STACC is developing a variety of artificial intelligence solutions for companies doing business in the field of e-commerce. These can for example, bring more visitors to the e-shop, increase turnover by increasing the cost of the shopping cart and, in the end, improve the customer experience, too.
Each innovative idea or new technology costs money, so it is reasonable to assess its profitability before making an investment. That is why our team has developed a profitability calculator for STACC`s recommendation system, with which you can try out different scenarios and see how would it work for your business.
Have you ever wondered how does Amazon recommend products you might be interested in purchasing? Recommender systems study patterns of behavior to know what the customer of the web store will prefer from among a collection of products they either have an experience with before or not.
A large number of marketers segment their customers based on specific features and send a personalized email with different content to each segment. Imagine taking personalization to a level where each customer is a segment on his own and will receive special offers directed specially to him in the mailbox.
Any web store that wants to stand out in the market should consider the implementation of machine learning, because in order to remain competitive, one has to know better and better their customer, make precise management decisions to perform business goals, and ensure the quality of products and services.
Online recommender system for maximizing customer lifetime value
Offline recommender system for personalized email marketing campaigns
Online recommender system, which combines the capabilities of both up-sell and cross-sell