Recommendation Engine

To better inform your customers about your product offering, adverts and offers are very important. Through printed media, online ads and newsletters you can inform the customer, but which products deserve extra attention? The optimal selection of products maximizes the amount of sales but a personalized selection is needed since every customer is unique. Recommender systems of Netflix, Amazon and Facebook show the enormous power of this personalized approach.

Through advanced machine learning techniques, ML2Grow can make this selection for you. Based on historic sales data of all customers our recommendation engine calculates for each customer the most effective selection of products to suggest. This selection can then be integrated into existing business processes.

Various studies have shown that recommender systems result in more sales and a positive effect on the diversity of purchases. It is not surprising then that more and more companies embrace this technology: if your competitors do this as well there may be a risk that your revenue decreases significantly. The following features characterize the solution of ML2Grow:

  • Service-based solution: integration via a simple JSON interface.
  • Ability to handle thousands of customers and products.
  • New products and customers are automatically taken into account.