
MongoDB
Java
JavaScript
Node.js
Glassfish
MongoDB
Java
JavaScript
Node.js
Glassfish
Let’s see our results
of the users choose a recommended search

Key features of Fact Combiner
Recommending products to users
Improving marketing campaigns
The algorithm displays the suggestions for the client and gathers data for automation marketing purposes. What kind of data does it collect? Everything that may matter in the marketing context: how many people were looking at the particular trip or their geolocation data, the frequency of entries, the browsed and booked offers, and many more. Based on this, the algorithm creates a marketing profile of the client that can be later used for optimizing marketing campaigns. The client can also access statistics anytime they need it to analyze them.
Results
Fact Combiner positively influenced the travel deals sales process thanks to additional functionalities that improved the overall customer experience and conversion rate;
Delivered valuable insights about e-commerce customer behavior that would be difficult to learn without automation tools;
Higher customer satisfaction and loyalty thanks to faster, more efficient, and satisfying searching and purchasing processes;
The e-commerce product search algorithm has already created about 600k behavioral profiles and nearly 4 million anonymous profiles. All data is being updated in real-time. Tour operator tracks 120 million user actions each month, allowing it to improve and simplify the shopping process for users and achieve better results.


Next steps
Fact Combiner is dedicated not only to the travel industry but can be easily adapted to any business where online consumer decisions are being made. What’s essential Fact Combiner includes offline bookings, too, and can analyze data and generate real-time stats and reports. So, we expect it to grow in the upcoming years, and we will keep implementing the solution for the next clients according to their needs and business models.