Continuous pricing and dynamic ancillary pricing
In short: Continuous pricing and algorithmic ancillary prices capture more value only when tested, measured and governed before scaling. Here is how to do it.
Written for: Airline revenue management, pricing, ecommerce and retailing leaders.
A pricing algorithm without a good experiment behind it does not optimise revenue: it optimises the team's confidence in the algorithm.
From fare classes to continuous pricing
For decades, airline pricing has been built on a limited number of booking classes. Continuous pricing allows any price point to be set based on demand and context, and algorithmic pricing extends that logic to seats, baggage and other services.
At the World Aviation Festival 2026, Lufthansa Group shares lessons under the title "Proof before scale" on making continuous pricing pay, and other sessions cover next-generation ancillaries with algorithmic pricing, price automation as part of modern retailing, and dynamic bundling.
What changes for the direct channel
Price is no longer a table
With continuous prices and dynamic offers, the direct channel shows prices generated at every search. This requires the website, app and measurement systems to understand offers rather than filed fares, one of the shifts described in the differences between NDC, ONE Order and PNR.
Ancillaries become contextual
The same seat or bag can carry different prices depending on route, lead time, load or profile. Done well, it lifts conversion and revenue; done badly, it creates a perception of arbitrary pricing. The fundamentals are in how to increase airline ancillary revenue.
Bundles built in real time
Dynamic bundling combines flight and services based on what the customer values, extending the logic of airline offer personalisation and bundles.
Why prove before scaling
Pricing models learn from the data they generate: if they are deployed without a control group, it is impossible to know how much revenue comes from the algorithm and how much from the market. Airlines that get sustained results share three practices:
1. Experiments with a control group. Routes, markets or traffic shares where the algorithm does not set the price, following the principles of an ecommerce experimentation programme.
2. Total revenue metrics, not product metrics. A pricier ancillary can reduce flight conversion.
3. Guardrails. Price limits, cross-channel consistency and explainability to customers and regulators.
Risks to anticipate
Perceived unfairness: variations customers do not understand and share on social media.
Cross-channel inconsistency: different prices for the same product on the website, app and agencies.
Regulatory change: transparency of prices and extra charges is under scrutiny in several markets.
Black-box dependency: if nobody in the organisation understands the model's decisions, nobody can correct them.
Indicators for deciding whether to scale
Revenue per passenger versus control group.
Flight and ancillary conversion.
Ancillary take-up rate by segment.
Price-related complaints and contacts.
Stability of results across seasons.
Conclusion
Continuous pricing and algorithmic ancillary pricing can increase revenue per customer, but only when they are tested rigorously, measured on total revenue and governed with clear rules. Scaling without that foundation turns a retailing opportunity into a commercial and reputational risk.
Consumer Services Hub helps airlines design and measure pricing and retailing strategies in the direct channel.
Consumer Services Hub - Strategic ecommerce consultancy for B2C service companies
Written by
Rodrigo MarotoFounder of Consumer Services Hub. Consultant and strategist with 15+ years of experience in ecommerce, digital product management, and consumer services.
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