The world has and continues to suffer sizeable losses and setbacks due to COVID-19. Industry leaders are seizing the crisis as an opportunity to enhance the current seamless travel experience and embrace the integration of new technologies to meet the new customer demands whilst increasing revenue contributions and spend per head.
Yield management as part of an overall revenue management strategy is a key component of this approach. Organisations are recognising that legacy systems are not equipped with the functionality to optimise upsells, cross-sells, promotions, with many lacking a revenue and yield management tool.
Legacy systems are often complicated and technically deficient. For instance, revenue managers must manually tweak prices, limiting the agility of the dynamic pricing approach. The problem extends to other operations as well. Demand forecasting may be based on simple methods like “the-last-year-demand.”
Due to old software performance or a reliance on manual processes, data processing can be delayed. The information on inventories and manifests are frequently inconsistent because the revenue management function is often disparate from any access systems – which can again be a manual tick-list.
These problems lead to inefficient pricing and timing, which results in under performance and potential revenue losses. With the emergence of sophisticated ticketing and booking platforms organisations can prevent overbooking and selling below costs.
Yield management (YM) and revenue management (RM) apply analytics to predict demand and other consumer behaviour and optimize attendance and price. In other words, they are utilised to “sell the right product; to the right customer; at the right time; at the right price”, according to the definition of Robert Cross, the theorist behind airline revenue management.
This is a complex task embracing several components that are shaped by demand, market conditions, customer behaviour, and demographics.
Industries that use yield management include airlines, hotels, stadiums and other venues with a fixed number of seats or capacity. With an advance forecast of demand and pricing flexibility, buyers will self-sort based on their price sensitivity (using more power in off-peak hours or going to the theater mid-week), their demand sensitivity (must have the higher cost early morning sightseeing tour or must go to the Saturday night opera) or their time of purchase (usually paying a premium for booking late).
In this way, yield management's overall aim is to provide an optimal mix of goods at a variety of price points at different points in time or for different baskets of features.
Good yield management maximizes (or at least significantly increases) revenue production for the same number of units, by taking advantage of the forecast of high demand/low demand periods, effectively shifting demand from high demand periods to low demand periods and by charging a premium for late bookings. While yield management systems tend to generate higher revenues, the revenue streams tend to arrive later in the booking horizon as more capacity is held for late sale at premium prices.
Firms faced with lack of pricing power sometimes turn to yield management as a last resort. After a year or two using yield management, many of them are surprised to discover they have actually lowered prices for the majority of their opera seats, sightseeing tour or ferry crossing occupancy. That is, they offer far higher discounts more frequently for off-peak times, while raising prices only marginally for peak times, resulting in higher revenue overall.
By doing this, they have actually increased quantity demanded by selectively introducing many more price points, as they learn about and react to the diversity of interests and purchase drivers of their customers.
How machine learning can improve Revenue Management
Machine learning entails building, and training statistical models using data inputs to classify input items or forecast output continuous values.
Demand forecasting
Another important part of revenue management is demand forecasting. A demand forecast provides critical information for pricing across customer segments and allows for selecting an appropriate distribution strategy.
Yields
Yield management deals with inventory. In the final analysis, it should optimize profit and revenue, controlling utilisation of event spaces, vessels or attractions, striving to maximize revenue opportunities during high demand days and maximize occupancy during low demand days. This is achieved by quickly covering fixed costs for managing inventories. The technique is particularly important when the proportion of fixed costs is much higher than that of variable costs. The disparity between fixed and variable cost covers overhead and then contributes to profit.
As the same ticket can be demanded by different customers, the system will assist with the application of one or several yield tactics. This may be limiting availability of discounted or promotional rates, managing allocations – often at a discounted rate or deals made available for last-minute inventory. Real time decision making facilitates the ability to rapidly choose the best yield tactic.
Dynamic Pricing
Dynamic pricing is an important part of revenue management. It offers variable rates based on demand and supply. This allows organisations to quickly react to changing market values maximizing revenue and occupancy rates. Customer demand, and supply insights allow the application of different pricing strategies.
In summary, revenue management is a critical function in the travel, tourism & hospitality industry, improving profitability, maximising occupancy, and reduced time expenditures associated with traditional pricing and reporting.