Born in the 80s
Airlines have long been pioneers in pricing and revenue management. In fact, back in the 1980s, the use of dynamic pricing was kickstarted by the aviation industry.
Rather than let the value of seats drop to zero, airlines began offering discounted fares for last-minute travellers. The objective was simple: minimise the number of empty seats to boost revenue.
Revenue management today
Today, the overall objective remains the same: maximise revenue. But the means of doing it have become significantly more complex.
We might describe revenue management as the science of maximising revenue – by setting the right price, at the right time, for the right passenger.
This means pricing fares in accordance with factors like seat capacity, flight schedules, traveller type and competitor prices – to name a few. Simple in theory, complex in practice. And today, it’s more complex than ever.
Whilst the industry at present is recovering from the impact of the COVID pandemic, passenger rates are set to rise higher and higher over the long term. And as demand increases, so too does complexity. More passengers, more types of passengers and more destinations mean pricing complexity adds up fast.
“So, how many seats do we sell at a discount?”
This brings us to the age-old question: how many seats should you sell at a discount? I’d argue that, in today’s market, it’s no longer the best question to ask. As dynamic pricing evolves - along with the technology that powers it - pricing is becoming ever more personalised.
Of course, there will still be “discounts”. But, the meaningful question for dynamic pricing has shifted from seats to customers. The new question? How much is this specific customer willing to pay for a seat?
The value of a seat
The same seat has a different value for every customer. Business flyers are happier to pay higher fares than holiday-makers. And they’re happier to pay for add-ons that maximise flexibility, like refundable tickets. Whereas holiday-makers book further in advance and are more sensitive to price.
Yes – this doesn’t scratch the surface of the factors in play. But, it does highlight the importance of catering to the unique needs of different customer segments in dynamic pricing models. And companies today have access to more data on buying habits than ever.
But, for some time now, it’s been difficult to unlock the value trapped in the newfound treasure trove. That’s exactly where an AI-powered price optimiser can help.
How an AI price optimiser can help
The next paradigm of dynamic pricing will have AI at its core. And for good reason, too. Working in harmony with humans, AI can explore millions upon millions of potential solutions to the pricing conundrum.
Here are a few ways it’s set to benefit airlines.
1. Increase revenue
At the risk of stating the obvious, the core benefit of using an AI-powered price optimiser is that it can maximise revenue. It does so by finding the highest ticket price for which there’s likely to be demand. With the ability to analyse millions of potential prices - evaluating using dozens of parameters: flight capacity, competitor prices and time remaining to book - AI produces extraordinary results. Quite simply, the shift towards AI is ushering in the next generation of dynamic pricing.
2. Gain insight
Knowing why AI makes decisions enables better collaboration between humans and machines. AI should have explainability built-in; in other words, it should be able to clearly tell you why it’s made the pricing decision it has. Not only is this crucial knowledge for pricing analysts and revenue managers, but the legal requirement for AI to be explainable is growing too.
3. Continually improve
AI has the ability to intelligently and automatically analyse and learn from the past, compare it to the present, and make informed decisions based on this learning. This is reinforcement learning, and it is a key tool in a modern dynamic pricing solution’s arsenal.
4. Enhance existing platforms
A good AI-powered revenue optimiser will complement an airline’s existing revenue management system. It shouldn’t be a case of replacing or replatforming; rather, it should be about enhancing. We often hear this concern from those in strategy, operations or innovation roles, but in reality, there’s nothing to worry about. Successful AI solutions need good quality underlying data, something existing revenue management systems can provide, and they need to be tailored to address specific challenges, something off-the-shelf solutions struggle with.
Airlines have been pioneers in dynamic pricing for decades – and that’s not set to change anytime soon. The next paradigm of pricing for airlines will see AI take a central role.
And those working in revenue, strategy & tech roles will drive the change.
In 2023 the value trapped in data will start to be unlocked by AI – those who embrace it are set to reap the rewards.