Why did I pay so much? – about airline price discrimination methods

17

September

2024

5/5 (2)

Most of us had probably bought a plane ticket and wondered where the price came from. For many it might see like airlines set their price at random, as for each flight prices change from day to day. Despite how it looks from the outside, various revenue management systems and pricing strategies make sure that each customer pays the most optimised price. The goal of these is to make sure that revenue is maximised with a limited seat capacity. The question is, can we say that airlines are getting close to a perfect price discrimination? In the long term, fuel prices are the single most significant factor influencing ticket prices. In the short term, which is usually more relatable for customers, there are numerous other factors, a few of which I would like to name below.

For easier customer segmentation airlines use versioning and allow two primary choices. Firstly, airlines offer different price points for classes (first, business, premium and economy). Secondly, fare bundles are offered to further optimise pricing. Consumers, depending on their needs and willingness to pay, choose baggage options, fast track access, seat selection, refundability and many more. For airlines these are called ancillary products, which are usually sold in bundles with the primary product, an airline ticket (Boin et al., 2017).

One of the basic ways that airlines segment their customer base is leisure and business travel. This division is not connected with classes as both groups fly in all classes. Airlines use a number of criteria to assign consumers to the correct group. Firstly, how many days before departure was the ticket bought. Corporate travel often has a shorter booking window (buying tickets closer to departure), as plans often change when many stakeholders are included. Other criterias are whether flights are on business days or weekends, how long the stay at the destination is and how big the group is. 

Time is another aspect you need to think about when looking for the cheapest ticket. It is not only about when you buy the ticket, but also when you fly. The most visible difference is between off-peak and peak seasons, including Christmas, New Years. Some peaks are local, most commonly for events or local holidays. Depending on your destination prices can vary significantly among months. On some connections, for example to major academic centres, the beginning and end of the academic year is reflected in prices. Travel to leisure destinations will be more expensive between June and September, but during the same time business destinations are usually cheaper. Even during the same day prices may differ between the same route at different hours. As some flights are used more for point to point travel and some are feeder flights for other routes (Abdelhady & Abou-Hamad, 2020). There are many other factors on which a ticket price depends. Such as group discounts, student programs, frequent flyer programs, geographical price differences and many more, but I will not elaborate on these here.

Nowadays, most traditional airlines use systems based on Reservation Booking Designators (RBDs) to assign prices to each customer. This results in limitations, as the number of RBDs is limited (standard number of RBDs is 26)(Fiig et al., 2018). Continuous pricing is expected to transform that situation and offer airlines unlimited opportunities to personalise prices to the willingness to pay of each customer. Despite having a lot of personalisation possibilities, airline pricing is not a perfect price discrimination example. It is still far from name-your-own-price models, but looking at improving usage of algorithms and possibly AI it is getting close.

Sources

Abdelhady, M. R. R., & Abou-Hamad, M. M. H. (2020). Airlines’ Pricing Strategies and O-D Markets: Theoretical and Practical Pricing Strategies. Journal of Travel, Tourism and Recreation, 2(3), 19–36. https://doi.org/10.22259/2642-908x.0203004

Boin, R., Coleman, W., Delfassy, D., & Palombo, G. (2017). How airlines can gain a competitive edge through pricing. McKinsey. https://www.mckinsey.com/industries/travel-logistics-and-infrastructure/our-insights/how-airlines-can-gain-a-competitive-edge-through-pricing

Fiig, T., Le Guen, R., & Gauchet, M. (2018). Dynamic pricing of airline offers. Journal of Revenue and Pricing Management, 17(6), 381–393. https://doi.org/10.1057/s41272-018-0147-z

Please rate this

The bumpy road towards personalized pricing

28

September

2021

No ratings yet.

Among ‘tailored offerings’, ‘interests-based content’ and other promises of customized user experience companies employ to retain their clients and boost profitability, ‘personalized pricing’ is perhaps the holy grail. Personalized pricing entails offering each customer a unique price for a product, according to their individual profile. In more technical terms, personalized pricing is a First-Degree Price Discrimination Mechanism, aiming to identify the exact amount each customer is ready to pay for a product (their ‘maximum willingness to pay’) in order to maximize potential profits for the firm and make the product affordable for as many people as possible (Varian, 1996). The maximum willingness to pay can be inferred from the aforementioned individualized customer profile, which is based on a series of factors such as employment situation, geographical residence and level of interest in the given product. The higher the number of factors taken into account when building the customer profile, the higher the likelihood that the inferred maximum willingness to pay is equal to the customer’s actual one (Stobierski, 2020).


With companies seemingly having more access to granular customer data than ever before, ‘big data’ analytics techniques evolving rapidly and clear economic incentives to implement personalized pricing, it can appear surprising that this practice is still relatively uncommon in the market (Vomberg, 2021). However, early adopters have faced several difficult hurdles in implementation, detracting others from trying the model. The key difficulties in implementing personalized pricing are:


1. Customer backlash over perceived unfairness
So far, companies openly engaging in ‘pure personalized pricing’ (i.e., showing different retail prices for each customer based on their profiles) have been subjected to severe backlash, with customers questioning the fairness of the process and feeling aggrieved when finding out they paid more than some of their peers for the same product. Amazon was one of the pioneers of this technique in the early 2000’s, using personalized pricing for its best-selling DVDs range (Reinartz, 2002). The customers’ anger was so severe that the company quickly reversed its policy and to this day, has not discussed introducing it again.


2. Data usability and accuracy
While larger amounts of data can now indeed be more easily stored and analyzed, growing public concerns over privacy are limiting companies in the use of the customers’ individualized data. In addition, more tech-savvy customers can try to understand the algorithms behind personalized pricing and ‘game’ the system to obtain the best deals, regardless of their true customer profiles (Howe, 2017).

3. Regulatory concerns
Regulators and, in particular, Competition Councils, are stringently assessing any attempts at personalized pricing, wary of the potential anti-trust implications they may have. Migros, an international grocery retailer, was severely challenged by Swiss regulators when deploying a new ‘personalized discounts’ scheme in its stores throughout the country. Moreover, governmental entities must ensure no discrimination based on sensitive characteristics such as sex, religion or nationality is made (Nakahara, 2020).


Given the existing obstacles, it is likely that the business environment is still years away from seeing personalized pricing become ubiquitous. Creating transparency over the algorithms behind personalized pricing, in order to win the customers’ trust, while making the system complex enough not to be easily ‘gamed’ and ensuring all regulatory requirements are met present a formidable challenge for businesses over the next decade. However, the first ones to manage this successfully stand to gain considerable boosts to their margins and even unlock a new source of competitive advantage.


References


Howe, N. (2017) A Special Price Just for You. Forbes. Available at: https://www.forbes.com/sites/neilhowe/2017/11/17/a-special-price-just-for-you/?sh=4aba44bb90b3 (Accessed: September 28, 2021)


Nakahara, M. (2020) Regulatory Solutions for Personalized Pricing. The Regulatory Review. Available at: https://www.theregreview.org/2020/08/06/nakahara-regulatory-solutions-personalized-pricing-2/ (Accessed: September 28, 2021)


Reinartz, W., 2002. “Customizing Prices in Online Markets.” Emerging Issues in Management, 6(1), doi:10.4468/2002.1.05reinartz.


Stobierski, T. (2020) Willingness to pay: what it is & how to calculate. Harvard Business School Online. Available at: https://online.hbs.edu/blog/post/willingness-to-pay (Accessed: September 28, 2021)


Varian, H., 1996. “Differential Pricing and Efficiency.” First Monday, 1 (2-5), https://doi.org/10.5210/fm.v1i2.473.


Vomberg, A. (2021) Pricing in the Digital Age: A Roadmap to Becoming a Dynamic Pricing Retailer. Groningen Digital Business Centre. Available at: https://www.rug.nl/gdbc/white-paper-digital-pricing.pdf (Accessed: September 28, 2021)

Please rate this

Personalized Pricing and GDPR

28

September

2020

No ratings yet. Many companies use pricing strategies whereby they charge different prices to different customers, based on personal data. This type of price discrimination is called personalized pricing. Through this pricing strategy, companies are trying to charge a price that is close to the consumers’ willingness to pay in order to increase their profits (Whinston, Stahl & Choi, 1997). Price discrimination has been applied for many years in various sectors. For example, E-commerce companies adjust their prices based on the website visitor’s search history. If they can deduce from the search history that an individual is highly price sensitive, it is likely that this person will see a lower price for the same good than someone who is not being considered as price sensitive (Mikians et al., 2012). Also, different prices are being charged to individuals based on for instance their geographical locations (Borgesius & Poort, 2017). With the emergence of the Internet, firms have gained more access to personal data, making it easier to apply price discrimination (Borgesius & Poort, 2017).

As data has become increasingly important in the digital age, new legislation was introduced in Europe on 28 May 2018. The General Data Protection Regulation (GDPR) aims to improve the protection of personal data by giving people more say in what companies do with their data (Europese Commissie, 2020). This law concerns many organizations, as it covers not only the data that companies have stored in their systems but also the data linked to Cookies and IP Addresses (Den Breejen, 2020).

According to the law, firms are required to be transparent in what is done with consumer data and also need the consent to use the data of the consumer (Borgesius & Poort, 2017). Therefore, the introduction of GDPR has made it more complex for companies to apply price discrimination. Previously, companies could apply price discrimination without website users or consumers being aware of it, in order to make profits. Nowadays, violating GDPR could result in high fines and damage to the company’s reputation (Schoonen, 2020). It is therefore important for companies to comply with the law.

For me, it is questionable whether companies that use personalized pricing can continue to do so while still complying with the General Data Protection Regulation (GDPR). In my opinion, greater transparency in companies’ pricing strategies could evoke feelings of unfairness. Moreover, consumers’ confidence in companies may decrease if they find out that their data is being used for profit objectives. Subsequently, this may lead to a decrease in demand for the product or service.

I am very interested in your opinion on this.

References

Borgesius, F.Z.& Poort, J. (2017). Online Price Discrimination and EU Data Privacy Law. Journal of Consumer Policy, 40(3), 347-366.

Den Breejen, A. (2020). Privacywetgeving AVG, wat moet je ermee? Available at: https://www.kvk.nl/advies-en-informatie/wetten-en-regels/privacywetgeving-avg-wat-moet-je-ermee/ [Accessed 27 September 2020]

Europese Commissie. (2020). Gegevensbescherming in de EU. Available at: https://ec.europa.eu/info/law/law-topic/data-protection/data-protection-eu_nl [Accessed 27 September 2020

Mikians, J., Gyarmati, L., Erramilli, V. & Laoutaris, N. (2012). Detecting price and search discrimination on the internet. Proceedings of the 11th ACM Workshop on Hot Topics in Networks, 79-84. HotNets-XL. ACM. http://doi.acm.org/10.1145/2390231.2390245.

Schoonen, D. (2020). Al 160,000 schendingen van de GDPR gerapporteerd. Available at: https://www.techzine.be/nieuws/security/51890/al-160-000-schendingen-van-de-gdpr-gerapporteerd/ [Accessed 28 September 2020]

Whinston, A., Stahl, D.O., Choi, S.-Y. (1997). Chapter 2: Characteristics of digital products and processes. The Economics of Electronic Commerce. Indianapolis, IN: Macmillan Technical Publishing

 

Please rate this

Five Games For A Dollar – How Humble Bundle Uses Price Discrimination

24

September

2016

No ratings yet. Do you remember the time when you had to pay $50 for a game in the store? And the price did not change much even after a long time. How things have changed since then. Ever since games are available in fully digital form on platforms such as Steam, prices have gone down a lot (even though they often still start out as expensive as in the past). How is it possible that games have become so much cheaper? Does the gaming industry simply make less profit? This is possible, but not necessarily the case. The answer lies in the fact that games are an information good, which means that while it is very expensive to produce the first copy, creating more copies is relatively cheap. So the more copies you manage to sell, the smaller your total cost per copy is (because the production cost is spread out over more products). In other words: to maximize your profit as a game developer, you want to sell as many copies as possible, even if this means reducing your price. Now, keeping this in mind, let us consider the concept of price discrimination: each individual has a willingness to pay for a particular product. Some people might be willing to pay $50 to get a game as soon as it is released. However, other people may only want buy that same game for $1. Ideally, you’d offer the game to the one person for $50 and for $1 to the other. However, if the game is sold in a store, you cannot differentiate the price, which is why in the past the only way to discriminate prices for certain groups of individuals was by changing the price over time, so that those with a lower willingness to pay would wait until the price dropped. But even then, putting a game in a store is obviously more expensive than selling a digital, downloadable version online, such as what Steam offers.

 

This is all very interesting of course, and a very happy development for all gamers, but this is not the phenomenon that I wanted to talk about. I’d like instead to point out another website that sells games: Humble Bundle. They have a very interesting business model where they have extended this idea of willingness to pay and combined it with the idea of bundles. What Humble Bundle does is they create a bundle of games and offer it for about a week. Now what is special is that you can pay what you want! In fact, you could get many of the games they offer for free (although you must pay at least $1 to get Steam keys, allowing you to download the games in Steam). What’s more: you can choose where your money goes. By default, part of it goes to each game developer, part goes to Humble Bundle itself and part goes to charity. But you can customize this any way you want, choosing not to give anything to Humble Bundle, or giving everything to a charity. In this way, you have the possibility to support the developers of the games that you really like. So why does this concept even work? If you are giving away games for free, how can you possibly make a profit? Well, obviously most people choose to pay a little bit, either to get access to the games on Steam or to ease their consciousness. In addition, Humble Bundle smartly gives an incentive to pay more by allowing you to ‘upgrade’ your bundle by paying more, meaning that other (usually more recent or more popular) games are added. This works because, as mentioned earlier, the Humble Bundle system allows great personalization, thus making it possible to make maximum use of each individual’s willingness to pay (and some people do in fact pay over $50 for a bundle). In addition, the idea of making bundles is very smart. People will feel that the total value is more, even if they only end up playing one game in the bundle. After all, it is easier to motivate someone to buy that one game that they want for $15 even though their willingness to pay was $10, since they get that other game that they were kind of interested in as well. Not to mention that a great way to sell unpopular games is by combining them with more popular games. Even if people can choose where their money goes, they likely won’t often choose to give nothing at all to a particular company.

 

All in all, I believe Humble Bundle’s business model is very smart, and while it may at first seem counter-intuitive, it likely leads to quite a bit of profit for game developers. In addition, they have executed this idea, that can be brought back to various economic theories, in a really good way. I hope they will continue to experiment and find new ways to make both consumers and developers happy. Now go celebrate this great development by treating yourself to a bundle of games – for whatever you’re willing to pay!

Please rate this