rise under the surge pricing model. According to Uber’s explanation of its model, the goal is to rebalance demand and driver availability: the higher price may encourage more drivers to head to the area, while some passengers may decide to wait until demand subsides.

This is where an important economic point arises: price does not merely describe the market; it helps change it.

A higher price signals that the resource has become relatively scarce. Some consumers accept the price, others postpone their purchase, while providing the service becomes more attractive to suppliers.

That is why dynamic pricing can be a tool for managing imbalances between supply and demand, rather than simply a way to raise prices.

But does every customer get a different price?

This is a common misconception.

Dynamic pricing does not necessarily mean that a company knows you are someone willing to pay more and automatically decides to charge you a higher price. The price may change because of timing, demand, available capacity, competition, or market conditions, even without knowing the buyer’s identity.

This differs from personalized pricing, which relies more heavily on characteristics or information associated with the consumer themselves.

The distinction matters because two people may pay different prices for the same trip simply because they purchased at different times—not necessarily because the company decided that one of them was wealthier than the other.

Where does the company gain?

The idea is not for the company to always set the highest possible price.

If it raises the price too much, it may lose the customer and leave a seat or room unsold. If it lowers the price too much when demand is strong, it may sell a limited resource for less than the market was willing to pay.

So it tries to find the right price for the right circumstances.

This is part of a broader concept called revenue management: using price, available capacity, and demand forecasts to improve revenue from a limited resource.

This is where data and technology become valuable. The better a company can understand demand patterns, remaining capacity, and market changes, the more responsive its pricing decisions become to reality.

Where does the problem begin?

What seems logical to the company may not seem fair to the consumer.

The customer sees the same service but may find a different price within a short period. If they do not understand the reason for the difference, they may feel that the price is arbitrary or that they are being taken advantage of when their need is greatest.

This is one of the most important trade-offs in dynamic pricing: efficiency versus trust.

Variable pricing may help a company distribute demand and improve the use of its capacity, but excessive use or a lack of clarity around it can damage customer trust. The issue becomes more sensitive when prices rise in circumstances that consumers cannot easily avoid.

There is another, less obvious aspect related to competition. As companies increasingly rely on pricing algorithms, concerns arise that some uses of these algorithms could facilitate algorithmic collusion or reduce the intensity of competition. The existence of an algorithm does not in itself mean that collusion is taking place, but the regulatory question becomes more complex when systems make pricing decisions rapidly and based on market and competitor data.

What about Saudi Arabia?

The idea is highly relevant to Saudi consumers. Airlines, hotels, and app-based transportation are all sectors in which demand changes according to seasons, holidays, events, and peak times.

Data from the General Authority for Statistics illustrates how much capacity utilization can vary in the hospitality sector itself: the hotel room occupancy rate in the Kingdom reached 63% in the first quarter of 2025, while it stood at 49.1% in the third quarter of the same year. These figures are not direct evidence of changing prices, but they illustrate the environment in which businesses with limited capacity operate and demand for that capacity changes over time.

As tourism, events, and digital services expand, the ability to forecast demand, manage capacity, and set prices becomes a more important part of business decisions, especially in activities whose unused capacity cannot be stored and sold later.

What happens when the algorithm knows more?

The most interesting development may not be faster price changes, but rather the information that can be used to determine the price.

Traditional dynamic pricing may consider demand, timing, and available capacity. Personalized pricing, however, goes a step further by potentially relying on information related to the consumer and their behavior to tailor the offer or price.

As data analytics and artificial intelligence advance, the boundaries between the two models become more important. The question will not only be: Did the price change? It will also be: Why did it change, and what data was used to determine it?

This is where transparency becomes part of the economics of pricing itself. An algorithm may be able to determine the price that maximizes revenue more accurately, but the company must also preserve customer trust and comply with competition and consumer-protection rules.

Price has become information

Ultimately, dynamic pricing changes the way we think about price. Price is no longer always a fixed number placed on a product; it can become a signal that moves with time, demand, and available capacity.

For the company, the challenge is to use this flexibility to improve revenue and manage demand without losing the customer. For the consumer, knowing that prices move explains why when you buy can sometimes matter as much as what you buy.

This is where the paradox lies: technology can make prices more economically precise, but it does not necessarily make them fairer in everyone’s eyes.