Recent popular events and experiences such as the solar eclipse and Taylor Swift's tour have put a spotlight on changing digital models for ticket sales at giant scale. At the heart of this lies the concept of "dynamic" ticket pricing, a model that sees prices rise or fall dynamically according to levels of real-time demand.
For Swift’s 2018 Reputation Tour, dynamic pricing was part of a strategy aimed at combating the huge volumes of ticket "scalping" and secondary market sales. The strategy was effective in that aim but also caused some controversy, with knock-on effects around ticket availability and unprecedented demand crashing ticketing sites.
Fast-forward and the record-breaking 60 show, 4-million-plus ticket "Eras Tour" has netted sales of more than $1 billion - and crucially delivered a more nuanced and selective use of dynamic pricing, catering to varied fan priorities and budgets.
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All of this puts the spotlight on the retail and customer experience opportunities and challenges presented by dynamic pricing, as it appears operationally across many industries, whether that’s concert tickets, airline seats, commuter rail fares or even buying a meal and a round of drinks.
A more recent example is Monday's total solar eclipse, which presented airlines, and accommodation providers, with an opportunity to capitalize on an event that has almost 32 million living along its path. Meanwhile, Delta Airlines scheduled two flights to Detroit, to provide passengers with "optimal views" of the event.
What’s new? Toward real, dynamic airline pricing
You might think that none of this is new news for the airline business. But existing airline applications commonly dubbed "dynamic pricing" are not really dynamic at all, relying on static, pre-determined pocketed allocations of class fares and simple plug-in tools to manage their allocation. In simplistic terms, once a pocket sells out at a certain price point, prices get bumped up into a higher price allocation band, which may (or problematically, may not) sell out.
The first knock-on impact here lies in the perception that airlines unfairly rely on basic "surge pricing" - matching spikes in demand to crude price increases, a model that many feel punishes the average customer, who may have no choice but to travel during peak periods or not fly at all. The second impact lies in levels of unsold, higher-priced ticket inventory, a situation in which both customers and airlines lose out.
By contrast, real dynamic pricing could be transformational for airlines and really benefit their customers. But as it becomes a boardroom hot topic in the light of lower industry margins, airlines need to think of this as an opportunity to maximize conversion, not simply a new device with which to hike prices.
Real dynamic pricing models generate pricing options intelligently, automatically, and in real time, based on airlines' direct interactions and deep knowledge of their customers. That means better personalized offers and packages to ensure better customer loyalty, better value for customers and for airlines, lower levels of unsold ticket inventory.
To make this work, airlines need far better knowledge of who their customers are, what they are individually willing to pay and to then better match unsold seats to customer needs and price points.
Delivering on the promise
The solution lies in a shift from blunt price hikes to a data-driven, personalized approach. And that depends on modern technology foundations.
First, the technology platforms the industry relies on need to be able to ride the dynamic pricing roller coaster - handling rapid price changes at scale and accommodating diverse pricing without technical glitches or delays. That means delivering dynamic pricing at every request, with an open architecture that delivers scale and integration with the wider world of new distribution capability (NDC) and modern airline "offers and orders" retailing. The legacy software and deployment environments airlines operate often may not be fit for purpose in this regard.
Secondly, a key dimension of realizing real dynamic pricing means leveraging advanced analytics to predict willingness to pay, segment passengers based on preferences and dynamically adjust fares in real time to match specific needs and price sensitivity. Imagine an airline offering a flexible business traveler willing to pay extra for last-minute upgrades at a considered and interesting personalized price, while simultaneously presenting a budget-conscious student with enticing deals on less popular travel times.
This format is dynamic, with pricing changes uniquely based on a whole range of factors like time of purchase, customer qualities such as loyalty, age, purpose of travel and the customer’s overall shopping context. This format is intelligent in that each of these contributing factors impacts pricing differently and to varying degrees, without a strict adherence to predetermined values. Automation through advanced analytics, machine learning, and artificial intelligence are key to realizing this opportunity.
From pipe dream to new generation distribution pipeline
None of this is achievable without digital infrastructure that can analyze and react to real-time market and customer conditions. Legacy airline software and systems, however, commonly deliver little insight about individual customers and are unable to recognize and adapt to buyers.
Replacing legacy technology with capabilities able to understand customers’ preferences and habits is a critical step toward implementing successful dynamic pricing, whether for seats or wider services or travel experiences. The "Taylor Swift effect" points to dynamic pricing as a mainstream consumer experience, with customers increasingly becoming attuned to sophisticated, personalized offers, pricing and engagement. One thing’s for sure - dynamic pricing will become a "must have" not just a "nice to have" pipe dream.