Dynamic pricing in the car rental industry

Overview

The most important question on the minds of most mobility companies is how to maximise revenues and limit external and internal influences on their business. This is more true for smaller businesses and independent car rental companies who are struggling to compete with bigger players in the market. We wanted to explore techniques used by different organisations and how they get around to solving this problem.

Demand planning and pricing management is a crucial function in most organisations and can be described as actively managing the revenue by forecasting demand and controlling the capacity or inventory, though at times it’s not very visible to the outside world. Pricing is a function of supply and demand and it becomes imperative to achieve an equilibrium between the two to maximize the revenue. However, recent innovations in technology and data analytics now allow management of the price of the product or service itself to obtain optimal revenue. This process of changing the price to achieve an equilibrium of demand and supply in almost real time is termed as dynamic pricing.

Airlines companies were the early adopters of dynamic pricing and since then it has found its way into hotel, travel, online retail, insurance, and many other industries. It’s proven to be beneficial for consumers as well as providers. Consumers benefit from an improved supply when demand is high and discounts when demand is low. At the same time, companies have been able to manage their optimal margins efficiently.

In this article, we will look at how dynamic pricing can lead to improving the service experience for all stakeholders in the car rental industry.

The Role of Dynamic Pricing in Car Rental

The usage of dynamic pricing is forecast to grow by 20% CAGR between 2017 and 2021. However, a market study done by Nuvven shows that a majority of the independent players in the car rental industry still rely on flat-fee pricing or have a rule-based pricing engine. Such methods are devoid of intelligence from the data that the company has been capturing for years.

For example, a rule-based pricing engine will always be adverse for a customer who was involved in an accident five years ago but has maintained good driving behaviour since then. It will always rank this incident higher when deriving a price for this customer.

Another good example could be high rental prices in a location during tourist season or a major event, citing increased demand without taking into consideration competitors’ prices or weather data during that period.

We understand that a combination of factors, as opposed to a single fixed rule-based factor, can significantly improve how a final price can be set. This is where our machine learning — backed up by insights from our AI data engine — is playing a pivotal role.

Three major factors that necessitate a dynamic pricing approach for car rentals:

• Fixed capacity in terms of number of cars available for rent
• Willingness to pay with early customers being price sensitive
• Demand varies on factors like location, day, season and so on

Benefits of Dynamic Pricing

Our study shows that traditional pricing has so far been constant or requires significant manual effort to make it “appear” dynamic. Dynamic pricing, on the other hand, considers multiple features before adjusting the final price. A customer’s driving history, current location, weather data, time of day and average rent spend play an important role in providing a price for that customer. A good driving profile maintained by customers can convert into discounts or a lower price for future bookings.

A dynamic pricing algorithm should be ‘efficient’ at managing thousands of price points and at the same time granular to look at the price point on a periodic basis. Dynamic pricing is not about pricing lower or higher, it is about pricing intelligently and using customer data for tailoring products or services for a much better experience.

Implementation

At Nuvven, incorporating a fair and efficient dynamic pricing engine is at the core of our strategy. Our logical engines suggest a price based on various factors, including data-driven profiles such as customer information, regular trips, preferred vehicles and much more. This improves the quality of service that the customer receives, for the same price as a flat fee-based price with no data behind it.

Typically, a dynamic pricing approach assumes that demand is a stochastic function of price and that only one price is available (posted) at a given time. Below is an illustration of how a competitor’s offered price is an important factor when you, as a car rental company, determine the best price from your platform for your customer.

The price of hire in the car rental industry is affected by many parameters like location, time of day, day of the week, car type, distance/days of hire and much more. One important feature — competitors’ price elasticity — is illustrated in the figure below.

As the figure shows, the change in demand (∆Q2) is considerably less (inelastic) when price changes from P2 to P3 as it stays below the competitor price (PC). On the other hand, the demand change (∆Q1) is very elastic for a small price change from P1 to P2 as it crosses the competitor’s price. The price P2 is a win-win situation for customers as well as the car rental provider. Customers pay less than the competitor’s price, whereas providers witness a substantial increase in demand when compared to an initial price of P1.

Here at Nuvven, we are continuously engaged with independent car rental companies to ensure that our platform and pricing strategies always create a win-win scenario for you and your current/potential customers.

If you are an independent car rental company trying to grow and become more competitive in the market or a mobility focussed investor, please get in touch with us to know more about our Artificial Intelligence and IoT enabled marketplace platform and how we are revolutionising the car rental ecosystem with data driven insights. We would love to have you onboard as we embark on this journey.

In the meantime, be safe, drive safe and keep exploring!

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