The customer travel buying experience is centered around two major decisions:
- the itinerary they want to take based on the schedule and price, and
- the extra features, or ancillaries, that they want to include.
You can read all about the value that number 1 provides for maximizing airline revenue through dynamic pricing here. This article will discuss number 2—ancillaries. The combination of 1 and 2 together make up what we call Airline Offer Optimization. It’s the process of optimizing the total offer that is presented to the customer and ensuring the most revenue potential is recognized for the airline.
Defining Airline Ancillary Optimization
As the focus is turned to ancillaries, it’s important to highlight where the value comes from to the airline, as well as to customers. The three key areas that define the PROS approach to Dynamic Ancillary Pricing are: ranking, bundling, and pricing ancillaries. Each one of these can drive incremental revenue benefits for the airline, while bringing a better customer experience for the passenger making the purchase.
For many airlines, there are a lot of ancillaries for a passenger to choose from. Simply the order in which those are displayed to the passenger can have a significant impact to the buying behavior and the likelihood of conversion. There are a few reasons why this is important:
- Choice: In many cases, the passenger is fatigued with the long catalog of optional products and services once presented with too many options. Thus, airlines need to focus on relevance rather than quantity to make it easy and fast for customers to choose and purchase.
- Order and willingness-to-pay: The customer may have a limited amount of money available to spend on ancillaries, so the order in which they are displayed can ensure that the airline maximizes revenue by presenting the ancillaries in the right order. For example, let’s say that an airline has Wi-Fi for $8, drinks for $10, and Seat Selection for $25. And let’s assume that the passenger has $30 she’s willing to spend on ancillaries. Depending on the way the airline presents this to her, if she chooses Wi-Fi and a drink pass, the airline will make $18 in revenue, but the passenger is out of money to spend. However, if presented with Seat Selection first, she would have made that choice, giving the airline $25 in revenue.
- Segmentation: Customer characteristics dictate different likelihood of buying certain ancillaries. Something as simple as market characteristics, like a beach destination, could be important to consider and ensure that ancillaries like golf bags and surfboards are presented first to lead to better conversion.
PROS AI has been used to optimize ancillary ranking in a live airline trial, driving 0.5% conversion uplift and proving that this is just the starting point for driving revenue growth with PROS Dynamic Ancillary Pricing.
Building on the momentum from ranking, the natural next step is to upsell by grouping ancillaries together in bundles with a higher likelihood to purchase. This can be done with or without changing the price. The perception of getting a bundle alone can lead to higher conversions.
Imagine the customer was presented with a bundle of Wi-Fi and Seat Selection for $33. Despite having a total willingness-to-pay of $30, seeing a bundle could be enough to entice the passenger into spending the extra $3. Paired with the right data, the price for the bundle could even be adjusted if the data supported that decision, to ensure conversion. As with ranking of ancillaries, the right science and customer segmentation through their attributes is critical to maximize ancillary revenue.
Dynamic Ancillary Pricing (DAP) is where things get exciting and the real revenue opportunity for the airlines comes to light. The concept of DAP is to leverage AI to dynamically set the price of ancillary products based on static dimensions (like day of week), market conditions, and/or customer attributes.
Historical information is obviously important to driving what you should do in the future. Airlines that have been deploying robust rule-based merchandising techniques through PROS Offer Creation solutions or other, are well poised for AI-based ancillary optimization.
airBaltic is one of the carriers, that leverages PROS merchandising technology to fully manage a dynamic ancillary catalogue and personalize offers based on granular customer and market segmentation. Today, the airline is advancing their eCommerce with AI-fueled seat assignment pricing:
However, what do you do if your historical data has little or no variability, because you’ve only presented static ancillary catalog? For example, let’s say that for Seat Selection, you have only ever charged $25. Any predictive model is simply going to take in the observations of $25 and suggest a price of, you guessed it, $25. That’s not revenue optimal.
This is where artificial intelligence and the idea of re-enforcement learning models come in. You must pair the predictive element of the AI with an inferential element. That means you need to intentionally introduce variability into the price, in a very controlled way. Those prices are then used in the model to update what the right price is for the given dimensions, market conditions, and/or customer attributes. The model can then quickly learn, or infer, through the interactions of the different observations what the right price is for the particular request, and customer. The AI behind this is cutting edge for the airline industry and ready to be deployed to help airlines drive better ancillary pricing.
Of course, you can come up with the best prices for ancillaries but getting those to your passengers efficiently is just as important and PROS can help in that area too. Combining the power of PROS Dynamic Ancillary Pricing with our Offer Creation and Retailing solutions creates the end-to-end solution. It receives the request from the airline.com, makes the call to the merchandising system, responds with the dynamic bundle and price, and returns that to present to the customer, all in an integrated workflow. The result - Offer optimization delivered.
Do you think this sounds interesting? Contact PROS at firstname.lastname@example.org and let’ talk ancillary optimization through AI.