Airlines understand the value of selling ancillaries – those beneficial add-ons such as premium pricing for extra leg room and charges for once-free items like baggage, headphones, meals and even pillows and blankets.
Ancillaries have provided much-needed revenue for airlines in recent years, so much that they have taken selling these add-ons a step further by using product bundling – where, for example, they might combine a seat, wireless Internet and a beverage of choice for a single price.
Yet greater opportunity awaits airlines in the ancillary business. By adopting some traditional Revenue Management strategies – as well as the latest advances in bundling analytics – airline executives can push ancillary revenues to even loftier heights.
The flight path to ancillary optimization includes:
- Ancillary Demand Forecasting – leveraging customer data, historical ancillary purchases, competitive pricing, and utilizing the latest statistical demand forecasting models provides airlines with the ability to predict demand for ancillary products at a granular level and across their network;
- Price Sensitivity Modeling – developing sophisticated market response models to explicitly measure price sensitivity and predict consumer response to price changes. Additionally, developing price elasticity curves at an airline day-of-week/booking window level allows airlines to truly measure the demand and return on investment of each ancillary. Once complete, incorporating elasticity into the forecast will help to create a price sensitive forecast;
- Ancillary Price Optimization– combining critical optimization inputs such as the demand forecast, price elasticity, and competitive pricing are essential to produce the optimal ancillary price and better manage the required inventory of a specific ancillary product.
These Revenue Management strategies can work for airlines because they have worked for other industries, such as our collaboration with a global hotel operator with more than 4,000 properties worldwide. Revenue Analytics developed an innovative price optimization model that facilitated informed, yet dynamic pricing decisions at the hotel level, and provided corporate pricing guidance overall. This next‑generation Revenue Management system produced an annual 2.7 percent revenue uplift for the hotel company.
In addition, a leading national automotive retailer, operating more than 120 dealerships faced increasing challenges in their underperforming Finance and Insurance (F&I) business. Tasked with helping the client improve profits and business processes, Revenue Analytics leveraged Revenue Management capabilities which dynamically recommended F&I products and prices for each customer based on their automobile purchase. For the client this solution generated a 7% increase in gross Finance & Insurance profits, and improved product penetration by 6%.
Leveraging predictive analytics for both the global hotel operator and national automotive retailer produced immediate organic growth opportunities.