7 Myths of AI-Powered Pricing Demystified
Airlines have concerns and incorrect assumptions about the role of AI in powering the future of pricing. In this blog, we share insights from airline questions to Datalex regarding the role of AI in transforming airline pricing for the better, and for better revenues.
True AI-powered pricing, that eliminates rules and automated tasks, is a relatively new concept and is not fully understood industry-wide. Conor O’Sullivan, Chief Product Officer at Datalex and Navin Gupta, Product Manager for Pricing AI were on hand to answer burning questions, demystify some of the myths and addressing concerns that airlines have about AI-powered pricing.
Myth #1 – AI-powered pricing will replace my revenue management team
While some industry providers claim they will replace revenue management functions entirely, Datalex knows this is not what the industry needs. With Datalex Pricing AI, instead of replacing, we work collaboratively with airline revenue management teams to enhance what they do today, except in real-time and at scale.
Myth #2 – The airline will lose all control of its pricing strategy
We know from Datalex’s own research with airline executives that 93% of airlines say it is important to retain an element of control with AI-powered pricing so that the pricing strategy supports strategic objectives such as those to enter new markets, remain competitive, ensure customer loyalty, gain new customers, and maintain brand reputation. It’s important that an AI-pricing product is transparent the airline is satisfied that a degree of control is retained through supervising and monitoring techniques that give airlines peace of mind that they are very much still in control of their pricing strategy.
Myth #3 – Our airline will run into privacy / consumer rights issues with personalised pricing
This is a common misconception with AI-powered pricing and this concern is assuaged by the fact that we do not incorporate customer willingness to pay in order to sell the same product at different prices. The aim should be not be ‘personalised pricing’ in the strictest meaning of this; this aim should be ‘optimal pricing’ for optimal conversion dependent on demand and other inputs. This is the approach we have taken with Datalex Pricing AI, which is based on the concept of efficiency, in that the customer benefits from the optimal price based on market conditions at any given moment and this is beneficial to the airline because it is the most efficient price. For this reason, instead of mistakenly believing that AI-powered pricing is a customer-specific endeavour, it should be thought of as customer-centric as it is the most efficient price for any customer at any given moment. AI-powered pricing should be customer-centric, not customer specific.
Myth #4 – Our airline can make the best pricing decisions quick enough because we know our business and our customers
What your airline does today is most likely a limiting price decision-making process that tracks demand and does not take real-time competitor pricing and customer segmentation into account. Once revenue management teams consider and deal with each input and constraint, they must immediately start all over again. Thus, creating a trade-off between accuracy and speed which is a vicious circle with current revenue management processes, and a significant hindrance to an airline’s ability to react. A revenue management team cannot process all relevant demand factors, competitive insights and suggest the most optimal price at every given moment. Some products, like Datalex’s Pricing AI product, can process all inputs at any moment – within 200 to 500 milliseconds to be exact.
Myth #5 – Our airline data is exposed, we will be exposing our data to other airlines
It’s a common misconception that AI is a generic tool used across customers, but powerful, intelligent AI tools are uniquely trained and completely bespoke to each airline because it leverages an airline’s proprietary data and no other.
Myth #6 – We don’t have the internal resources needed to integrate with our revenue management system / We don’t know or have the right AI expertise
Internal resources and a lack of AI expertise are cited by airlines as obstacles to overcome in implementing AI-powered pricing. What is different about AI is that it is built on scalable, easy-to-integrate technology that is a huge change from existing legacy systems. Despite the technology being SaaS based, AI-powered pricing products still integrate seamlessly with existing legacy systems and an airline’s existing Revenue Management tools and processes.
AI education and awareness must not be underestimated. It’s important for airlines to trust technology and experienced technology providers like Datalex to fully embrace the potential of AI and lean on AI experts in the process to bring them along on this journey.
Myth #7 – Our revenue management team will not learn anything if they hand all the data over
It is important for Revenue Management to feel close to and involved in the AI process. To this end, we at Datalex work closely an airline’s revenue management team directly when models are trained initially. Decisions made by models which are reviewed with Revenue Management teams to assure them that it works as expected. We do not take a “big bang” approach and we always advise deploying the product initially into a small number of markets. AI adoption is a journey.
Summary
Beyond the obvious revenue tailwind that AI-powered pricing represents (which has been proven to increase revenue by 2% – 3.82% in Datalex production trials), there are many more opportunities for airlines to stay competitive in-market.
With demand patterns ebbing and flowing, customer confidence changing like the wind, geo-political issues and staff shortages – all industry-wide problems – airlines must have a dynamic, fast acting product that they trust is ready to react at any given moment to such a an ever-changing travel landscape. environment.
Many airlines are keen to start their AI-powered pricing initiatives, but it must be seen as a journey that is taken in steps, with existing revenue management teams in control every step of the way.
Conor O’Sullivan, Chief Product Officer at Datalex
Navin Gupta, Product Manager for Pricing AI