Algorithmic pricing: Features and benefits

Algorithmic pricing: Features and benefits

03/07/2022 - Artificial Intelligence

Process automation arrived long ago and looks set to stay for e-commerce and online retailers. An example of this is automated pricing management using tools that incorporate certain types of artificial intelligence that allow changes to be made to optimise catalogue prices. Dynamic pricing is just one of the options available for you to use, known as algorithmic pricing. Here’s how to get the most out of these pricing strategies.

What is ‘algorithmic pricing’?

Algorithmic pricing is the trend that encompasses all pricing strategies that depend on an automated system to set their price adjustments. In all cases, algorithmic pricing includes the use of artificial intelligence processes and data processing, that enable you to establish rules to execute the desired changes. In other words, they use an algorithm to do this.

Algorithmic pricing has been one of the determining factors in increasing the growing proportion of businesses that make multiple price changes. The More Amazon Effects: Online Competition and Pricing Behaviors study by Alberto Cavallo explains that the frequency of monthly price changes in online businesses in the U.S.A. increased from 15% to nearly 30% between 2008 and 2017.


3 benefits of ‘algorithmic pricing’

Algorithmic pricing-based strategies have a positive impact on online sales. Both retail and digital businesses (marketplace, comparison websites, dropshipping platforms …) have benefited from dynamic changes in their pricing strategies.

  1. Unification of the market. Prices adjusted by automated techniques allow the market to work within ever more comparable ranges. Analysis of competition and knowledge of potential buyers make stores’ sales prices similar.
  2. Personalisation. Algorithmic pricing has the advantage that prices can be personalised on a case-by-case basis. By analysing the context in which the price change occurs and its effect on the sale, various consumer types are identified, to offer them appropriate prices accordingly.
  3. Safe implementation. Automated algorithmic pricing techniques work according to standards set by the business. Large-scale data processing techniques, big data, and machine learning help regulate decision-making.
algorithmic pricing strategies

What are ‘algorithmic pricing’ strategies?

Different techniques exist to help implement an algorithmic pricing strategy, depending on the main objective of each retailer. In any case, a pricing strategy simulator can be key to successful pricing, as the effectiveness of the pricing strategy can be tested in real circumstances.

For algorithmic pricing you can put the following types of strategies in place:

  1. Dynamic pricing: Dynamic pricing strategies allow you to adjust each price according to changes in catalogue, demand, sales volume, and market fluctuations.
  2. Personalised pricing: Prices tailored to the user’s profile based on their purchase history, relationship to the product, and decision-making process.
  3. Discriminatory pricing: Strategy based on the offer and promotion of certain products according to fixed characteristics of the buyer, such as origin, demographic profile, etc.

In short, automated pricing allows you to maximise market possibilities based on context, competition, and user expectations. Try it with Reactev.

Category: Artificial Intelligence

Tags: pricing

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