Fact Combiner – algorithm-based sales booster 

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ABOUT THE PROJECT
One of the biggest challenges in the travel industry is how to deliver a given offer to the customer to make a purchase. In response to these needs, we have created Fact Combiner - an algorithm-based system that matches the offer to user behavior on the website using machine learning and AI. Eventually, the customer receives recommended trips to their needs, and the tour operator gains a satisfied customer and increases the value of the shopping cart and conversion rate. 
TECHNOLOGIES

MongoDB

Java

JavaScript

Node.js

Glassfish

INDUSTRY
Travel
SERVICES
Web Development
 
Data Analytics & Machine Learning
ABOUT THE PROJECT
One of the biggest challenges in the travel industry is how to deliver a given offer to the customer to make a purchase. In response to these needs, we have created Fact Combiner - an algorithm-based system that matches the offer to user behavior on the website using machine learning and AI. Eventually, the customer receives recommended trips to their needs, and the tour operator gains a satisfied customer and increases the value of the shopping cart and conversion rate. 
TECHNOLOGIES

MongoDB

Java

JavaScript

Node.js

Glassfish

INDUSTRY
Travel
SERVICES
Web Development
 
Data Analytics & Machine Learning

Let’s see our results

>60k
per day recommended products
120M
per month recorded interactions on the website
60%

of the users choose a recommended search

factcombiner_1

Key features of Fact Combiner

Recommending products to users

The tool automatically recommends products to users thanks to the Machine Learning mechanism, which learns from users’ behaviors, predicts future customer actions, and chooses the products of their preferences. How does it work? If enough data is collected, the association rule gets activated, and the algorithm compares the frequently browsed products and places similar offers next to each other. If the mechanism knows nothing about the user yet, it recommends the TOP options. The client can view the results as a “recommended offers” bar on the main product page. The system generates recommendations for nearly 60k users in real time.

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

01

Fact Combiner positively influenced the travel deals sales process thanks to additional functionalities that improved the overall customer experience and conversion rate;

02

Delivered valuable insights about e-commerce customer behavior that would be difficult to learn without automation tools;

03

Higher customer satisfaction and loyalty thanks to faster, more efficient, and satisfying searching and purchasing processes;

04

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. 

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