What Is Revenue Management? Is This Really Best Practice…?
What is revenue management: More Australian businesses across retail, airlines and energy have been exploring “flexible pricing opportunities” which consumers may be a little less pleased with…
Over the past 2-3 years, the airlines, entertainment, travel, hospitality and retail sector (online and brick and mortar) have been testing and trialling dynamic pricing options on us. This basically means they have been seeing how we respond to being offered different prices for the same item every time (they have already asked what is revenue management).
Have you noticed this when you have been buying something online?
At the moment dynamic pricing operates at a fairly crude level where consumers buying online for say a MAC computer are sometimes offered more expensive prices than PC users.
Toby Walsh, professor of artificial intelligence at the University of New South Wales, says the continued rise of AI driven dynamic pricing is inevitable.
“Google, for example, tracks a billion shop visits every year and has access to 75 per cent of all credit card activity in the US, it’s not just your online activity that is being tracked but it is also related to your offline activity.”
Currently all these businesses and more (listed below) are using dynamic pricing and consumer data with little to no backlash from consumers.
What is revenue management?
The execution of dynamic pricing in the Australian marketplace is a major development in commercial pricing. It started off in the airlines and is now being widely adopted in our retail sector too. It can be classified under revenue management, however it is not uncommon for a business to implement fixed and dynamic pricing at the same time.
What is revenue management (RM) refers to the collection of strategies and tactics firms use to scientifically manage demand for their assets, products, services or perishable inventory or capacity.
Unlike pure price management, what is revenue management has a much heavier inventory component to it. A pure price management looks at product mix but does not really deal with inventory allocation or controls in the same way or to the same extent that a true revenue management function does.
Revenue management, conversely, does not have the cost picture to deal with perishable or time constrained inventory (inventory that go away have a shelf life and airlines seats, media space, car rental).
The marginal cost of next sales is much lower, so they don’t really have to factor costs in as much as B2B price management function i.e., a plane must take off – fixed cost for the plane to take off are the same.
Online platform businesses like Amazon have been moving away from fixed pricing to test and trial dynamic pricing across the retail sector. Dynamic pricing is traditionally based on the laws of supply and demand: Typically, prices fluctuate for certain products and services like airlines fares, hotel rooms and ride-sharing services like Uber when there are spikes in demand, and the charges go up.
New developments in artificial intelligence and virtual assistants are radically changing the relationship between retailers and customers using price optimisation software and algorithms.
Price Optimization software are driven off regression models that calculate how demand varies at different price levels and then combine that data with information on costs and inventory levels to recommend prices that will improve profits.
Latest price optimisation software has moved a step beyond supply and demand and asset allocation levels and is now combining forecasting data with customer data and information sources to help pricing and revenue management teams predict customer willingness to pay.
Customer data used by pricing algorithms is gathered from sources such as loyalty cards, individual online shopping behaviour, price-sensitivity analysis, post codes and prior behaviour.
Understanding the demand profile for hard durable goods and supply constrained assets is fast becoming the norm in high performing B2B and B2C pricing and revenue management teams.
However, it is very difficult to chart a course for the future or bring about change merely by analysing history. The behavioural profile of customers can never be changed by pricing processes based purely on an analysis of their past behaviour.
Price Optimization models have been used to tailor pricing for customer segments by simulating how targeted customers will respond to price changes with data-driven scenarios.
Given the complexity of pricing thousands of items in highly dynamic market conditions, modelling results and insights helps to forecast demand, develop pricing and promotion strategies, control inventory levels and improve customer satisfaction.
Conclusion on what is revenue management
Over the past 5 years, there has been a clear move towards flexible pricing, algorithmic pricing and automation. Indicators suggest customer focused pricing process is likely to become the prevailing catalyst to setting and achieving optimal prices for all our shopping and grocery needs.
Yet, transforming customer habits and experiences is still largely limited to cause and effect analysis – i.e., via demand profile analysis. Of course we need to incorporate scientific proof into our price models, but a scientific approach to understanding customers has its limitations. Tracking customers as they buy seems to break a moral code of conduct and has ethical considerations.
Pricing and revenue management teams need to figure out where data driven limitations lie and imagine pricing processes that possibly don’t exist yet to get closer to developing optimal price points that influence behaviour and drive profitability.
As a pricing or revenue manager or general manager commercial, do you think dynamic pricing undermines a largely unspoken moral tradition?
Did you know?
Traditional revenue management did not start off deriving price points based on demand at all. Only 10-15 years ago, the airlines industry was still allocating and assigning fixed price levels to seats in advanced of them being sold. There was very limited real time analytics going on and no accurate view on demand. Inventory allocation and pricing was largely manual and predefined.
Once, an allocation of seats was sold at a lower price level, another allocation of seats at a higher price level would begin to sell. This fixed allocation and pricing system was not based on real insight into consumer demand and only gave the impression that the prices for seats was going up when really it was just another bucket of seats being sold.
Revenue management now has evolved since then and is now much more about price optimisation as well. Not just a static view: i.e., let’s just fill 10 seats at x price.
Revenue management now seeks to understand the overall demand profile of the system and then optimises prices using price optimisation software against that demand profile. A different way to approach the same problem.
How do you think your customers would respond to dynamic pricing – do you think they’d complain or even notice?
How do you think dynamic pricing impacts you business’s brand or price positioning in the market?
Can you answer “what is revenue management to your boss”?
Check out the “entertaining” CNN overview on revenue management in the airline industry below:
See our blog on what is pricing.