Revenue management, dynamic pricing, and price optimization can seem like different names for the same thing. They’re not — and if you’re investing in something that controls your price, the distinctions are worth knowing.
A bit of history
I first heard “dynamic pricing” in the mid-2010s as an airline analyst. Airlines have good forecasting and optimization models but archaic reservation and distribution systems that rely on infrequently updated historical data — so “dynamic” was largely about overcoming stale forecasts and stale distribution. Per Google Trends the term really took off around 2022, and other industries now use it to solve their own problems.
Dynamic pricing
“Dynamic” refers to the frequency of change — a price that updates often. What counts as frequent is subjective: airlines distribute prices slowly, while in STR you can push updates to almost any channel as often as you like. Crucially, dynamic pricing says nothing about the model or rules behind the change; it only tells you the price moves frequently.
Dynamic pricing does not explain what is happening behind the scenes causing the price to update; it just describes that the price does change frequently.
Optimized pricing
Like AI, “optimization” has two uses: the colloquial/marketing one, and mathematical optimization — a specific process that finds the revenue-maximizing price. When revenue managers say optimization, they should mean the mathematical kind. It describes HOW the price is set, and on its own it doesn’t have to be dynamic — that’s about frequency.
Optimization models on their own do not have to be dynamic; that is based on frequency.
Does changing prices increase revenue?
Every price change moves either toward a better price or away from one, so changing frequently only helps if the change is toward a better price. That’s why the pricing model matters far more than how often it updates — a really good model may not need to be as dynamic.
The best case: dynamic and optimized
The ideal is the practice of revenue management, using a mathematical-optimization model, updated dynamically — and Quibble is the one solution that does all three. When you invest in pricing software, focus more on how prices are set than how often they change. In short: revenue management varies price to grow revenue; dynamic pricing changes price frequently; optimization is the model that finds the optimal price.