Beat Airline Price Hikes: Your Personalised Flight Fares Guide

Delta Air Lines’ recent announcement regarding the expanded use of artificial intelligence (AI) to offer personalised pricing to its customers has ignited a debate amongst travellers and politicians alike. However, Delta isn’t alone in exploring the potential of AI in this manner. Personalised pricing strategies are increasingly prevalent across various sectors, from finance to the ever-enticing world of online gaming.

The Allure of Customised Pricing

Customised pricing – the practice of offering different prices for the same product to different customers – represents a significant opportunity for businesses seeking to maximise profits. This approach allows companies to charge more to customers with a higher willingness to pay, while offering lower prices to those who are more price-sensitive. The idea is to tailor the price to each individual’s perceived ability and desire to spend, much like a bespoke suit is tailored to fit a specific individual.

Concerns About Transparency and Fairness

While the potential benefits for businesses are clear, concerns are mounting about the ethical implications of AI-driven personalised pricing. A key worry centres around the lack of transparency in these AI pricing models, and the potential for them to unfairly exploit individuals with limited financial understanding. The complexity of these algorithms can make it difficult for consumers to understand how prices are determined, raising concerns about potential price gouging.

A Historical Perspective on Pricing Strategies

Customised pricing, in many ways, represents a return to older, more traditional methods of commerce. Historically, bargaining was the norm. Business owners would assess each customer individually and negotiate prices on a case-by-case basis. The final price was determined by the bargaining skills of both the buyer and the seller, as well as their respective levels of urgency.

A classic anecdote illustrates this point perfectly: A wealthy man, travelling in his carriage, stopped at a restaurant for breakfast. Upon receiving the bill for his eggs, he was shocked by the exorbitant price. “Are eggs rare in this neighbourhood?” he inquired. The owner replied, “No, eggs are plentiful, but very rich men are quite rare.”

While direct bargaining is less common today, it still exists in certain industries, such as car sales, where individual negotiation is expected. Economists refer to this as “first-degree” or “perfect” price discrimination, a strategy that allows sellers to extract the maximum possible price from each customer.

The rise of fixed pricing, where items are sold at a non-negotiable price, is often attributed to the opening of John Wanamaker’s department store in Philadelphia in 1876. This approach simplified the shopping experience for customers and quickly gained popularity.

The Advantages of Uniform Pricing

Fixed pricing offers several advantages for businesses. It allows retailers to employ less specialised staff, rather than requiring skilled negotiators. Historically, it also simplified the process of determining prices. Before the advent of AI, many companies relied on a “cost-plus” pricing model, where a fixed percentage or markup was added to the cost of the item to cover profits and overhead.

Even today, large retailers like Costco utilise a cost-plus approach, adding a relatively consistent markup to their products. However, the limitation of cost-plus pricing is that it treats all items the same, regardless of demand or customer willingness to pay. For example, a bottle of premium Champagne could command a higher markup than a basic bottle of wine, yet under a cost-plus system, the markup would be similar. AI overcomes this by dynamically adjusting markups based on real-time data and customer behaviour.

Navigating the World of Personalised Pricing

AI relies on vast amounts of data to function effectively. The increasing shift towards electronic payments has provided businesses with a wealth of information about consumer spending habits. Companies can now use this data to analyse individual preferences and tailor pricing strategies accordingly.

The sheer volume of data collected through electronic transactions has raised concerns among regulators. The Federal Trade Commission, for example, has launched investigations into the use of AI in pricing, seeking to understand how these technologies might be used to manipulate prices based on individual consumer data.

Some regions have implemented laws requiring retailers to display a single price for each product, in an attempt to prevent overt personalised pricing. However, even with these regulations, businesses can still utilise targeted digital coupons to offer different discounts to different shoppers.

Strategies for Outsmarting AI Pricing

Despite the increasing sophistication of AI pricing models, consumers can take steps to protect themselves from potentially unfair pricing practices. The key is to limit the amount of data that AI algorithms can collect.

Here are some practical strategies:

• Embrace Cash: When shopping in physical stores, opt for cash payments whenever possible. Cash transactions leave no digital footprint, preventing businesses from tracking your purchases and building a profile.

• Clear Your Cache: Regularly clear your browser cache and cookies. This removes stored data about your browsing history and online activity, preventing algorithms from using this information to adjust prices.

• Be Mindful of Your Location: Be aware that your location can influence pricing. Consider using a VPN to mask your location, particularly when making online purchases.

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• Practice Patience: When shopping online, add items to your basket and then wait before completing the purchase. Sometimes, the delay will trigger the website to offer a discount to encourage you to complete the transaction.

The rise of customised pricing, facilitated by AI and the cashless society, raises important questions about transparency and fairness in the marketplace. In a world where prices are tailored to individual willingness to pay, it’s crucial for consumers to be vigilant and proactive in protecting their interests. Simply seeing a high price does not mean the item is of higher quality; it could simply mean the business believes you are willing to pay more. Increased use of cash, alongside other data-minimisation techniques, can help to level the playing field. Furthermore, it is imperative that open discussions are held regarding price determination before customised pricing becomes ubiquitous.