Uber, Amazon and Airbnb all have one thing in common — aside from rapid growth, creating entirely new markets and crushing their competition. All three price dynamically using advanced artificial intelligence (AI) and machine learning. Leading companies know that in today’s digital marketplace, dynamic pricing is a key driver for growth and success.
But what is dynamic pricing, and why is it so important?
The Rise Of Dynamic Pricing
Dynamic pricing is when a company changes their pricing to match demand and supply. Uber’s base fares are typically less than a taxi, but when a baseball game lets out and demand spikes, prices go up. You may have to pay more, but you can always get a car when you need one — and more drivers show up at the ballpark knowing there are better fares. As people leave and availability opens up again, the price goes back down.
Uber was not the first company to optimize pricing to align supply and demand; airlines, hotels and others have invested in pricing technology for decades. Before the internet, airlines bought expensive price optimization software, built out giant data centers full of servers to run it and hired large pricing teams to do manual analysis and then set business rules. Many still do it this way.
These pre-internet technologies cannot adjust for unforeseen events. Consider a familiar problem: Hotel occupancy rates in the U.S. have hovered around 60-65% (paywall) over the past two decades, meaning about one in three hotel rooms goes unsold. To deliver the constant availability, competitive prices and instant buying experience that today’s consumers demand, companies need new capabilities.
To implement dynamic pricing and solve this inefficiency, AI and machine learning are critical. These technologies enable dynamic pricing algorithms to train on inputs — transactions, external data — and understand patterns. AI can find patterns humans cannot see. As a result, an AI dynamic pricing engine can operate at a much more granular level than a pre-internet rules-based engine, where humans have to understand and anticipate what might happen.
