How Can Big Shops Guarantee ‘The Lowest Prices or Money Return’ Policy?: About Dynamic Pricing in Commerce

Have you ever seen a shop whose prices were always the cheapest in the comparisons? Probably they were even guaranteeing a return of costs if you find a cheaper offer. How did they manage to set the prices always 1 cent below their competitor prices? On the other hand, how do they know that competitors have no products and they can increase their prices?

If you have ever seen such dynamic changes in prices, most probably it was done by a tool that adjusts prices automatically based on the internal and external data, called Dynamic Pricing. This solution gains popularity as the e-commerce market grows and both the number of offers and competitors increase and manual changes are almost impossible.

This tool gathers information about prices on the market, checks internal data (e.g. stock, minimum margin, etc.), and adjusts the price in such a way that maximizes the profits of the seller. The simplest tools base only on the external prices from e-shops and e-commerce platforms like Google Shopping, Amazon, or eBay. If a seller wants to be the cheapest or in TOP3 cheapest sellers on a given platform, they can change prices accordingly. On the other hand, if the system sees that competitors offer their products at much higher prices, it can increase the price, maximize margin, and keep the position of the price leader.

A similar case is when competitors are out of stock or products are not available. The pricing system detects this and uses the opportunity to increase the price.

Often, the dynamic pricing tool is integrated with shop software and thanks to this the tool knows how much product is left in the warehouse, and in case of ending of inventory, it can decrease the price to sell it out.

As you can guess, even in this area Artificial Intelligence found its place. Algorithms based on AI can gather such information as website traffic, can detect user’s IP and cookies, gather information from other shops or the number of sold products for a given time. The algorithm learns from the source of gathered data and in an optimum way adjusts the prices to the market needs.

An example of a system that detects users can be the prices of airline tickets. If somebody checks the prices of tickets a few times from a given computer and browser, prices in further searches can increase. Another example of dynamic pricing can be Uber, which adjusts prices of fares, according to the actual demand in a given area at the moment. The biggest difference is that Uber (probably) checks only its system, while dynamic pricing in e-commerce takes under consideration the competitors’ offers as well.

The other example of dynamic pricing can be a change in price depending on where the user came from. Entering the shop’s page from price comparison websites (e.g. Google Shopping), prices can be lower than during a direct entry. The algorithm can offer discounted prices for people from the chosen price comparison site, knowing that these customers look for the cheapest offers. When a customer comes directly to the e-shop’s page, the seller knows that he doesn’t have to lure him with the lowest price.

Another interesting solution using Dynamic pricing, which can be easily observed is setting different prices at chosen days of a week and different hours. Recently, quite popular became “night promotions”, which directly inform when the prices are lower.

In some particular industries, sellers can observe much higher sales during a weekend, thus they don’t compete with prices from Monday to Friday, to start a hard fight from Saturday morning to become competitive.

One could think that Dynamic Pricing works only online. But let us consider one scenario. Let’s imagine a shopping center, where you can find 3 shops in the electronics industry. All of them have a console X in their offer. However, if 2 out of 3 sell out the console, the last one can use the opportunity and either increase the price in the local shop or place advertisements in the shop window to inform customers that the particular console is available in this shop. Using proper algorithms, online tools can gather information about offline product availability from the biggest shops and use this data to maximize their profits.

To sum up, it is better to be aware of the fact that prices are not constant and can be easily and rapidly adjusted. It is better to use some time and check the prices on a price comparison platform, to be sure that you don’t overpay. If the product is a more expensive one, it is worth checking its price history to be sure that due to lack of inventory the prices didn’t peak recently.