Dynamic Pricing

Use AI to price complex commercial products

Increase revenue
Improve profitability
Automate & optimise pricing

Dynamic pricing

Table of contents

AI for dynamic pricing

Dynamic pricing is a commercial strategy whereby businesses adjust the prices of their goods and/or services on the basis of factors such as demand, supply and competitor pricing, to name a few. The goal is to maximise revenue and profit.

It's a complex strategy to implement. Not only does it require businesses to collect, analyse and action a large amount of data; it's highly sensitive. Setting prices too high or low can alienate customers, leading to lost profits and damaged reputation.

AI dynamic pricing helps businesses overcome the challenges of traditional dynamic pricing methods. AI is the best tool when it comes to analysing large, complex datasets. At Datasparq, we typically using reinforcement learning (RL) when building AI dynamic pricing solutions.


AI-powered dynamic pricing solutions can provide a number of benefits to businesses, including:

  • Increased profits: By setting optimal prices based on demand and supply, AI solutions can help businesses to maximise their profits.
  • Improved customer satisfaction: By offering competitive prices, AI solutions can help businesses to improve customer satisfaction.
  • Reduced costs: AI solutions can help businesses to reduce their costs by automating the pricing process and eliminating the need for manual price adjustments.
  • Increased agility: AI solutions can help businesses to respond quicker to changes in demand and market conditions.

Who it helps

AI dynamic pricing solutions can benefit businesses in a wide range of industries, including retail, travel, hospitality and transportation. They benefit businesses of all sizes, from small businesses to large enterprises.

Some of the specific roles that can benefit from AI-powered dynamic pricing solutions include:

  • Revenue managers
  • Pricing analysts
  • Marketing managers
  • Sales managers
  • Product managers

How it works

A typical Datasparq dynamic pricing solution works by analysing the following types of data:

  • Historical sales data
  • Real-time demand data (such as website traffic, social media engagement and competitor pricing)
  • Cost data
  • Operational data (such as inventory levels and shipping costs)
  • Competitor data

This data is then used to train a reinforcement learning (RL) model to predict optimal prices for products and services. As our dynamic pricing solution uses reinforcement learning, the model learns from the results of prices it sets. That means the solution typically gets increasingly effective over time.

Getting started

As outlined above, AI dynamic pricing solutions set optimal prices, helping businesses maximise profits, improve customer satisfaction, reduce costs and increase agility.

Contact us today for a free consultation.

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Guide to AI-Powered Dynamic Pricing ⚡️

Learn how AI can boost your revenue by up to 7% in 12-24 weeks.

  • Prepare: Discover the seven steps to preparing to implement an AI pricing solution in your business
  • Implement: Learn how reinforcement learning can be used for dynamic pricing
  • Examples: Find out how AI dynamic pricing has helped other businesses boost their revenue
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