SALESmanago Copernicus – Machine Learning & AI


The ultimate product recommendation mechanism based on artificial intelligence and developed specially for eCommerce and online shops.

Artificial intelligence is transforming Marketing Automation. New generation solutions such as SALESmanago Copernicus that are based on AI and Machine Learning support the traditional marketing activities and permit perfect delivery of tailored offers to the customers at the right time. AI Recommendations, the new dashboard in SALESmanago Copernicus module, provide advanced data about AI-based product recommendations in your online store.

Next generation predictive marketing based on self-learning algorithms

Machine Learning & AI engine SALESmanago Copernicus uses complex algorithms to analyze transactional and behavioral data and prepares product recommendations for the store customers. Not only the specific customer behaviour is analyzed, but also the correlations between other users who have bought the same product, for instance. The data about transactions of other customers’ with similar interests make it possible for the algorithm to forecast which products may hold the attention of the purchaser in the future. Additionally, artificial intelligence is in constant self-development process, so the predictions and recommendations become more precise with time.

The mechanism prepares offers on the basis of 5 recommendation types:

  • Collaborative filtering – this type of recommendation involves two approaches. The first one called Product-Product is connected with probability and frequency of co-occurrence of different products (not necessarily similar to each other). The second approach is called User-Product approach and it shows which products may interest a user based on the interests of other users who have similar profiles to the chosen one. Generally speaking, the idea behind this type of AI recommendation is to offer products based on the similarity of users and concurrence of various products.
  • Most frequently bought after visit other – based on the product the customer is currently displaying on the website, the system analyzes purchases of other customers who also displayed this product and recommends the products purchased by other users to this particular user.
  • Most frequently visited together – as the name suggests these are the products that are often viewed together by all users. The system offers products which were browsed by other users along with these products.
  • Most frequently bought together – the system analyzes the products the customer has purchased. And also the system analyzes the products which have been purchased by other users along with the same products.
  • Mixed statistics with weight – the mechanism behind this recommendation type employs all previously enlisted types of recommendations and additionally assigns a weight for each action. The value of the weight can be determined by you. How does it translate into practice? The system creates connections and analyses products bought by the contact, recommending in the first place several products which are probable to be bought, then products which the user wants to see and so on and so forth prioritizing the rest of the products with regard to the actions.

Predicting Customer Journey models and AI-driven recommendations

SALESmanago Copernicus – Machine Learning & AI module can automatically select appropriate products for each customer. Moreover, the Marketing Automation system stores information on the behavior of anonymous website visitors, allowing the content to be personalized even for unidentified contacts. This means that all customers are subject to analysis of their Behavior Mechanisms.

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SALESmanago Copernicus recommendation analytics

Inbound and outbound marketing activities greatly benefit from the additional information gained in the process. The analytical panel guarantees the access to the charts that present the connections between products and categories. Moreover, the charts present the correlations of recommended products in the most popular categories. Additionally, the panel lets you choose a product or category to which the system prepares similar products which recommendation power between products and the main product is the highest.

Business benefits

  • Impress your customers with personalized product offers
  • Get real results and grow your sales by adjusting your marketing to what consumers want to see
  • Achieve the maximum customer lifetime value in each case
  • Streamline your marketing budget
  • Find out which products and categories are the most successful
  • Learn about your customers’ individual preferences and predict their next purchase

Customer Reference

„Support from Project Manager helped me a lot ! My PM is very patience with me explaining in details everything I needed and saved me a lot of time! Without this willingness to help I wouldn’t use Sales Manago as much as I do now because I don’t have time to watch all the video tutorials or to read the articles. I needed a solution to my issues now, and support gave it to me. I am extremely grateful for that help and it is a real pleasure working with my PM. Co-working with my support team improved a lot my satisfaction from the product.”
Valentina Makarestova, Marketing Manager, Balkan Services