Rules based vs. machine learning based pricing

Machine-learning

Rule-based pricing or rule engines are the traditional way of pricing in retail and online retail. Most online retailers change prices using this methodology. In this case prices are changed according to static formulas. This type of pricing can also be dynamic. For example, a retailer can set the rule to always match the third cheapest competitor price. This way prices can change everyday or even multiple times per hour. There are two main shortfalls of rules based pricing:

  • It takes a lot of manual effort to administer the price formulas and
  • price rules are often based on parameters that are easy to measure but entail only limited information about customer behavior

 

Retailers that use rule-based pricing give away profit and revenue potential because their pricing is not based on the willingness-to-pay of their customers.

Next generation dynamic pricing based on machine learning algorithms

On the contrary, advanced machine learning algorithms can measure the willingness-to-pay of customers. To be exact they measure price elasticity which is the key to set optimal prices. Combined with advanced forecasting algorithms they can model the price demand curve of each product. Based on this, companies can steer prices automatically towards their company goals. They do not have to create rules and test their performance. Their pricing reacts dynamically and automatically to a change of customer behavior. As a result, retailers apply discounts more differentiated and smarter.

Real AI vs. fake AI

Customers who source machine learning based pricing software need to be aware that machine learning and AI are buzz words that are often used inflationary. A basic AI system analyzes existing data and uncovers hidden patterns. Based on this, it can make predictions or even prescribes actions. More advanced algorithms use methods called deep learning and reinforcement learning. They outperform basic AI methods by gaining more insights out of existing data. They are also able to process larger amounts of data sources. Most importantly, these methods continuously learn and improve their results.

At 7Learnings we have more than 10 years experience with machine learning technology. We helped some of Europe’s leading online retailers to apply them and use them to optimize prices. If you want to learn more about the potential of next generation dynamic pricing and see it in action, reach out to us and book a product demo.