Consumers are turning to advanced AI tools to help track dynamic pricing trends: according to a recent study, 44% of Black Friday shoppers¹ planned to use AI tools like ChatGPT to find the best prices and deals. Online shopping for Black Friday hit a new high, reaching $10.8 billion in online sales in 2024.²

The practice of “dynamic pricing” – presenting customers with different prices depending on the time of day, inventory, consumer behaviors and even the weather – is now more the rule than the exception.³ It’s widely used on big e-commerce platforms like Amazon and eBay, which together are projected to account for 25% of all retail sales in 2025.⁴ Amazon reportedly changes prices millions of times per day, with the average product’s price shifting every 10 minutes.⁵ In February 2024, fast-food chain Wendy’s mentioned rolling out digital menu boards that would allow for price changes based on demand, consumers took notice.⁶

The pioneers of dynamic pricing were online ride-sharing services, airlines, event ticketing services and hotels. With the development of online systems, other retail sectors as well as brick-and-mortar stores have started to adopt the practice, too.⁷ Walmart, for instance, has recently started using digital price tags that allow for dynamic pricing of items on the shelves: though the retailer attributes the tech-savvy move to cutting down costs, noting the substantial labor hours associated with manually changing prices on its 120,000 products⁸ across thousands of stores each week.

An emerging market for dynamic pricing is electric vehicle charging. By 2030, it is expected that there will be an eightfold increase in public charger demand compared with 2021. While flat kilowatt-hour (kWh) pricing is dominant now, dynamic pricing is emerging to better balance supply and demand.⁹ Dynamic pricing could even come to grocery stores as more U.S. retailers install electronic shelf labels that allow merchants to effortlessly tweak prices for thousands of products.⁷

From the old world to the new

Fixed retail prices began in the 19th century with the advent of department stores, particularly Le Bon Marché in Paris (1830s) and Macy’s in the U.S. (1858). Before this, most retail transactions involved a price negotiation between buyer and seller. Fixed prices sped up shopping and led to more sales across the industry.¹⁰

The earliest manifestation of dynamic pricing came in the form of surge pricing: Higher prices during periods of peak demand. Starting in the 1970s and continuing through the early 2000s, airlines and hotels began to charge more around holidays and vacation periods. These systems were based on historical demand patterns, rather than real-time data.¹¹

The internet created a new era where real-time data such as competitor prices and customer behavior can be harvested and analyzed rapidly, which is central to dynamic pricing as we know it today.⁵

From a profit-maximizing perspective, a business wants to charge every customer the most they are willing to pay – a price that is different for every buyer. That price used to be unknown. Now it’s much more knowable, thanks to machine learning algorithms aimed at the data trail of the customer’s IP address, device, phone number and email, demographics, purchase history, and social media posts.¹²

Combine those predictions with software that adjusts prices instantly and the result is personalized pricing.¹³ A slew of startups offering dynamic pricing engines has emerged, with the market for dynamic pricing software projected to grow 12% annually.¹⁴

The US Federal Trade Commission recently requested information from JPMorgan Chase, Mastercard, McKinsey, Accenture and four software vendors on their personalized pricing products, who uses them, the data they use, and the effect on prices.¹⁵

Real-world examples

Dynamic pricing algorithms can lead to significant price fluctuations across everyday purchases. Here are some real-world examples.

Entertainment and tickets

• Ticketmaster adjusts ticket costs in real-time based on demand. Ticket prices for high-demand events can double or triple in a short time. Prices for Oasis reunion concerts in Ireland recently surged from €160 to €400.¹⁶ Taylor Swift famously refused to allow Ticketmaster to set prices using their dynamic pricing algorithm, mandating fixed-price tickets.¹⁷
• Disney utilizes dynamic pricing models that vary ticket costs depending on expected crowd levels, offering lower prices during less busy periods. This reflects a broader trend in the theme park industry, where operators adjust prices constantly to fine-tune attendance and revenue.¹⁸

Airlines and travel

• Airlines adjust ticket prices based on demand, time of day and seasonality. There’s no universal rule for when to buy to get the lowest prices, but Google Flights indicates that 38 days before departure (US domestic flights) and 129 days (international flights) – and earlier for holidays and peak travel periods – are good rules of thumb.¹⁹
• Fees for checked baggage also vary. In 2024, JetBlue introduced dynamic pricing for checked baggage; so does Spirit Airlines, with prices varying based on factors such as booking time, route, and demand. This approach allows the airline to adjust fees in real-time to boost revenue.  Booking far in advance can help mitigate the fees.²⁰
• Dynamic pricing also surfaces in airline loyalty programs. The number of points or miles required for award flights now fluctuates with demand.²¹

Restaurants and food delivery

• Platforms like Uber Eats and DoorDash increase delivery fees during peak times or bad weather. But both also offer fixed-price subscription plans that eliminate fluctuating delivery fees for frequent users, providing more predictable costs. Those plans may not absolutely guarantee fixed prices, however, as the restaurants supplying the meals may also use dynamic pricing.⁷
• Beyond the food delivery industry, dynamic pricing is entering the restaurant space. As restaurants turn to QR-code menus, they also got a quicker and more efficient way to update pricing and offerings.⁶
• Reservations for the best seat in the establishment at primetime on a Friday or Saturday, for example, could come at a higher cost than a midday reservation during the week.

These examples demonstrate how dynamic pricing algorithms create a fluid marketplace, with real-time price adjustments influencing consumer behavior. In a world where price increasingly “depends,” understanding the system is key. Some are turning to ChatGPT and other AI tools to stay one step ahead and find the best prices.¹