Highlights
FINN.no delivers personalised targeted ads based on machine-learning models in real-time with Cassandra.

50M monthly visits

Personalization use case

Cloud-native deployment

Launched in 2000, FINN.no is the leading classified advertising company in Norway with around 50 million monthly visits. It provides customers with the ability to buy and sell goods and services, covering everything from everyday products through to boats, houses, and used cars and services like loans, utilities, and travel.

A critical cluster that supports the company’s personalization engine for advertisements runs on Apache Cassandra. This application uses data such as a user’s preferences and advertising history to shape the experience that customers have while they visit the site.

“This personalization engine is essential to us as a company. It helps us to up sell products that might be interesting to customers, it can deliver sponsored products to target customer groups, and it supports other companies in the group with their personalization services too,” explained Espen Amble Kolstad, Senior Developer, FINN.no. “It supports around twenty percent of our traffic as a site, which represents millions of interactions, so it’s an important part of the business.”

FINN.no uses Cassandra alongside its data lake as part of its data science pipeline. The Data Intelligence team takes data from the data lake and builds their models in Python. These models are then loaded into the company’s API framework and used alongside the data held in the Cassandra cluster.

“Our Cassandra installation takes the most recent data from our user behavior and data models and uses this to personalize the adverts that users can see, so it has to work in real-time as people are browsing,” stated Kolstad.

“Our data scientists create and test their models based on data from our data lake. Once we have the models finalised, they get published and used as part of our API, which then gets combined with our Cassandra implementation. The combination of our API, which contains all our data models, and our Cassandra instance, now runs our recommendation engine. We use Cassandra as it provides the read performance and the resiliency that we require,” according to Benjamin Weima Lager, Technical Domain Expert – Data Intelligence, Finn.no.

This helps the Data Intelligence team deliver the speed of recommendations that the FINN.no team requires, as well as supporting more organizations within the Schibsted Group in making use of personalization and data science in their day-to-day activities.

“Personalization can be hard, but it is essential for our team and for our business. Getting it right takes a mix of data science, infrastructure, and customer value,” stated Kolstad. The system powered by Cassandra helps deliver recommendations that customers think are valuable.