The same product can have different prices depending on the context. Selling internationally is a good example. Not only does the currency change, but also the amount. Another example is when your product has different prices for B2C and B2B customers, or taxes that can or can't be included.
All those scenarios can be handled by keeping different price lists. Depending on the context, such as the current market or customer, the price list can simply be swapped. This adds some dynamism to your product prices. However, there are some cases where this isn't enough.
Some businesses need to adjust product prices in real-time depending on market demand, stock levels, competitor monitoring, or customer behavior. Clearly, you can't manage all these scenarios just by having different price lists for each. Rather, you need a dynamic pricing engine that provides you with the current price for a given product and context.
In general, you need a rules engine to calculate prices based on input data. Ideally, you should build or buy an independent microservice to provide product prices based on context. The endpoint of such a microservice would display prices on your frontend and apply the right price when you add a product to the shopping cart.
It goes without saying that AI could support the price engine. Earlier this year, Fabrizio Picca, our Head of Solution Engineering at Commerce Layer, published an article on how to build your own dynamic pricing engine using ChatGPT. It includes detailed step-by-step instructions and code snippets and I think it's essential reading for any developer interested in the topic. Check it out here!