Dynamic Pricing and Price Discrimination: What’s the Difference?

Dynamic pricing and price discrimination are two concepts that are often used interchangeably. Dig into the details, though, and they couldn’t be more different.

Both involve changing the price of a product or service depending on market conditions or customer attributes, but the way they’re executed reveals that there are some important differences between the two.

These concepts can be a little confusing at first, but you don’t need an economics major to wrap your head around them. Let’s explore both separately before we weigh them side-by-side.

What is Price Discrimination?

Price discrimination, sometimes referred to as differential pricing, is the practice of charging different customers different prices for identical goods. The price difference between consumers is based on what the seller thinks they can get the customer to pay.

There are some nuances in there—price discrimination isn’t a binary practice where you either do it or you don’t. A perfect price discrimination strategy would simply charge each customer the maximum they can pay for the product. This is very rare.

More commonly, sellers segment customers by certain attributes that signal how price-sensitive or price-insensitive they are, and charge each group a different price.

There are three degrees of price discrimination.

  • First-degree price discrimination is when a seller charges the buyer the maximum price they are willing to pay. The goal here is complete maximization of profit via perfectly personalized pricing.
  • Second-degree price discrimination is when sellers give discounts based on quantity purchased, generally lowering the per-unit cost. A bulk discount is a common example.
  • Third-degree price discrimination is when a seller segments its customers based on certain relevant attributes. Age discounts and group status-based discounts, such as student discounts, are good examples here.

Third-degree price discrimination is the one that often sparks controversy.

If a brand or retailer is discovered to be altering prices based on market segment, it usually leads to accusations of price discrimination. When retailers charge online shoppers more if they live more than a certain distance away from a brick-and-mortar location, that’s third-degree price discrimination.

Charging different prices through price discrimination

 

What is Dynamic Pricing?

Dynamic pricing is a pricing strategy in which prices adjust at regular time intervals in response to real-time supply and demand data. It’s also known as demand-based or time-based pricing.

Compare that to a fixed-price strategy, where a retailer has a single price for a product that every consumer pays, no matter who they are and what is going on in the wider market. “Everyday low price” retailers fit that mold.

“Dynamic pricing is one of the central issues facing legacy brick-and-mortar retailers today,” explained Forbes contributor and OmniTalk’s Chris Walton. “Unless they change how they do things, their prices in-store won’t be able to keep pace with the market.”

Here are a few examples of dynamic pricing:

  • Amazon reprices every 10 minutes, and can even revise prices on a customer-by-customer basis based on supply and demand.
  • Ridesharing services like Uber and Lyft use “surge pricing” when demand spikes, as it does during rush hour or right after a major sporting event.
  • In the travel industry, airlines, trains, and bus lines raise or decrease ticket prices based on how many available seats there are, the number of days until the flight, average cancellations, and several other factors.

It’s not an exaggeration to say that a brand’s or retailer’s ability to implement dynamic pricing is directly tied to its success. It’s because consumers today are dynamic. They can research and shop around quickly, gathering information like price, product specs, and reviews and using it all to make decisions. If you can’t respond to the market, the market leaves you behind.

Dynamic pricing requires retailers and brands to have access to real-time supply and demand data. This is vital for tracking the market, and in particular, your competitors. They also need to have the ability to collect, analyze, and act on first- and third-party customer data to understand their unique customer segments.

Dynamic pricing digital arrows

Dynamic Pricing vs. Price Discrimination

That last point above is where we can start to see some key differences between price discrimination and dynamic pricing. The former is exclusively focused on the qualities and actions of individual customers or groups of customers, while the latter takes into account market trends like supply and demand.

Macroeconomic conditions are a major data point that gets reflected in a good dynamic pricing strategy. For example, due to COVID-19 and the impact it has had on the economy, consumer behavior has changed. Research from McKinsey showed that consumers have shifted away from discretionary spending and more toward essentials. People are concerned with value right now when they make purchases.

A dynamic pricing strategy allows you to consider which category your products fit into and price them to reflect the realities of the economy.

Unless [brick-and-mortar retailers] change how they do things, their prices in-store won’t be able to keep pace with the market.

It’s not an either/or when it comes to price discrimination and dynamic pricing. You can use both to maximize your profits. For example, say you use price intelligence software to find out that your competitors are offering discounts on winter coats during an off-peak season. You can automatically adjust your prices through dynamic pricing.

From there, you can price discriminate based on if someone has signed up for your email list. Those customers can get a promotion that gives them an even greater incentive to buy. The discrimination comes in because non-members won’t get the same price as members.

To sum it up, when we say “dynamic pricing vs price discrimination,” we’re being a little misleading. The two aren’t mutually exclusive or opposed to one another. In fact, one could say that price discrimination is one type of dynamic pricing.

They can be used together strategically to drive critical business results. Here are just a few of the benefits of dynamic pricing and price discrimination:

  • Increasing sales when demand drops. Seasonality can lead to decreased demand. If you can lower your prices for that time, you can entice customers to buy from you. Extra discounts for people on your email list can be another tool in your chest for getting you through low-demand periods.
  • Driving greater profits. If you can identify customers who are willing to pay more than others for identical goods, you can raise prices to increase profits. This applies whether the entire market is increasing prices or if you know which customers are price-insensitive.
  • Beating out competitors. Dynamic pricing lets you be proactive and beat out slow-moving competitors For example, if a key competitor is charging $10 for an item you normally charge $7 for, you can raise your price and charge $8.50. Adding a bulk discount could boost sales volume even further. This gives the impression of more value than your competitor while also increasing your profits.

Dynamic pricing and price discrimination give you overlapping but unique strategies for increasing the value of every sale. Of course, there are other considerations that have to be taken into account, such as avoiding MAP violations. A dynamic pricing or price discrimination strategy that leads to a MAP violation is counterproductive, so having safeguards in place is essential.

Apply these strategies where they’re appropriate to help you reach your business goals, satisfy your customers, and beat your competitors.

Editor’s Note: This post was originally written by Brian Smyth and published in May 2015. It has since been updated and refreshed for readability and accuracy.

Matt Ellsworth

Matt is the Sr. Manager, Marketing & Demand at Wiser, the leading provider of actionable data for better decisions.

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