Pricing strategies: dynamic pricing

A pricing strategy sets how an organisation charges for an offer and must fit the product, channel and promotion choices around it. Dynamic pricing is the controlled adjustment of price in response to time, demand, available capacity, market conditions or other declared rules. It can improve capacity use and revenue, but it also creates fairness, trust and governance risks.

When to use it

• Decide how much to charge for a new product or service.

• Understand the economics and likely response behind competitors’ prices.

• Identify lawful opportunities to improve contribution or capacity utilisation.

• Adapt prices when demand, supply or time-to-expiry changes materially.

• Avoid or constrain it where customers cannot understand the rules, vulnerability is material or price stability is part of the promise.

Origins

Pricing theory developed in microeconomics around the relationship among price, output and profit. Business practice added differentiated offers, customer willingness to pay, cost changes and game-theoretic responses to competitors.

Dynamic pricing long predates the internet: transport, hospitality and other capacity-constrained sectors varied prices by season, booking time and availability. Airline revenue-management systems made the practice more systematic. Internet commerce then accelerated data collection, price transparency and automated changes, allowing many industries to update offers rapidly.

What it is

A pricing strategy normally reflects three broad conditions: the business’s economic objective, customer demand and alternatives, and competition. Common approaches include:

• Target-return pricing: set price to support a required return on investment.

• Cost-plus pricing: add a defined margin to a chosen cost base, common in some procurement and established categories.

• Value-based pricing: relate price to customer outcomes and alternatives rather than cost alone.

• Psychological pricing: consider quality signals, reference points, prestige and perceived fairness.

Over the last 15 years, digital dynamic pricing has become especially visible as another approach. It is well suited to perishable capacity such as airline seats, hotel rooms and holiday bookings. Once a departure or night passes, unsold capacity cannot be stored; the provider tries to balance price and the probability of sale.

Dynamic pricing is not necessarily personalised pricing. A public room rate that changes with occupancy differs from a price calculated from an individual’s identity or predicted willingness to pay. The latter requires stronger justification, privacy controls and fairness review.

How to use it

Define the unit, objective and constraints. For a hotel room, the decision may seek contribution across the stay date while protecting minimum margin, contractual commitments, brand positioning and customer rules.

Estimate demand by booking horizon, season, events, channel, room type and remaining capacity. Include cancellations, no-shows and competitor conditions where lawfully obtained. A rate set too low may leave value unclaimed; one set too high may leave the room empty. Near the stay date, low remaining demand can justify a discount, while scarce capacity can support a higher price.

Build clear decision rules or a validated model, then set floors, ceilings, rate-of-change limits and circumstances requiring human review. Pricing “bots” can execute decisions, but owners must monitor errors, feedback loops and competitor interactions. An automated system should be auditable and reversible.

Test with controlled exposure. Track revenue and occupancy together with cancellations, repeat purchase, complaints and distributional effects. Explain the principal pricing conditions in terms customers can understand. Review applicable consumer, competition, discrimination, privacy and sector rules with qualified specialists.

Amazon.com is often cited as an early online experimenter and low-cost airlines such as Easyjet.com and Southwest Airlines as early industry users. Treat those labels as historical illustrations rather than current descriptions of proprietary systems.

Top practical tip

Start with customer value and the capacity that expires, then define transparent drivers, floors, ceilings and monitoring. Optimise the combined economic and customer outcome rather than the highest price obtainable in one transaction.

Top pitfall

Frequent, opaque or personally targeted changes can feel arbitrary and teach customers to wait. Do not hide cheap capacity merely to obscure the rule, or allow automated competitor matching to operate without legal and human oversight.

Further reading

• Talluri, K.T. and van Ryzin, G.J. (two thousand and four). The Theory and Practice of Revenue Management. Springer.
• Phillips, R.L. (two thousand and five). Pricing and Revenue Optimization. Stanford University Press.